GemGIS API Reference#

The API reference provides an overview of all functions and methods implemented in GemGIS.

gemgis.download_gemgis_data module#

Contributors: Alexander Jüstel, Arthur Endlein Correia, Florian Wellmann, Marius Pischke.

GemGIS is a Python-based, open-source spatial data processing library. It is capable of preprocessing spatial data such as vector data raster data, data obtained from online services and many more data formats. GemGIS wraps and extends the functionality of packages known to the geo-community such as GeoPandas, Rasterio, OWSLib, Shapely, PyVista, Pandas, and NumPy.

GemGIS is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

GemGIS is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License (LICENSE) for more details.

gemgis.download_gemgis_data.create_pooch(storage_url: str, files: List[str], target: str)#

Create pooch class to fetch files from a website.

Parameters

storage_url (str) – Base URL for the remote data source.
files (List[str]) – A record of the files that are managed by this Pooch.
target (str, default: '') – The path to the local data storage folder, e.g. target='Documents/gemgis/'.

Returns

Pooch class.

Return type

pooch.core.Pooch

See also

download_tutorial_data: Download the GemGIS data for each tutorial.

gemgis.download_gemgis_data.download_tutorial_data(filename: str, dirpath: str = '', storage_url: str = 'https://rwth-aachen.sciebo.de/s/AfXRsZywYDbUF34/download?path=%2F')#

Download the GemGIS data for each tutorial.

Parameters

filename (str) – File name to be downloaded by pooch, e.g. filename='file.zip'.
dirpath (str, default: '') – Path to the directory where the data is being stored, default to the directory where the notebook is located, e.g. dirpath='Documents/gemgis/'.
storage_url (str, default ‘https://rwth-aachen.sciebo.de/s/AfXRsZywYDbUF34/download?path=%2F’) – URL to the GemGIS data storage, default is the RWTH Aachen University Sciebo Cloud Storage.

See also

create_pooch: Create pooch class to fetch files from a website.

gemgis.gemgis module#

Contributors: Alexander Jüstel, Arthur Endlein Correia, Florian Wellmann, Marius Pischke

class gemgis.gemgis.GemPyData(model_name=None, crs=None, extent=None, resolution=None, interfaces=None, orientations=None, section_dict=None, customsections=None, dem=None, stack=None, surface_colors=None, is_fault=None, geolmap=None, basemap=None, faults=None, tectonics=None, raw_i=None, raw_o=None, raw_dem=None, wms=None, slope=None, hillshades=None, aspect=None, contours=None)#

Bases: object

This class creates an object with attributes containing i.e. the interfaces or orientations that can directly be passed to a GemPy Model

The following attributes are available: - model_name: string - the name of the model - crs: string - the coordinate reference system of the model - interfaces: pd DataFrame - DataFrame containing the interfaces for the GemPy model - orientations: pd DataFrame - DataFrame containing the orientations for the GemPy model - extent: list - List containing the minx, maxx, miny, maxy, minz and maxz values - section_dict: dict - Dictionary containing the section_dict for custom sections for the GemPy model - customsections: GeoDataFrame containing the Linestrings or Endpoints of custom sections - resolution: list - List containing the x,y and z resolution of the model - dem: Union[string, array] - String containing the path to the DEM or array containing DEM values - stack: dict - Dictionary containing the layer stack associated with the model - surface_colors: dict - Dictionary containing the surface colors for the model - is_fault: list - list of surface that are classified as faults - geolmap: Union[GeoDataFrame,np.ndarray rasterio.io.Datasetreader] - GeoDataFrame or array containing the geological map either as vector or raster data set - basemap: Union[np.ndarray rasterio.io.Datasetreader] - Array or rasterio object containing a base map of the area - tectonics: GeoDataFrame - GeoDataFrame containing the LineStrings of fault traces - raw_i: GeoDataFrame - GeoDataFrame containing the raw interfaces point data - raw_o: GeoDataFrame - GeoDataFrame containing the raw orientations data - raw_dem: GeoDataFrame or np.ndarray - Raw dem data such as topographic lines or (gdf) or raster (array) - slope: np.ndarray - array containing the slope values of the DEM - hillshades: np.ndarray - array containing the color values of the hillshades - aspect: np.ndarray - array containing the aspect values of the DEM - faults: GeoDataFrame containing the Linestrings or vertices of faults - wms: np.ndarray containing data obtained from a WMS layer - contours: GeoDataFrame containing the contour lines of the model area

set_extent(minx: Union[int, float] = 0, maxx: Union[int, float] = 0, miny: Union[int, float] = 0, maxy: Union[int, float] = 0, minz: Union[int, float] = 0, maxz: Union[int, float] = 0, **kwargs)#

Setting the extent for a model :param minx - float defining the left border of the model: :param maxx - float defining the right border of the model: :param miny - float defining the upper border of the model: :param maxy - float defining the lower border of the model: :param minz - float defining the top border of the model: :param maxz - float defining the bottom border of the model:

Kwargs:: gdf - GeoDataFrame from which bounds the extent will be set

Returns: extent - list with resolution values

set_resolution(x: int, y: int, z: int)#

Setting the resolution for a model :param x - int defining the resolution in X direction: :param y - int defining the resolution in Y direction: :param z - int defining the resolution in Z direction:

Returns: [x, y, z] - list with resolution values

to_gempy_df(gdf: geopandas.geodataframe.GeoDataFrame, cat: str, **kwargs)#

Converting a GeoDataFrame into a Pandas DataFrame ready to be read in for GemPy :param gdf - gpd.geodataframe.GeoDataFrame containing spatial information: :param formation names and orientation values: :param cat - str/type of point data: :type cat - str/type of point data: interfaces or orientations

Kwargs:: dem -

Returns: df - interface or orientations DataFrame ready to be read in for GemPy

to_section_dict(gdf: geopandas.geodataframe.GeoDataFrame, section_column: str = 'section_name', resolution=None)#

Converting custom sections stored in shape files to GemPy section_dicts :param gdf - gpd.geodataframe.GeoDataFrame containing the points or lines of custom sections: :param section_column - string containing the name of the column containing the section names: :param resolution - list containing the x: :param y resolution of the custom section:

Returns: section_dict containing the section names, coordinates and resolution

to_surface_color_dict(path: str, **kwargs)#

Create GemPy surface color dict from a qml file :param path: str/path to the qml file

Returns: dict containing the surface color values for GemPy
Return type: surface_color_dict

gemgis.misc module#

Contributors: Alexander Jüstel, Arthur Endlein Correia, Florian Wellmann, Marius Pischke.

gemgis.misc.get_meta_data(page: List[str]) → list#

This function is used to extract the name, coordinates and depths, of one page with one well provided by the Geological Survey NRW. It is using the extracted page as string as input data and returns floats of the coordination data and the well name

Parameters: page (List[str]) – List containing the strings of the borehole pdf
Returns: data – List containing the extracted data values
Return type: list

New in version 1.0.x.

Changed in version 1.1.7.

Adapting positions of coordinate values.

Example

>>> # Loading Libraries and split data
>>> import gemgis as gg
>>> # Split Data - from get_meta_data_df(...)
>>> data = data.split()
>>> data = '#'.join(data)
>>> data = data.split('-Stammdaten')
>>> data = [item.split('|')[0] for item in data]
>>> data = [item.split('#') for item in data]

>>> # Filter out wells without Stratigraphic Column
>>> data = [item for item in data if 'Beschreibung' in item]

>>> # Get Coordinates of data
>>> coordinates = [get_meta_data(page=item) for item in data]
>>> coordinates[0]
['DABO_196747', 'B.19ESCHWEILER', '19', 70.3, 32310019.32, 5633520.32, 130.0,
2521370.0, 5631910.0, 'Karbon', 'Eschweiler [TK 5103]', 'Eschweiler/Weißweiler',
'ungeprüfte Angabe aus dem Bohrarchiv', 'ungeprüfte Angabe aus dem Bohrarchiv',
'Exploration, Lagerstättenerkundung', 'Bohrung', '', 'vertraulich, offen nach Einzelfallprüfung;',
'Übertragung eines alten Archivbestandes', '1', 'Schichtdaten von guter Qualität; genaue stratigrafische
Einstufung aufgestellt', '', '', 'Original-Schichtenverzeichnis liegt vor']

See also

load_pdf: Loading PDF data as string
get_meta_data_df: Getting the meta data of wells as DataFrame
get_stratigraphic_data: Getting the stratigraphic data of a well
get_stratigraphic_data_df: Getting the stratigraphic data of wells as DataFrame

gemgis.misc.get_meta_data_df(data: str, name: str = 'GD', return_gdf: bool = True) → Union[pandas.core.frame.DataFrame, geopandas.geodataframe.GeoDataFrame]#

Function to create a dataframe with coordinates and meta data of the different boreholes

Parameters

data (str) – String containing the borehole data
name (str) – Prefix for custom index for boreholes, default ‘GD’, e.g. name='GD'
return_gdf (bool) – Variable to return GeoDataFrame. Options include: True or False, default set to True

Returns

coordinates_dataframe_new – (Geo-)DataFrame containing the coordinates and meta data of the boreholes

Return type

Union[pd.DataFrame, gpd.geodataframe.GeoDataFrame]

New in version 1.0.x.

Changed in version 1.1.7.

Fixed bug in parsing PDF.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> content = gg.misc.load_pdf(path='file.pdf')
>>> content
'Stammdaten    -     2521/ 5631/ 1         -          Bnum: 196747  .  .  Objekt / Name :B. 19  ESCHWEILER
Bohrungs- / Aufschluß-Nr. :19  Archiv-Nr. :  Endteufe [m] :70.30  Stratigraphie der Endteufe :Karbon
.  TK 25 :Eschweiler [TK 5103]  Ort / Gemarkung :Eschweiler/Weißweiler  GK   R...'

>>> # Creating meta data DataFrame
>>> gdf = gg.misc.get_meta_data_df(data=content, name='GD', return_gdf=True)
>>> gdf
    Index   DABO No.    Name            Number  Depth   X           Y           Z       X_GK        Y_GK        ... Kind    Procedure   Confidentiality                             Record Type                             Lithlog Version Quality                                             Drilling Period Remarks Availability Lithlog                    geometry
0   GD0001  DABO_196747 B.19ESCHWEILER  19      70.30   32310019.32 5633520.32  130.00  2521370.00  5631910.00  ... Bohrung             vertraulich, offen nach Einzelfallprüfung;  Übertragung eines alten Archivbestandes 1               Schichtdaten von guter Qualität; genaue strati...                           Original-Schichtenverzeichnis liegt vor POINT (32310019.320 5633520.320)
1   GD0002  DABO_196748 B.16ESCHWEILER  16      37.61   2310327.14  5632967.35  122.00  2521700.00  5631370.00  ... Bohrung             vertraulich, offen nach Einzelfallprüfung;  Übertragung eines alten Archivbestandes 1               Schichtdaten von guter Qualität; genaue strati...                           Original-Schichtenverzeichnis liegt vor POINT (32310327.140 5632967.350)

See also

load_pdf: Loading PDF data as string
get_meta_data: Getting the meta data of a well
get_stratigraphic_data: Getting the stratigraphic data of a well
get_stratigraphic_data_df: Getting the stratigraphic data of wells as DataFrame

gemgis.misc.get_stratigraphic_data(text: list, symbols: List[Tuple[str, str]], formations: List[Tuple[str, str]]) → list#

Function to retrieve the stratigraphic data from borehole logs

Parameters

text (list) – String containing the borehole data
symbols (List[Tuple[str, str]]) – List of symbols to be removed from list of strings
formations (List[Tuple[str, str]]) – List of categorized formations

Returns

data – List of extracted data values

Return type

list

New in version 1.0.x.

Changed in version 1.1.7.

Fixed bug in parsing PDF.

Example

>>> # Loading Libraries and getting the stratigraphic data of borehole
>>> import gemgis as gg
>>> data = gg.misc.get_stratigraphic_data(text=text, symbols=symbols, formations=formations)

See also

load_pdf: Loading PDF data as string
get_meta_data: Getting the meta data of a well
get_meta_data_df: Getting the meta data of wells as DataFrame
get_stratigraphic_data_df: Getting the stratigraphic data of wells as DataFrame

gemgis.misc.get_stratigraphic_data_df(data: str, name: str, symbols: List[Tuple[str, str]], formations: List[Tuple[str, str]], remove_last: bool = False, return_gdf: bool = True) → Union[pandas.core.frame.DataFrame, geopandas.geodataframe.GeoDataFrame]#

Function to create a dataframe with coordinates and the stratigraphy of the different boreholes

Parameters

data (list) – List containing the strings of the borehole log
name (str) – Name for index reference, e.g. name='GD'
symbols (List[Tuple[str, str]]) – List of tuples with symbols to be filtered out
formations (List[Tuple[str, str]]) – List of tuples with formation names to be replaced
remove_last – Variable to remove the last value of each well. Options include: True or False, default set to False

Returns

strata – (Geo-)DataFrame containing the coordinates and the stratigraphy of the boreholes

Return type

Union[pd.DataFrame, gpd.geodataframe.GeoDataFrame]

New in version 1.0.x.

Changed in version 1.1.7.

Fixed bug in parsing PDF.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> content = gg.misc.load_pdf(path='file.pdf')
>>> content
'Stammdaten    -     2521/ 5631/ 1         -          Bnum: 196747  .  .  Objekt / Name :B. 19  ESCHWEILER
Bohrungs- / Aufschluß-Nr. :19  Archiv-Nr. :  Endteufe [m] :70.30  Stratigraphie der Endteufe :Karbon
.  TK 25 :Eschweiler [TK 5103]  Ort / Gemarkung :Eschweiler/Weißweiler  GK   R...'

>>> # Getting stratigraphic data DataFrame
>>> gdf = gg.misc.get_stratigraphic_data_df(data=data, name='GD', symbols=symbols, formations=formations)
>>> gdf
    Index   Name            X           Y           Z       Altitude    Depth   formation   geometry
0   GD0001  B.19ESCHWEILER  32310019.32 5633520.32  125.30  130.00      70.30   Quaternary  POINT (32310019.320 5633520.320)
1   GD0001  B.19ESCHWEILER  32310019.32 5633520.32  66.50   130.00      70.30   Miocene     POINT (32310019.320 5633520.320)
2   GD0001  B.19ESCHWEILER  32310019.32 5633520.32  60.90   130.00      70.30   Oligocene   POINT (32310019.320 5633520.320)

See also

load_pdf: Loading PDF data as string
get_meta_data: Getting the meta data of a well
get_meta_data_df: Getting the meta data of wells as DataFrame
get_stratigraphic_data: Getting the stratigraphic data of a well

gemgis.misc.load_formations(path: str) → list#

Loading formations for extraction of borehole data

Parameters: path (str) – Path to the file containing the symbols for extracting the borehole data, e.g. path='boreholes.txt'
Returns: formations – List of tuples with formations to be extracted
Return type: list

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> formations = gg.misc.load_formations(paths='formations.txt')

>>> # Inspecting the formations
>>> formations
[('UnterdevonKalltalFormation', 'KalltalFM'),
('Bölling', 'Quaternary'),
('AtlantikumAuenterrassen[TalterrasseInselterrasse]', 'Quaternary'),
('nullLöss', 'Quaternary'),
('Waal', 'Quaternary')]

gemgis.misc.load_pdf(path: str, save_as_txt: bool = True) → str#

Load PDF file containing borehole data.

Parameters

path (str) – Name of the PDF file, e.g. path='file.pdf'.
save_as_txt (bool, default: True) – Variable to save the extracted data as txt file. Options include: True or False.

Returns

Extracted page content from borehole data.

Return type

str

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> content = gg.misc.load_pdf(path='file.pdf')
>>> content
'Stammdaten    -     2521/ 5631/ 1         -          Bnum: 196747  .  .  Objekt / Name :B. 19  ESCHWEILER
Bohrungs- / Aufschluß-Nr. :19  Archiv-Nr. :  Endteufe [m] :70.30  Stratigraphie der Endteufe :Karbon
.  TK 25 :Eschweiler [TK 5103]  Ort / Gemarkung :Eschweiler/Weißweiler  GK   R...'

See also

get_meta_data: Get the meta data of a well.
get_meta_data_df: Get the meta data of wells as DataFrame.
get_stratigraphic_data: Get the stratigraphic data of a well.
get_stratigraphic_data_df: Get the stratigraphic data of wells as DataFrame.

gemgis.misc.load_symbols(path: str) → list#

Loading symbols for extraction of borehole data

Parameters: path (str) – Path to the file containing the symbols for extracting the borehole data, e.g. path='boreholes.txt'
Returns: symbols – List of tuples with symbols to be removed
Return type: list

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> symbols = gg.misc.load_symbols(paths='symbols.txt')

>>> # Inspecting the symbols
>>> symbols
[('.m ', ''),
(', ', ''),
('; ', ''),
(': ', ''),
('/ ', ''),
('? ', ''),
('! ', ''),
('-"- ', ''),
('" ', ''),
('% ', ''),
('< ', ''),
('> ', ''),
('= ', ''),
('~ ', ''),
('_ ', ''),
('Â° ', ''),
("' ", '')]

gemgis.postprocessing module#

Contributors: Alexander Jüstel, Arthur Endlein Correia, Florian Wellmann, Marius Pischke

gemgis.postprocessing.calculate_dip_and_azimuth_from_mesh(mesh: pyvista.core.pointset.PolyData) → pyvista.core.pointset.PolyData#

Calculating dip and azimuth values for a mesh and setting them as scalars for subsequent plotting

Parameters: mesh (pv.core.pointset.PolyData) – PyVista Mesh for which the dip and the azimuth will be calculated
Returns: mesh – PyVista Mesh with appended dips and azimuths
Return type: pv.core.pointset.PolyData

New in version 1.0.x.

gemgis.postprocessing.clip_fault_of_gempy_model(geo_model, fault: str, which: str = 'first', buffer_first: Union[int, float] = None, buffer_last: Union[int, float] = None, i_size: Union[int, float] = 1000, j_size: Union[int, float] = 1000, invert_first: bool = True, invert_last: bool = False) → Union[pyvista.core.pointset.PolyData, List[pyvista.core.pointset.PolyData]]#

Clip fault of a GemPy model.

Parameters

geo_model (gp.core.model.Project) – GemPy Model containing the faults.
fault (str) – String or list of strings containing the name of faults to be clipped, e.g. faults='Fault1'.
which (str, default: 'first') – Parameter to decide which end of the faults to clip. Options include 'first', 'last', or both, e.g. 'which='first'.
buffer_first (Union[int, float]) – Int or float value or list of values to clip the fault/s behind the first interface point, e.g. 'buffer_first=500'.
buffer_last (Union[int, float]) – Int or float value or list of values to clip the fault/s behind the last interface point, e.g. 'buffer_last=500'.
i_size (Union[int, float]) – Size of the plane in the i direction.
j_size (Union[int, float]) – Size of the plane in the j direction.
invert_first (bool, default: 'True') – Invert clipping for first plane.
invert_last (bool, default: 'False') – Invert clipping for second plane.

Returns

Clipped faults.

Return type

pv.core.pointset.PolyData

New in version 1.1.

See also

create_plane_from_interface_and_orientation: Create PyVista plane from GemPy interface and orientations DataFrames.
translate_clipping_plane: Translate clipping plane.

Example

gemgis.postprocessing.create_attributes(keys: list, values: list) → list#

Creating a list of attribute dicts

Parameters

key (list) – List of keys to create the attributes with
values (list) – List of values for the dicts

Returns

dicts – List containing the attribute dicts

Return type

list

New in version 1.0.x.

gemgis.postprocessing.create_plane_from_interface_and_orientation_dfs(df_interface: pandas.core.frame.DataFrame, df_orientations: pandas.core.frame.DataFrame, i_size: Union[int, float] = 1000, j_size: Union[int, float] = 1000) → pyvista.core.pointset.PolyData#

Create PyVista plane from GemPy interface and orientations DataFrames.

Parameters

df_interface (pd.DataFrame) – GemPy Pandas DataFrame containing the interface point for the plane creation.
df_orientations (pd.DataFrame) – GemPy Pandas Dataframe containing the orientations for the plane creation.
i_size (Union[int, float]) – Size of the plane in the i direction.
j_size (Union[int, float]) – Size of the plane in the j direction.

Returns

plane (pv.core.pointset.PolyData) – Plane for clipping the fault.
azimuth (Union[int, float]) – Azimuth of the fault.

New in version 1.1.

See also

clip_fault_of_gempy_model: Clip fault of a GemPy model.
translate_clipping_plane: Translate clipping plane.

Example

gemgis.postprocessing.create_subelement(parent: xml.etree.ElementTree.Element, name: str, attrib: dict)#

Creating Subelement

Parameters

parent (xml.etree.ElementTree.Element) – Parent Element
name (str) – Name of the Element
attrib (dict) – Dict containing the attributes of the element

New in version 1.0.x.

gemgis.postprocessing.create_symbol(parent: xml.etree.ElementTree.Element, color: str, symbol_text: str, outline_width: str = '0.26', alpha: str = '1')#

Creating symbol entry

Parameters

parent (xml.etree.ElementTree.Element) – Parent Element
color (str) – RGBA values provided as string
outline_width (str) – Outline width of the polygons
alpha (str) – Opacity value
symbol_text (str) – Number of the symbol

New in version 1.0.x.

gemgis.postprocessing.crop_block_to_topography(geo_model) → pyvista.core.pointset.UnstructuredGrid#

Cropping GemPy solutions block to topography

Parameters: geo_model (gp.core.model.Project) –
Returns: grid
Return type: pv.core.pointset.UnstructuredGrid

New in version 1.0.x.

gemgis.postprocessing.extract_borehole(geo_model, geo_data: gemgis.gemgis.GemPyData, loc: List[Union[int, float]], **kwargs)#

Extracting a borehole at a provided location from a recalculated GemPy Model

Parameters

geo_model (gp.core.model.Project) – Previously calculated GemPy Model
geo_data (gemgis.GemPyData) – GemGIS GemPy Data class used to calculate the previous model
loc (list) – List of X and Y point pairs representing the well location
zmax (Union[int, float]) – Value indicating the maximum depth of the well, default is minz of the previous model
res (int) – Value indicating the resolution of the model in z-direction

Returns

sol (np.ndarray)
well_model (gp.core.model.Project)
depth_dict (dict)

New in version 1.0.x.

gemgis.postprocessing.extract_lithologies(geo_model, extent: list, crs: Union[str, pyproj.crs.crs.CRS]) → geopandas.geodataframe.GeoDataFrame#

Extracting the geological map as GeoDataFrame

Parameters

geo_model (gp.core.model.Project) – GemPy geo_model
extent (list) – Extent of geo_model
crs (Union[str, pyproj.crs.crs.CRS]) – Coordinate References System

Returns

lith – Lithologies of the geological map

Return type

gpd.geodataFrame.GeoDataFrame

New in version 1.0.x.

gemgis.postprocessing.extract_orientations_from_mesh(mesh: pyvista.core.pointset.PolyData, crs: Union[str, pyproj.crs.crs.CRS]) → geopandas.geodataframe.GeoDataFrame#

Extracting orientations (dip and azimuth) from PyVista Mesh

Parameters

mesh (pv.core.pointset.PolyData) – PyVista Mesh from which the orientations will be extracted
crs (Union[str, pyproj.crs.crs.CRS]) – Coordinate reference system of the returned GeoDataFrame, crs='EPSG:4326'

Returns

gdf_orientations – GeoDataFrame consisting of the orientations

Return type

gpd.geodataframe.GeoDataFrame

New in version 1.0.x.

gemgis.postprocessing.save_model(geo_model, path)#

Function to save the model parameters to files

Parameters

geo_model (gp.core.model.Project) – GemPy model to be saved
path (str) – Path/folder where data is stored, e.g. path='model/'

New in version 1.0.x.

gemgis.postprocessing.save_qgis_qml_file(gdf: geopandas.geodataframe.GeoDataFrame, value: str = 'formation', color: str = 'color', outline_width: Union[int, float] = 0.26, alpha: Union[int, float] = 1, path: str = '')#

Creating and saving a QGIS Style File/QML File based on a GeoDataFrame

Parameters

gdf (gpd.geoDataFrame.GeoDataFrame) – GeoDataFrame containing the Polygons, formation names and color values
value (str) – Name of the column used to categorize the layer
color (str) – Name of the column containing the color values
outline_width (Union[int, float]) – Outline width of the polygons
path (str) – Path where the QML file will be stored

New in version 1.0.x.

gemgis.postprocessing.translate_clipping_plane(plane: pyvista.core.pointset.PolyData, azimuth: Union[int, float, numpy.int64], buffer: Union[int, float]) → pyvista.core.pointset.PolyData#

Translate clipping plane.

Parameters

plane (pv.core.pointset.PolyData) – Clipping Plane.
azimuth (Union[int, float, np.int64]) – Orientation of the Fault.
buffer (Union[int, float, type(None)]) – Buffer to translate the clipping plane along the strike of the fault.

Returns

Translated clipping plane.

Return type

pv.core.pointset.PolyData

New in version 1.1.

See also

create_plane_from_interface_and_orientation: Create PyVista plane from GemPy interface and orientations DataFrames.
clip_fault_of_gempy_model: Clip fault of a GemPy model.

Example

gemgis.raster module#

Contributors: Alexander Jüstel, Arthur Endlein Correia, Florian Wellmann

GemGIS is a Python-based, open-source geographic information processing library. It is capable of preprocessing spatial data such as vector data (shape files, geojson files, geopackages), raster data, data obtained from WMS services or XML/KML files. Preprocessed data can be stored in a dedicated Data Class to be passed to the geomodeling package GemPy in order to accelerate to model building process.

gemgis.raster.calculate_aspect(raster: Union[numpy.ndarray, rasterio.io.DatasetReader], extent: List[Union[int, float]] = None, band_no: int = 1) → numpy.ndarray#

Calculating the aspect based on a digital elevation model/raster

Parameters

raster (np.ndarray, rasterio.io.DatasetReader) – NumPy array or rasterio object containing the elevation data
extent (List[Union[int, float]]) – List of minx, maxx, miny and maxy coordinates representing the raster extent if raster is passed as array, e.g. extent=[0, 972, 0, 1069]
band_no (int) – Band number of the raster to be used for calculating the hillshades, e.g. band_no=1, default is 1

Returns

aspect – NumPy array containing the aspect values

Return type

np.ndarray

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import rasterio
>>> raster = rasterio.open(fp='raster.tif')

>>> # Calculating the aspect of a raster
>>> aspect = gg.raster.calculate_aspect(raster=raster)
>>> aspect
array([[246.37328, 245.80156, 245.04022, ..., 269.87958, 270.11377,
270.32904],....], dtype=float32)

See also

calculate_hillshades: Calculating the hillshades of a raster
calculate_slope: Calculating the slope of a raster
calculate_difference: Calculating the difference between two rasters

gemgis.raster.calculate_difference(raster1: Union[numpy.ndarray, rasterio.io.DatasetReader], raster2: Union[numpy.ndarray, rasterio.io.DatasetReader], flip_array: bool = False) → numpy.ndarray#

Calculating the difference between two rasters

Parameters

raster1 (np.ndarray) – First array
raster2 (np.ndarray) – Second array
flip_array (bool) – Variable to flip the array. Options include: True or False, default set to False

Returns

array_diff – Array containing the difference between array1 and array2

Return type

np.ndarray

New in version 1.0.x.

Example

>>> # Loading Libraries and Files
>>> import gemgis as gg
>>> import rasterio
>>> raster1 = rasterio.open(fp='raster1.tif')
>>> raster2 = rasterio.open(fp='raster2.tif')

>>> # Calculate difference between two rasters
>>> difference = gg.raster.calculate_difference(raster1=raster1, raster2=raster2)
>>> difference
array([[-10., -10., -10., ..., -10., -10., -10.],.....], dtype=float32)

See also

calculate_hillshades: Calculating the hillshades of a raster
calculate_slope: Calculating the slope of a raster
calculate_aspect: Calculating the aspect of a raster

gemgis.raster.calculate_hillshades(raster: Union[numpy.ndarray, rasterio.io.DatasetReader], extent: List[Union[int, float]] = None, azdeg: Union[int, float] = 225, altdeg: Union[int, float] = 45, band_no: int = 1) → numpy.ndarray#

Calculating Hillshades based on digital elevation model/raster

Parameters

raster (np.ndarray, rasterio.io.DatasetReader) – NumPy array or rasterio object containing the elevation data
extent (List[Union[int, float]]) – List of minx, maxx, miny and maxy points representing the extent of the raster if raster is passed as array, e.g. extent=[0, 972, 0, 1069]
azdeg (Union[int, float]) – Azimuth value for the light source direction, e.g. azdeg=225, default is 225 degrees
altdeg (Union[int, float]) – Altitude value for the light source, e.g. altdeg=45, default is 45 degrees
band_no (int) – Band number of the raster to be used for calculating the hillshades, e.g. band_no=1, default is 1

Returns

hillshades – NumPy array containing the hillshade color values

Return type

np.ndarray

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import rasterio
>>> raster = rasterio.open(fp='raster.tif')

>>> # Calculating hillshades from raster
>>> hillshades = gg.raster.calculate_hillshades(raster=raster)
>>> hillshades
array([[250.04817, 250.21147, 250.38988, ..., 235.01764, 235.0847 ,
235.0842 ], ....], dtype=float32)

See also

calculate_slope: Calculating the slope of a raster
calculate_aspect: Calculating the aspect of a raster
calculate_difference: Calculating the difference between two rasters

gemgis.raster.calculate_slope(raster: Union[numpy.ndarray, rasterio.io.DatasetReader], extent: List[Union[int, float]] = None, band_no: int = 1) → numpy.ndarray#

Calculating the slope based on digital elevation model/raster

Parameters

raster (np.ndarray, rasterio.io.DatasetReader) – NumPy array or rasterio object containing the elevation data
extent (List[Union[int, float]]) – List of minx, maxx, miny and maxy coordinates representing the raster extent if raster is passed as array, e.g. extent=[0, 972, 0, 1069]
band_no (int) – Band number of the raster to be used for calculating the hillshades, e.g. band_no=1, default is 1

Returns

slope – NumPy array containing the slope values

Return type

np.ndarray

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import rasterio
>>> raster = rasterio.open(fp='raster.tif')

>>> # Calculating the slope of a raster
>>> slope = gg.raster.calculate_slope(raster=raster)
>>> slope
array([[37.092472, 36.95191 , 36.649662, ..., 21.988844, 22.367924,
22.584248],....], dtype=float32)

See also

calculate_hillshades: Calculating the hillshades of a raster
calculate_aspect: Calculating the aspect of a raster
calculate_difference: Calculating the difference between two rasters

gemgis.raster.clip_by_bbox(raster: Union[rasterio.io.DatasetReader, numpy.ndarray], bbox: List[Union[int, float]], raster_extent: List[Union[int, float]] = None, save_clipped_raster: bool = False, path: str = 'raster_clipped.tif', overwrite_file: bool = False, create_directory: bool = False) → numpy.ndarray#

Clipping a rasterio raster or np.ndarray by a given extent

Parameters

raster (Union[rasterio.io.DatasetReader, np.ndarray]) – Array or Rasterio object to be clipped
bbox (List[Union[int, float]]) – Bounding box of minx, maxx, miny, maxy values to clip the raster, e.g. bbox=[0, 972, 0, 1069]
raster_extent (List[Union[int, float]]) – List of float values defining the extent of the raster, default None, e.g. raster_extent=[0, 972, 0, 1069]
save_clipped_raster (bool) – Variable to save the raster after clipping. Options include: True or False, default set to False
path (str) – Path where the raster is saved, e.g. path='raster_clipped.tif'
overwrite_file (bool) – Variable to overwrite an already existing file. Options include: True or False, default set to False
create_directory (bool) – Variable to create a new directory of directory does not exist Options include: True or False, default set to False

Returns

raster_clipped – Clipped array after clipping

Return type

np.ndarray

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import rasterio
>>> raster = rasterio.open(fp='raster.tif')
>>> raster.read(1).shape
(275, 250)

>>> # Creating bounding box and defining raster extent
>>> bbox = [250, 500, 250, 500]
>>> raster_extent = [0, 972, 0, 1069]

>>> # Clipping raster by bounding box
>>> raster_clipped = gg.raster.clip_by_bbox(raster=raster, bbox=bbox, raster_extent=raster_extent)
>>> raster_clipped.shape
(65, 65)

See also

clip_by_polygon: Clipping raster by a Shapely Polygon

gemgis.raster.clip_by_polygon(raster: Union[rasterio.io.DatasetReader, numpy.ndarray], polygon: shapely.geometry.polygon.Polygon, raster_extent: List[Union[int, float]] = None, save_clipped_raster: bool = False, path: str = 'raster_clipped.tif', overwrite_file: bool = False, create_directory: bool = False) → numpy.ndarray#

Clipping/masking a rasterio raster or np.ndarray by a given shapely Polygon

Parameters

raster (Union[rasterio.io.DatasetReader, np.ndarray]) – Array or Rasterio object to be clipped
polygon (shapely.geometry.polygon.Polygon) – Shapely polygon defining the extent of the data, e.g. polygon = Polygon([(0, 0), (1, 1), (1, 0)])
raster_extent (List[Union[int, float]]) – List of float values defining the extent of the raster, default None, e.g. raster_extent=[0, 972, 0, 1069]
save_clipped_raster (bool) – Variable to save the raster after clipping, default False. Options include: True or False, default set to False
path (str) – Path where the raster is saved, e.g. path='raster_clipped.tif
overwrite_file (bool) – Variable to overwrite an already existing file. Options include: True or False, default set to False
create_directory (bool) – Variable to create a new directory of directory does not exist Options include: True or False, default set to False

Returns

raster_clipped – Clipped array after clipping

Return type

np.ndarray

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import rasterio
>>> from shapely.geometry import Polygon
>>> raster = rasterio.open(fp='raster.tif')
>>> raster.read(1).shape
(275, 250)

>>> # Creating Shapely Polygon and defining raster extent
>>> polygon = Polygon([(250, 250), (500, 250), (500, 500), (250, 500)])
>>> raster_extent = [0, 972, 0, 1069]

>>> # Clipping the raster by a Shapely Polygon
>>> raster_clipped = gg.raster.clip_by_polygon(raster=raster, polygon=polygon, raster_extent=raster_extent)
>>> raster_clipped.shape
(65, 65)

See also

clip_by_bbox: Clipping raster by a Bounding Box

gemgis.raster.create_filepaths(dirpath: str, search_criteria: str, create_directory: bool = False) → List[str]#

Retrieving the file paths of the tiles to load and to process them later

Parameters

dirpath (str) – Path to the folder where tiles are stored, e.g. dirpath='Documents/images/'
search_criteria (str) – Name of the files including file ending, use * for autocompletion by Python, e.g. search_criteria='tile*.tif'
create_directory (bool) – Variable to create a new directory if directory does not exist Options include: True or False, default set to False

Returns

filepaths – List of file paths

Return type

List[str]

New in version 1.0.x.

Example

>>> # Loading Libraries
>>> import gemgis as gg

>>> # Defining filepath
>>> filepath = 'Documents/images/'

>>> # Creating list of filepaths based on search criteria
>>> filepaths = gg.raster.create_filepaths(dirpath=filepath, search_criteria='tile*.tif')
>>> filepaths
['Documents/images//tile_292000_294000_5626000_5628000.tif',
'Documents/images//tile_292000_294000_5628000_5630000.tif',
'Documents/images//tile_292000_294000_5630000_5632000.tif',
'Documents/images//tile_294000_296000_5626000_5628000.tif']

gemgis.raster.create_src_list(dirpath: str = '', search_criteria: str = '', filepaths: List[str] = None, create_directory: bool = False) → List[rasterio.io.DatasetReader]#

Creating a list of source files

Parameters

dirpath (str) – Path to the folder where tiles are stored, e.g. dirpath='Documents/images/'
search_criteria (str) – Name of the files including file ending, use * for autocompletion by Python, e.g. search_criteria='tile*.tif'
filepaths (List[str]) – List of strings containing file paths
create_directory (bool) – Variable to create a new directory of directory does not exist Options include: True or False, default set to False

Returns

src_files – List containing the loaded rasterio datasets

Return type

List[rasterio.io.DatasetReader]

New in version 1.0.x.

Example

>>> # Importing Libraries
>>> import gemgis as gg

>>> # Defining filepath
>>> filepath = 'Documents/images/'

>>> # Creating List of filepaths
>>> filepaths = gg.raster.create_filepaths(dirpath=filepath, search_criteria='tile*.tif')
>>> filepaths
['Documents/images//tile_292000_294000_5626000_5628000.tif',
'Documents/images//tile_292000_294000_5628000_5630000.tif',
'Documents/images//tile_292000_294000_5630000_5632000.tif',
'Documents/images//tile_294000_296000_5626000_5628000.tif']

>>> # Creating list of loaded rasterio objects
>>> src_list = gg.raster.create_src_list(filepaths=filepaths)
>>> src_list
[<open DatasetReader name='Documents/images/tile_292000_294000_5626000_5628000.tif' mode='r'>,
<open DatasetReader name='Documents/images/tile_292000_294000_5628000_5630000.tif' mode='r'>,
<open DatasetReader name='Documents/images/tile_292000_294000_5630000_5632000.tif' mode='r'>,
<open DatasetReader name='Documents/images/tile_294000_296000_5626000_5628000.tif' mode='r'>,

gemgis.raster.extract_contour_lines_from_raster(raster: Union[rasterio.io.DatasetReader, numpy.ndarray, str], interval: int, extent: Union[Sequence[float], None, Sequence[int]] = None, target_crs: Union[str, pyproj.crs.crs.CRS, rasterio.crs.CRS] = None) → geopandas.geodataframe.GeoDataFrame#

Extracting contour lines from raster with a provided interval.

Parameters

raster (Union[rasterio.io.DatasetReader, np.ndarray, str]) – Raster from which contour lines are extracted
extent (Optional[Sequence[float, int]]) – If raster given as array: values (minx, maxx, miny, maxy) to define raster extent, e.g. extent =[0, 972, 0, 1069]
target_crs (Union[str, pyproj.crs.crs.CRS, rasterio.crs.CRS]) – If raster given as array: name of the CRS is required to project values to coordinates of GeoDataFrame, e.g. target_crs='EPSG:4647'
interval (int) – Given interval for the extracted contour lines, e.g. interval=50

Returns

gdf_lines – GeoDataFrame containing the extracted contour lines as LineStrings

Return type

gpd.GeoDataFrame

New in version 1.0.x.

gemgis.raster.merge_tiles(src_files: List[rasterio.io.DatasetReader], extent: List[Union[int, float]] = None, res: int = None, nodata: Union[float, int] = None, precision: int = None, indices: int = None, method: str = 'first') → Tuple[numpy.ndarray, affine.Affine]#

Merging downloaded tiles to mosaic

Parameters

src_files (List[rasterio.io.DatasetReader]) – List of rasterio datasets to be merged
extent (List[Union[float, int]]) – Bounds of the output image (left, bottom, right, top). If not set, bounds are determined from bounds of input rasters, e.g. extent=[0, 972, 0, 1069], default is None
res (int) – Output resolution in units of coordinate reference system. If not set, the resolution of the first raster is used. If a single value is passed, output pixels will be square. e.g. res=50, default is None
nodata (Union[float, int]) – nodata value to use in output file. If not set, uses the nodata value in the first input raster, e.g. nodata=9999.0, default is None
precision (int) – Number of decimal points of precision when computing inverse transform, e.g. precision=2, default is None
indices (int) – Bands to read and merge, e.g. indices=1, default is None
method (str) – Method on how to merge the tiles, e.g. method='first', default is 'first'

Returns

mosaic (np.ndarray) – Array containing the merged tile data
transform (affine.Affine) – Affine Transform of the merged tiles

New in version 1.0.x.

Example

>>> # Loading Libraries
>>> import gemgis as gg

>>> # Creating filepath
>>> filepath = 'Documents/images/'

>>> # Creating list of filepaths
>>> filepaths = gg.raster.create_filepaths(dirpath=filepath, search_criteria='tile*.tif')
>>> filepaths
['Documents/images//tile_292000_294000_5626000_5628000.tif',
'Documents/images//tile_292000_294000_5628000_5630000.tif',
'Documents/images//tile_292000_294000_5630000_5632000.tif',
'Documents/images//tile_294000_296000_5626000_5628000.tif']

>>> # Creating list of loaded rasterio objects
>>> src_list = gg.raster.create_src_list(filepaths=filepaths)
>>> src_list
[<open DatasetReader name='Documents/images/tile_292000_294000_5626000_5628000.tif' mode='r'>,
<open DatasetReader name='Documents/images/tile_292000_294000_5628000_5630000.tif' mode='r'>,
<open DatasetReader name='Documents/images/tile_292000_294000_5630000_5632000.tif' mode='r'>,
<open DatasetReader name='Documents/images/tile_294000_296000_5626000_5628000.tif' mode='r'>,

>>> # Merging tiles
>>> mosaic, transform = gg.raster.merge_tiles(src_files=src_list)

>>> # Inspecting the mosaic data
>>> mosaic
array([[200.72, 200.73, 200.72, ..., 204.42, 204.45, 204.45],
[200.74, 200.74, 200.75, ..., 204.43, 204.44, 204.48]
[200.76, 200.76, 200.76, ..., 204.42, 204.48, 204.5 ],
...,
[329.15, 328.86, 328.74, ..., 242.45, 242.38, 242.28],
[329.29, 329.06, 328.87, ..., 242.45, 242.39, 242.31],
[329.47, 329.3 , 329.09, ..., 242.42, 242.37, 242.32]],
dtype=float32)

>>> # Inspecting the transform of the mosaic
>>> transform
Affine(1.0, 0.0, 292000.0,
0.0, -1.0, 5632000.0)

gemgis.raster.read_asc(path: Union[str, pathlib.Path]) → dict#

Function to read GoCAD .asc files

Parameters: path (Union[str, Path]) – Path to asc file, e.g. path='raster.asc'
Returns: data – Dict containing the array data, the extent, resolution and nodata_val of the raster
Return type: dict

New in version 1.0.x.

Example

>>> # Loading Libraries and Files
>>> import gemgis as gg
>>> data = gg.raster.read_asc('raster.asc')

>>> # Inspecting the content of the dict, here we only see the nodata_vals for now
>>> data['Data']
array([[-99999., -99999., -99999., ..., -99999., -99999., -99999.],
[-99999., -99999., -99999., ..., -99999., -99999., -99999.],
[-99999., -99999., -99999., ..., -99999., -99999., -99999.],
...,
[-99999., -99999., -99999., ..., -99999., -99999., -99999.],
[-99999., -99999., -99999., ..., -99999., -99999., -99999.],
[-99999., -99999., -99999., ..., -99999., -99999., -99999.]])

>>> data['Extent']
[-42250, 306000, 279000, 867000]

>>> data['Resolution']
250

>>> data['Nodata_val']
-99999

See also

read_ts: Reading a GoCAD TSurface File
read_msh: Reading a Leapfrog Mesh File
read_zmap: Reading Petrel ZMAP Files

gemgis.raster.read_msh(path: Union[str, pathlib.Path]) → Dict[str, numpy.ndarray]#

Function to read Leapfrog .msh files - https://help.leapfrog3d.com/Geo/4.3/en-GB/Content/meshes/meshes.htm

Parameters: path (Union[str, Path]) – Path to msh file, e.g. path='mesh.msh'
Returns: data – Dict containing the mesh data
Return type: Dict[str, np.ndarray]

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> data = gg.raster.read_msh('mesh.msh')
>>> data
{'Tri': array([[    0,     1,     2],
[    0,     3,     1],
[    4,     3,     0],
...,
[53677, 53672, 53680],
[53679, 53677, 53680],
[53673, 53672, 53677]]),
'Location': array([[ 1.44625109e+06,  5.24854344e+06, -1.12743862e+02],
[ 1.44624766e+06,  5.24854640e+06, -1.15102216e+02],
[ 1.44624808e+06,  5.24854657e+06, -1.15080548e+02],
...,
[ 1.44831008e+06,  5.24896679e+06, -1.24755449e+02],
[ 1.44830385e+06,  5.24896985e+06, -1.33694397e+02],
[ 1.44829874e+06,  5.24897215e+06, -1.42506587e+02]])}

See also

read_ts: Reading a GoCAD TSurface File
read_asc: Reading ESRI ASC files
read_zmap: Reading Petrel ZMAP Files

gemgis.raster.read_raster_gdb(path: str, crs: Union[str, pyproj.crs.crs.CRS, rasterio.crs.CRS] = None, path_out: str = '')#

Read Raster from OpenFileGDB.

Parameters

path (str) – Path to the OpenFileGDB.
crs (str, pyproj.crs.crs.CRS, rasterio.crs.CRS) – Coordinate Reference System of the dataset.
path_out (str) – Output folder path

New in version 1.1.1.

gemgis.raster.read_ts(path: Union[str, pathlib.Path]) → Tuple[list, list]#

Function to read GoCAD .ts files

Parameters

path (Union[str, Path]) – Path to ts file, e.g. path='mesh.ts'

Returns

vertices (list) – Pandas DataFrames containing the vertex data
faces (list) – NumPy arrays containing the faces data

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> vertices, faces = gg.raster.read_ts('mesh.ts')

>>> # Inspecting the vertices
>>> vertices
    id  X           Y           Z
0   0   297077.41   5677487.26  -838.50
1   1   297437.54   5676992.09  -816.61

>>> # Inspecting the faces
>>> faces
array([[    0,     1,     2],
[    3,     2,     4],
[    1,     5,     6],...,
[40335, 40338, 40336],
[40339, 40340, 40341],
[40341, 40342, 40339]])

See also

read_msh: Reading a Leapfrog Mesh File
read_asc: Reading ESRI ASC files
read_zmap: Reading Petrel ZMAP Files

gemgis.raster.read_zmap(path: Union[str, pathlib.Path]) → dict#

Reading Petrel ZMAP Files

Parameters: path (Union[str, Path]) – Path to dat file, e.g. path='raster.dat'
Returns: data – Dict containing the array data, the extent, array dimension, resolution and nodata_val of the raster
Return type: dict

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> data = gg.raster.read_zmap(path='file.dat')

>>> # Inspecting the content of the dict, here we only see the nodata_vals for now
>>> data
{'Data': array([[nan, nan, nan, ..., nan, nan, nan],
[nan, nan, nan, ..., nan, nan, nan],
[nan, nan, nan, ..., nan, nan, nan],
...,
[nan, nan, nan, ..., nan, nan, nan],
[nan, nan, nan, ..., nan, nan, nan],
[nan, nan, nan, ..., nan, nan, nan]]),
 'Extent': [-42250.0, 278750.0, 306000.0, 866750.0],
 'Resolution': [250.0, 250.0],
 'Nodata_val': 0.1000000E+31,
 'Dimensions': (2244, 1285),
 'CRS': 'Amersfoort * EPSG-Nld / RD New [28992,1672]',
 'Creation_date': '21/10/2019',
 'Creation_time': '16',
 'File_name': 'TOP_DINANTIAN_TVD_final'}

See also

read_ts: Reading a GoCAD TSurface File
read_msh: Reading a Leapfrog Mesh File
read_asc: Reading ESRI ASC files

gemgis.raster.reproject_raster(path_in: str, path_out: str, dst_crs: Union[str, pyproj.crs.crs.CRS, rasterio.crs.CRS], overwrite_file: bool = False, create_directory: bool = False)#

Reprojecting a raster into different CRS

Parameters

path_in (str) – Path to the source file, e.g. path_in='Images/'
path_out (str) – Path for the destination file, e.g. path_out='Images/'
dst_crs (Union[str, pyproj.crs.crs.CRS, rasterio.crs.CRS]) – CRS of the destination file, e.g. dst_crs='EPSG:25832'
overwrite_file (bool) – Variable to overwrite an already existing file. Options include: True or False, default set to False
create_directory (bool) – Variable to create a new directory of directory does not exist Options include: True or False, default set to False

New in version 1.0.x.

Changed in version 1.1: Fixing an issue where the file would be closed too soon, see https://github.com/cgre-aachen/gemgis/issues/294

Example

>>> # Loading Libraries
>>> import gemgis as gg

>>> # Reprojecting raster
>>> gg.raster.reproject_raster(path_in='raster_in.tif', path_out='raster_out.tif', dst_crs='EPSG:4326')

gemgis.raster.resize_by_array(raster: Union[numpy.ndarray, rasterio.io.DatasetReader], array: Union[numpy.ndarray, rasterio.io.DatasetReader]) → numpy.ndarray#

Rescaling raster to the size of another raster

Parameters

raster (Union[np.ndarray, rasterio.io.DatasetReader]) – Raster that is being resized
array (Union[np.ndarray, rasterio.io.DatasetReader]) – Raster with a size that the raster is being resized to

Returns

array_resized – Resized array

Return type

np.ndarray

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import rasterio
>>> import numpy as np
>>> raster = rasterio.open(fp='raster.tif')
>>> raster.read(1).shape
(275, 250)

>>> # Creating array
>>> array = np.zeros(100).reshape((10,10))
>>> array.shape
(10, 10)

>>> # Resizing a raster by an array
>>> raster_resized = gg.raster.resize_by_array(raster=raster, array=array)
>>> raster_resized.shape
(10, 10)

See also

resize_raster: Resizing a raster

gemgis.raster.resize_raster(raster: Union[numpy.ndarray, rasterio.io.DatasetReader], width: int, height: int) → numpy.ndarray#

Resizing raster to given dimensions

Parameters

array (Union[np.ndarray, rasterio.io.DatasetReader]) – Array that will be resized
width (int) – Width of the resized array, e.g. width=100
height (int) – Height of the resized array, e.g. height=100

Returns

array_resized – Resized array

Return type

np.ndarray

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import rasterio
>>> import numpy as np
>>> raster = rasterio.open(fp='raster.tif')
>>> raster.read(1).shape
(275, 250)

>>> # Resizing raster
>>> raster_resized = gg.raster.resize_raster(raster=raster, width=10, height=10)
>>> raster_resized.shape
(10, 10)

See also

resize_by_array: Resizing a raster by the shape of another array

gemgis.raster.sample_from_array(array: numpy.ndarray, extent: Sequence[float], point_x: Union[float, int, list, numpy.ndarray], point_y: Union[float, int, list, numpy.ndarray]) → Union[numpy.ndarray, float]#

Sampling the value of a np.ndarray at a given point and given the arrays true extent

Parameters

array (np.ndarray) – Array containing the raster values
extent (list) – List containing the values for the extent of the array (minx,maxx,miny,maxy), e.g. extent=[0, 972, 0, 1069]
point_x (Union[float, int, list, np.ndarray]) – Object containing the x coordinates of a point or points at which the array value is obtained, e.g. point_x=100
point_y (Union[float, int, list, np.ndarray]) – Object containing the y coordinates of a point or points at which the array value is obtained, e.g. point_y=100

Returns

sample – Value/s of the raster at the provided position/s

Return type

Union[np.ndarray, float]

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import rasterio
>>> raster = rasterio.open(fp='raster.tif')

>>> # Getting array data
>>> array = raster.read()

>>> # Sampling values from an array
>>> value = gg.raster.sample_from_array(array=array, extent=[0, 972, 0, 1069], point_x=500, point_y=500)
>>> value
562.0227

See also

sample_from_rasterio: Sample values from rasterio object
sample_randomly: Sample randomly from rasterio object or NumPy array
sample_orientations: Sample orientations from raster
sample_interfaces: Sample interfaces from raster

gemgis.raster.sample_from_rasterio(raster: rasterio.io.DatasetReader, point_x: Union[float, int, list, numpy.ndarray], point_y: Union[float, int, list, numpy.ndarray], sample_outside_extent: bool = True, sample_all_bands: bool = False) → Union[list, float]#

Sampling the value of a rasterio object at a given point within the extent of the raster

Parameters

raster (rasterio.io.DatasetReader) – Rasterio Object containing the height information
point_x (list, np.ndarray, float, int) – Object containing the x coordinates of a point or points at which the array value is obtained, e.g. point_x=100
point_y (list, np.ndarray, float, int) – Object containing the y coordinates of a point or points at which the array value is obtained, e.g. point_y=100
sample_outside_extent (bool) – Allow sampling outside the extent of the rasterio object. Options include: True or False, default set to True
sample_all_bands (bool) – Allow sampling from all bands returning Options include: True or False, default set to False

Returns

sample – Value/s of the raster at the provided position/s

Return type

list, float

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import rasterio
>>> raster = rasterio.open(fp='raster.tif')

>>> # Sampling values from a rasterio object
>>> value = gg.raster.sample_from_rasterio(raster=raster, point_x=500, point_y=500)
>>> value
561.646728515625

See also

sample_from_array: Sample values from NumPy array
sample_randomly: Sample randomly from rasterio object or NumPy array
sample_orientations: Sample orientations from raster
sample_interfaces: Sample interfaces from raster

gemgis.raster.sample_interfaces(raster: Union[numpy.ndarray, rasterio.io.DatasetReader], extent: List[Union[int, float]] = None, point_x: Union[float, int, list, numpy.ndarray] = None, point_y: Union[float, int, list, numpy.ndarray] = None, random_samples: int = None, formation: str = None, seed: int = None, sample_outside_extent: bool = False, crs: Union[str, pyproj.crs.crs.CRS, rasterio.crs.CRS] = None) → geopandas.geodataframe.GeoDataFrame#

Sampling interfaces from a raster

Parameters

raster (Union[np.ndarray, rasterio.io.DatasetReader) – Raster or arrays from which points are being sampled
extent (List[Union[int, float]]) – List containing the extent of the raster (minx, maxx, miny, maxy), e.g. extent=[0, 972, 0, 1069]
point_x (Union[float, int, list, np.ndarray]) – Object containing the x coordinates of a point or points at which the array value is obtained, e.g. point_x=100, default is None
point_y (Union[float, int, list, np.ndarray]) – Object containing the y coordinates of a point or points at which the array value is obtained, e.g. point_y=100, default is None
random_samples (int) – Number of random samples to be drawn, e.g. random_samples=10, default is None
formation (str) – Name of the formation the raster belongs to, e.g. formation='Layer1', default is None
seed (int) – Integer to set a seed for the drawing of random values, e.g. seed=1, default is None
sample_outside_extent (bool) – Allow sampling outside the extent of the rasterio object. Options include: True or False, default is False
crs (Union[str, pyproj.crs.crs.CRS, rasterio.crs.CRS]) – Coordinate reference system to be passed to the GeoDataFrame upon creation, e.g. crs='EPSG:4647

Returns

gdf – GeoDataFrame containing the sampled interfaces

Return type

gpd.geodataframe.GeoDataFrame

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import rasterio
>>> raster = rasterio.open(fp='raster.tif')

>>> # Sampling interfaces from an array or rasterio object
>>> gdf = gg.raster.sample_interfaces(raster=raster, point_x=500, point_y=500)
>>> gdf
    X       Y       Z       geometry
0   500.00  500.00  561.65  POINT (500.000 500.000)

See also

sample_from_array: Sample values from NumPy array
sample_from_rasterio: Sample values from rasterio object
sample_randomly: Sample randomly from rasterio object or NumPy array
sample_orientations: Sample orientations from raster

gemgis.raster.sample_orientations(raster: Union[numpy.ndarray, rasterio.io.DatasetReader], extent: List[Union[int, float]] = None, point_x: Union[float, int, list, numpy.ndarray] = None, point_y: Union[float, int, list, numpy.ndarray] = None, random_samples: int = None, formation: str = None, seed: int = None, sample_outside_extent: bool = False, crs: Union[str, pyproj.crs.crs.CRS, rasterio.crs.CRS] = None) → geopandas.geodataframe.GeoDataFrame#

Sampling orientations from a raster

Parameters

raster (Union[np.ndarray, rasterio.io.DatasetReader) – Raster or arrays from which points are being sampled
extent (List[Union[int, float]]) – List containing the extent of the raster (minx, maxx, miny, maxy), e.g. extent=[0, 972, 0, 1069]
point_x (Union[float, int, list, np.ndarray]) – Object containing the x coordinates of a point or points at which the array value is obtained, e.g. point_x=100, default is None
point_y (Union[float, int, list, np.ndarray]) – Object containing the y coordinates of a point or points at which the array value is obtained, e.g. point_y=100, default is None
random_samples (int) – Number of random samples to be drawn, e.g. random_samples=10, default is None
formation (str) – Name of the formation the raster belongs to, e.g. formation='Layer1', default is None
seed (int) – Integer to set a seed for the drawing of random values, e.g. seed=1, default is None
sample_outside_extent (bool) – Allow sampling outside the extent of the rasterio object. Options include: True or False, default is False
crs (Union[str, pyproj.crs.crs.CRS, rasterio.crs.CRS]) – Coordinate reference system to be passed to the GeoDataFrame upon creation, e.g. crs='EPSG:4647

Returns

gdf – GeoDataFrame containing the sampled interfaces

Return type

gpd.geodataframe.GeoDataFrame

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import rasterio
>>> raster = rasterio.open(fp='raster.tif')

>>> # Sampling orientations from an array or rasterio object
>>> gdf = gg.raster.sample_orientations(raster=raster, point_x=500, point_y=500)
>>> gdf
    X       Y       Z       geometry                dip     azimuth polarity
0   500.00  500.00  561.65  POINT (500.000 500.000) 19.26   145.55  1

See also

sample_from_array: Sample values from NumPy array
sample_from_rasterio: Sample values from rasterio object
sample_randomly: Sample randomly from rasterio object or NumPy array
sample_interfaces: Sample interfaces from raster

gemgis.raster.sample_randomly(raster: Union[numpy.ndarray, rasterio.io.DatasetReader], n: int = 1, extent: Optional[Sequence[float]] = None, seed: int = None) → tuple#

Sampling randomly from a raster (array or rasterio object) using sample_from_array or sample_from_rasterio and a randomly drawn point within the array/raster extent

Parameters

raster (Union[np.ndarray, rasterio.io.DatasetReader]) – NumPy Array or rasterio object containing the raster values
n (int) – Number of samples to be drawn, e.g. n=10, default 1
extent (Optional[Sequence[float]]) – List containing the values for the extent of the array (minx,maxx,miny,maxy), default is None, e.g. extent=[0, 972, 0, 1069]
seed (int) – Seed for the random variable for reproducibility, e.g. seed=1, default is None

Returns

sample – Float of sampled raster value and list containing the x- and y-points of the point where sample was drawn

Return type

tuple

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import rasterio
>>> raster = rasterio.open(fp='raster.tif')

>>> # Sampling randomly from an array or rasterio object
>>> value = gg.raster.sample_randomly(raster=raster, n=1)
>>> value
(617.0579833984375, [529.5110732824818, 717.7358438674542])

See also

sample_from_array: Sample values from NumPy array
sample_from_rasterio: Sample values from rasterio object
sample_orientations: Sample orientations from raster
sample_interfaces: Sample interfaces from raster

gemgis.raster.save_as_tiff(raster: numpy.ndarray, path: str, extent: Union[List[Union[int, float]], Tuple[Union[int, float]]], crs: Union[str, pyproj.crs.crs.CRS, rasterio.crs.CRS], nodata: Union[float, int] = None, transform=None, overwrite_file: bool = False, create_directory: bool = False)#

Saving a np.array as tif file

Parameters

array (np.ndarray) – Array containing the raster values
path (string) – Path and name of the file, e.g. path='mesh.msh'
extent (Union[List[Union[int, float]], Tuple[Union[int, float]]]) – List containing the bounds of the raster, e.g. extent=[0, 972, 0, 1069]
crs (Union[str, pyproj.crs.crs.CRS, rasterio.crs.CRS]) – CRS of the saved raster, e.g. crs='EPSG:4647'
nodata (Union[float, int]) – Nodata value of the raster, e.g. nodata=9999.0, default None
transform – Transform of the data, default is None
overwrite_file (bool) – Variable to overwrite an already existing file. Options include: True or False, default is False
create_directory (bool) – Variable to create a new directory of directory does not exist Options include: True or False, default set to False

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import rasterio
>>> raster = rasterio.open(fp='raster.tif')

>>> # Defining raster extent and CRS
>>> extent = [0, 972, 0, 1069]
>>> crs = 'EPSG:4326'

>>> # Saving raster as tiff
>>> gg.raster.save_as_tiff(raster=raster.read(1), path='raster_saved.tif', extent=extent, crs=crs)
Raster successfully saved

gemgis.utils module#

Contributors: Alexander Jüstel, Arthur Endlein Correia, Florian Wellmann, Marius Pischke

gemgis.utils.assign_properties(lith_block: numpy.ndarray, property_dict: dict) → numpy.ndarray#

Replacing lith block IDs with physical properties

Parameters

lith_block (np.ndarray) – GemPy lith block array containing the surface IDs
property_array (dict) – Dict containing the property values mapped to a surface ID

Returns

property_block – Array containing the properties

Return type

np.ndarray

New in version 1.0.x.

Example

>>> # Loading Libraries and lith_block plus reshaping
>>> import gemgis as gg
>>> import numpy as np
>>> lith_block = np.load('lith_block.npy').reshape(50,50,50)

>>> # Defining properties
>>> density_values = [0.1, 2.5, 3.0]

>>> # Creating dict
>>> density_dict = {k: v for k,v in zip(np.unique(np.round(lith_block)), density_values)}
>>> density_dict
{1.0: 0.1, 2.0: 2.5, 3.0: 3.0}

>>> # Assign properties
>>> property_block = gg.utils.assign_properties(lith_block=lith_block, property_dict=property_dict)

gemgis.utils.build_style_dict(classes: dict) → dict#

Building a style dict based on extracted style classes

Parameters: classes (dict) – Dict containing the styles of objects
Returns: styles – Dict containing styles for different objects
Return type: dict

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> column, classes = gg.utils.parse_categorized_qml(qml_name='style.qml')
>>>column
'formation'

>>> # Inspecting classes
>>> classes
{'Sand1': {'border_width_map_unit_scale': '3x:0,0,0,0,0,0',
'color': '179,90,42,255',
'joinstyle': 'bevel',
'offset': '0,0',
'offset_map_unit_scale': '3x:0,0,0,0,0,0',
'offset_unit': 'MM',
'outline_color': '102,51,24,255',
'outline_style': 'solid',
'outline_width': '0.26',
'outline_width_unit': 'MM',
'style': 'solid'},....}

>>> # Creating Style Dict
>>> style_dict = gg.utils.build_style_dict(classes=classes)
>>> style_dict
{'Sand1': {'color': '#b35a2a',
'color_rgb': [179, 90, 42],
'opacity': 1.0,
'weight': 0.26,
'fillColor': '#b35a2a',
'fillOpacity': 1.0},...}

See also

parse_categorized_qml: Reading the contents of a QGIS Style file (qml)
load_surface_colors: Loading surface colors as list
create_surface_color_dict: Creating dict with colors for each formation

gemgis.utils.calculate_lines(gdf: Union[geopandas.geodataframe.GeoDataFrame, pandas.core.frame.DataFrame], increment: Union[float, int], xcol: str = 'X', ycol: str = 'Y', zcol: str = 'Z') → geopandas.geodataframe.GeoDataFrame#

Function to interpolate strike lines

Parameters

gdf (Union[gpd.geodataframe.GeoDataFrame, pd.DataFrame]) – (Geo-)DataFrame containing existing strike lines
increment (Union[float, int]) – Increment between the strike lines, e.g. increment=50
xcol (str) – Name of X column, e.g. x='X'
ycol (str) – Name of X column, e.g. y='Y'
zcol (str) – Name of Z column, e.g. z='Z'

Returns

lines – GeoDataFrame with interpolated strike lines

Return type

gpd.geodataframe.GeoDataFrame

New in version 1.0.x.

Example

>>> import gemgis as gg
>>> import geopandas as gpd
>>> gdf = gpd.read_file(filename='lines5_strike.shp')
>>> gdf
    id  Z   formation   geometry
0   7   0   Coal1   LINESTRING (1642.839 2582.579, 2829.348 2205.937)
1   6   150 Coal1   LINESTRING (1705.332 1759.201, 2875.795 1406.768)
2   5   200 Coal1   LINESTRING (1017.766 1722.234, 2979.938 1137.003)
3   4   250 Coal1   LINESTRING (99.956 1763.424, 765.837 1620.705,...
4   3   200 Coal1   LINESTRING (1078.147 1313.501, 2963.048 752.760)

>>> gdf_interpolated = gg.utils.calculate_lines(gdf=gdf, increment=50)

gemgis.utils.calculate_number_of_isopoints(gdf: Union[geopandas.geodataframe.GeoDataFrame, pandas.core.frame.DataFrame], increment: Union[float, int], zcol: str = 'Z') → int#

Creating the number of isopoints to further interpolate strike lines

Parameters

gdf (Union[gpd.geodataframe.GeoDataFrame, pd.DataFrame]) – (Geo-)DataFrame containing existing strike lines
increment (Union[float, int]) – Increment between the strike lines, e.g. increment=50
zcol (string) – Name of z column, e.g. z='Z', default is 'Z'

Returns

number – Number of isopoints

Return type

int

New in version 1.0.x.

Example

>>> import gemgis as gg
>>> import geopandas as gpd
>>> gdf = gpd.read_file(filename='lines5_strike.shp')
>>> gdf
    id  Z   formation   geometry
0   7   0   Coal1   LINESTRING (1642.839 2582.579, 2829.348 2205.937)
1   6   150 Coal1   LINESTRING (1705.332 1759.201, 2875.795 1406.768)
2   5   200 Coal1   LINESTRING (1017.766 1722.234, 2979.938 1137.003)
3   4   250 Coal1   LINESTRING (99.956 1763.424, 765.837 1620.705,...
4   3   200 Coal1   LINESTRING (1078.147 1313.501, 2963.048 752.760)

>>> number = gg.utils.calculate_number_of_isopoints(gdf=gdf, increment=50)
>>> number
2

See also

get_nearest_neighbor: Getting the nearest neighbor to a point

gemgis.utils.convert_crs_seismic_data(path_in: str, path_out: str, crs_in: Union[str, pyproj.crs.crs.CRS], crs_out: Union[str, pyproj.crs.crs.CRS], cdpx: int = 181, cdpy: int = 185, vert_domain: str = 'TWT', coord_scalar: int = None)#

Convert CDP coordinates of seismic data to a new CRS.

Parameters

path_in (str) – Path to the original seismic data, e.g. path_in='seismic.sgy'.
path_out (str) – Path to the converted seismic data, e.g. path_out='seismic_converted.sgy'.
crs_in (str, pyproj.crs.crs.CRS) – Coordinate reference system of the original seismic data.
crs_out (str, pyproj.crs.crs.CRS) – Coordinate reference system of the converted seismic data.
cdpx (int) – Byte position for the X coordinates, default is cdpx=181.
cdpy (int) – Byte position for the Y coordinates, default is cdpx=185.
vert_domain (str) – Vertical sampling domain. Options include 'TWT' and 'DEPTH', default is vert_domain='TWT'.
coord_scalar (int) – Coordinate scalar value to set if NaN columns are returned, default is coord_scalar=None.

New in version 1.1.1.

gemgis.utils.convert_location_dict_to_gdf(location_dict: dict) → geopandas.geodataframe.GeoDataFrame#

Converting a location dict to a GeoDataFrame

Parameters: location_dict (dict) – Dict containing the name of the location and the coordinates
Returns: gdf – GeoDataFrame containing the location name and the coordinates of the location
Return type: gpd.geodataframe.GeoDataFrame

New in version 1.0.x.

Example

>>> # Loading Libraries
>>> import gemgis as gg

>>> # Creating a dict with coordinates
>>> coordinates_dict = gg.utils.get_locations(names = ['Aachen', 'Berlin', 'München', 'Hamburg', 'Köln'], crs='EPSG:4647')

>>> # Converting dict to GeoDataFrame
>>> gdf = gg.utils.convert_location_dict_to_gdf(location_dict=coordinates_dict)
>>> gdf
    City    X           Y           geometry
0       Aachen  32294411.33 5629009.36  POINT (32294411.335 5629009.357)
1       Berlin  32797738.56 5827603.74  POINT (32797738.561 5827603.740)
2       München 32691595.36 5334747.27  POINT (32691595.356 5334747.274)
3       Hamburg 32566296.25 5933959.96  POINT (32566296.251 5933959.965)
4       Köln    32356668.82 5644952.10  POINT (32356668.818 5644952.100)

gemgis.utils.convert_to_gempy_df(gdf: geopandas.geodataframe.GeoDataFrame, dem: Union[rasterio.io.DatasetReader, numpy.ndarray] = None, extent: List[Union[int, float]] = None) → pandas.core.frame.DataFrame#

Converting a GeoDataFrame into a Pandas DataFrame ready to be read in for GemPy

Parameters

gdf (gpd.geodataframe.GeoDataFrame) – GeoDataFrame containing spatial information, formation names and orientation values
dem (Union[np.ndarray, rasterio.io.DatasetReader]) – NumPy ndarray or rasterio object containing the height values
extent (List[Union[float,int]) – List containing the extent of the np.ndarray, must be provided in the same CRS as the gdf, e.g. extent=[0, 972, 0, 1069]

Returns

df – Interface or orientations DataFrame ready to be read in for GemPy

Return type

pd.DataFrame

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import geopandas as gpd
>>> import rasterio
>>> gdf = gpd.read_file(filename='file.shp')
>>> gdf
    id      formation   geometry
0   None    Ton         POINT (19.150 293.313)
1   None    Ton         POINT (61.934 381.459)
2   None    Ton         POINT (109.358 480.946)
3   None    Ton         POINT (157.812 615.999)
4   None    Ton         POINT (191.318 719.094)

>>> # Loading Digital Elevation Model
>>> dem = rasterio.open(fp='dem.tif')
>>> dem
<open DatasetReader name='dem.tif' mode='r'>

>>> # Defining extent
>>> extent = [0, 972, 0, 1069]

>>> # Converting GeoDataFrame to DataFrame
>>> df = gg.utils.convert_to_gempy_df(gdf=gdf, dem=dem, extent=extent)
>>> df
    formation   X       Y       Z
0   Ton         19.15   293.31  364.99
1   Ton         61.93   381.46  400.34
2   Ton         109.36  480.95  459.55
3   Ton         157.81  616.00  525.69
4   Ton         191.32  719.09  597.63

gemgis.utils.convert_to_petrel_points_with_attributes(mesh: pyvista.core.pointset.PolyData, path: str, crs: Optional[Union[str, pyproj.crs.crs.CRS]] = None, target_crs: Optional[Union[str, pyproj.crs.crs.CRS]] = None)#

Function to convert vertices of a PyVista Mesh to Petrel Points with Attributes

Parameters

mesh (pv.core.pointset.PolyData) – PyVista Mesh to be converted to points
path (str) – Path to store the converted points, e.g. path='project/'
crs (str, pyproj.crs.crs.CRS, type(None)) – Coordinate reference system for the GeoDataFrame, e.g. crs='EPSG:4326', default is None
target_crs (str, pyproj.crs.crs.CRS, type(None)) – Target coordinate reference system if coordinates of points should be reprojected, e.g. crs='EPSG:4326', default is None

New in version 1.0.x.

gemgis.utils.create_polygon_from_location(coordinates) → shapely.geometry.polygon.Polygon#

Creating Shapely Polygon from bounding box coordinates

Parameters: coordinates (geopy.location.Location) – GeoPy location object
Returns: polygon – Shapely Polygon marking the bounding box of the coordinate object
Return type: shapely.geometry.polygon.Polygon

New in version 1.0.x.

Example

>>> # Loading Libraries and get location object
>>> import gemgis as gg
>>> location = gg.utils.get_location_coordinate(name='Aachen')
>>> location
Location(Aachen, Städteregion Aachen, Nordrhein-Westfalen, Deutschland, (50.776351, 6.083862, 0.0))

>>> # Creating polygon from location bounds
>>> polygon = gg.utils.create_polygon_from_location(coordinates=location)
>>> polygon.wkt
'POLYGON ((50.8572449 5.9748624, 50.8572449 6.2180747, 50.6621373 6.2180747, 50.6621373 5.9748624, 50.8572449 5.9748624))'

See also

transform_location_coordinate: Transforming location coordinate to another CRS
get_location_coordinate: Get GeoPy Location Object
get_locations: Get location information for a list of city names

gemgis.utils.create_surface_color_dict(path: str) → dict#

Creating GemPy surface color dict from a QML file

Parameters: path (str) – Path to the qml file, e.g. qml_name='style.qml'
Returns: surface_color_dict – Dict containing the surface color values for GemPy
Return type: dict

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> surface_colors_dict = gg.utils.create_surface_color_dict(path='style.qml')
>>> surface_colors_dict
{'Sand1': '#b35a2a', 'Sand2': '#b35a2a', 'Ton': '#525252'}

See also

build_style_dict: Building style dictionairy from loaded style file
parse_categorized_qml: Reading the contents of a QGIS Style file (qml)
load_surface_colors: Loading surface colors as list

gemgis.utils.create_virtual_profile(names_surfaces: list, surfaces: list, borehole: pyvista.core.pointset.PolyData, first_point: bool = False) → pandas.core.frame.DataFrame#

Function to filter and sort the resulting well tops

Parameters

names_surfaces (list) – List of the names of the calculated GemPy surfaces, e.g. names_surfaces=['Layer1', 'Layer2']
surfaces (list) – List of calculated GemPy surfaces, e.g. surfaces=['Layer1', 'Layer2']
borehole (pv.core.pointset.PolyData) – Coordinates of the bottom of the well
first_point (bool) – Returns intersection of first point only. Options include: True or False, default set to False

Returns

df – DataFrame containing the well tops

Return type

pd.DataFrame

New in version 1.0.x.

gemgis.utils.create_zmap_grid(surface: pyvista.core.pointset.PolyData, cell_width: int, comments: str = '', name: str = 'ZMAP_Grid', z_type: str = 'GRID', nodes_per_line: int = 5, field_width: int = 15, nodata: Union[int, float] = - 9999.0, nodata2: Union[int, float, str] = '', decimal_places: int = 5, start_column: int = 1)#

Function to write data to ZMAP Grid, This code is heavily inspired by https://github.com/abduhbm/zmapio

Parameters

surface (pv.core.pointset.PolyData) – PyVista mesh
cell_width (int) – Width of grid cell, e.g. cell_width=50
comments (str) – Comments written to the ZMAP File, e.g. comments='Project: Einstein', default is ''
name (str) – Name of the ZMAP File, e.g. name='ZMAP_Grid', default is 'ZMAP_Grid'
z_type (str) – ZMAP Grid Type, e.g. z_type='GRID', default is 'GRID'
nodes_per_lines (int) – Number of values per line, e.g. nodes_per_line=5, default is 5
field_width (int) – Width of each field, e.g. field_width=15, default is 15
nodata (Union[int, float]) – No data value, e.g. nodata=-9999, default is -9999
nodata2 (Union[int, float, str]) – No data value, e.g. nodata2=-9999, default is ''
decimal_places (int) – Number of Decimal Places, e.g. decimal_places=5, default is 5
start_column (int) – Number of the start column, e.g. start_column=1, default is 1

Returns

lines – String containing the ZMAP Grid Data

Return type

str

New in version 1.0.x.

gemgis.utils.extract_zmap_data(surface: pyvista.core.pointset.PolyData, cell_width: int, nodata: Union[float, int] = - 9999)#

Function to extract a meshgrid of values from a PyVista mesh

Parameters

surface (pv.core.pointset.PolyData) – PyVista mesh
cell_width (int) – Width of grid cell, e.g. cell_width=50
nodata (Union[float, int]) – No data value, e.g. nodata=-9999, default is -9999

New in version 1.0.x.

gemgis.utils.get_cdp_linestring_of_seismic_data(path_in: str, crs_in: Union[str, pyproj.crs.crs.CRS], cdpx: int = 181, cdpy: int = 185, vert_domain: str = 'TWT')#

Extracting the path of the seismic data as LineString.

Parameters

path_in (str) – Path to the original seismic data, e.g. path_in='seismic.sgy'.
crs_in (str, pyproj.crs.crs.CRS) – Coordinate reference system of the original seismic data.
cdpx (int) – Byte position for the X coordinates, default is cdpx=181.
cdpy (int) – Byte position for the Y coordinates, default is cdpx=185.
vert_domain (str) – Vertical sampling domain. Options include 'TWT' and 'DEPTH', default is vert_domain='TWT'.

Returns

GeoDataFrame containing the surface path of the seismic data as LineString.

Return type

gpd.GeoDataFrame

New in version 1.1.1.

gemgis.utils.get_cdp_points_of_seismic_data(path_in: str, crs_in: Union[str, pyproj.crs.crs.CRS], cdpx: int = 181, cdpy: int = 185, vert_domain: str = 'TWT', filter: int = None, n_meter: Union[int, float] = None)#

Extracting the path of the seismic data as LineString.

Parameters

path_in (str) – Path to the original seismic data, e.g. path_in='seismic.sgy'.
crs_in (str, pyproj.crs.crs.CRS) – Coordinate reference system of the original seismic data.
cdpx (int) – Byte position for the X coordinates, default is cdpx=181.
cdpy (int) – Byte position for the Y coordinates, default is cdpx=185.
vert_domain (str) – Vertical sampling domain. Options include 'TWT' and 'DEPTH', default is vert_domain='TWT'.
filter (int) – Filtering the points to only return every n-th point, e.g. filter=100 to return only every 100-th point.
n_meter (int, float) – Parameter to select a point along the line every n-th meter.

Returns

GeoDataFrame containing the CDPs as Points.

Return type

gpd.GeoDataFrame

New in version 1.1.1.

gemgis.utils.get_location_coordinate(name: str)#

Obtaining coordinates of a given city

Parameters: name (str) – Name of the location, e.g. name='Aachen'
Returns: coordinates – GeoPy Location object
Return type: geopy.location.Location

New in version 1.0.x.

Example

>>> # Loading Libraries and get location object
>>> import gemgis as gg
>>> location = gg.utils.get_location_coordinate(name='Aachen')
>>> location
Location(Aachen, Städteregion Aachen, Nordrhein-Westfalen, Deutschland, (50.776351, 6.083862, 0.0))

See also

transform_location_coordinate: Transforming location coordinate to another CRS
create_polygon_from_location: Create Shapely Polygon from GeoPy Location Object bounds
get_locations: Get location information for a list of city names

gemgis.utils.get_locations(names: Union[list, str], crs: Union[str, pyproj.crs.crs.CRS] = 'EPSG:4326') → dict#

Obtaining coordinates for one city or a list of given cities. A CRS other than ‘EPSG:4326’ can be passed to transform the coordinates

Parameters

names (Union[list, str]) – List of cities or single city name, e.g. names=['Aachen', 'Cologne', 'Munich', 'Berlin']
crs (Union[str, pyproj.crs.crs.CRS]) – CRS that coordinates will be transformed to, e.g. crs='EPSG:4647', default is the GeoPy crs 'EPSG:4326'

Returns

location_dict – Dict containing the addresses and coordinates of the selected cities

Return type

dict

New in version 1.0.x.

Example

>>> # Loading Libraries and get location objects
>>> import gemgis as gg
>>> names = ['Aachen', 'Cologne', 'Munich', 'Berlin']
>>> location_dict = gg.utils.get_locations(names=names, crs='EPSG:4647')
>>> location_dict
{'Aachen, Städteregion Aachen, Nordrhein-Westfalen, Deutschland': (32294411.33488576,  5629009.357074926),
'Köln, Nordrhein-Westfalen, Deutschland': (32356668.818424627, 5644952.099932303),
'München, Bayern, Deutschland': (32691595.356409974, 5334747.274305081),
'Berlin, 10117, Deutschland': (32797738.56053437, 5827603.740024588)}

See also

transform_location_coordinate: Transforming location coordinate to another CRS
get_location_coordinate: Get GeoPy Location Object
create_polygon_from_location: Create Shapely Polygon from GeoPy Location Object bounds

gemgis.utils.get_nearest_neighbor(x: numpy.ndarray, y: numpy.ndarray) → numpy.int64#

Function to return the index of the nearest neighbor for a given point Y

Parameters

x (np.ndarray) – Array with coordinates of a set of points, e.g. x=np.array([(0,0), (10,10)])
y (np.ndarray) – Array with coordinates for point y, e.g. y=np.array([2,2])

Returns

index – Index of the nearest neighbor of point set X to point Y

Return type

np.int64

New in version 1.0.x.

Example

>>> import gemgis as gg
>>> import numpy as np
>>> x = np.array([(0,0), (10,10)])
>>> x
array([[ 0,  0],
        [10, 10]])

>>> y = np.array([2,2])
>>> y
array([2, 2])

>>> index = gg.utils.get_nearest_neighbor(x=x, y=y)
>>> index
0

See also

calculate_number_of_isopoints: Calculating the number of isopoints that are necessary to interpolate lines

gemgis.utils.getfeatures(extent: Optional[List[Union[int, float]]], crs_raster: Union[str, dict], crs_bbox: Union[str, dict], bbox: shapely.geometry.polygon.Polygon = None) → list#

Creating a list containing a dict with keys and values to clip a raster

Parameters

extent (Union[List[Union[int, float]]) – List of bounds (minx,maxx, miny, maxy), e.g. extent=[0, 972, 0, 1069]
crs_raster (Union[str, dict]) – String or dict containing the raster crs, e.g. crs='EPSG:4647'
crs_bbox (Union[str, dict]) – String or dict containing the bbox crs, e.g. crs='EPSG:4647'
bbox (shapely.geometry.polygon.Polygon) – Shapely polygon defining the bbox used to get the coordinates, , e.g. polygon = Polygon([(0, 0), (0, 10), (10, 10), (10, 0)])

Returns

data – List containing a dict with keys and values to clip raster

Return type

list

New in version 1.0.x.

gemgis.utils.interpolate_strike_lines(gdf: geopandas.geodataframe.GeoDataFrame, increment: Union[float, int], xcol: str = 'X', ycol: str = 'Y', zcol: str = 'Z') → geopandas.geodataframe.GeoDataFrame#

Interpolating strike lines to calculate orientations

Parameters

gdf (Union[gpd.geodataframe.GeoDataFrame, pd.DataFrame]) – (Geo-)DataFrame containing existing strike lines
increment (Union[float, int]) – Increment between the strike lines, e.g. increment=50
xcol (str) – Name of X column, e.g. x='X'
ycol (str) – Name of X column, e.g. y='Y'
zcol (str) – Name of Z column, e.g. z='Z'

Returns

gdf_out – GeoDataFrame containing the existing and interpolated strike lines

Return type

gpd.geodataframe.GeoDataFrame

New in version 1.0.x.

gemgis.utils.load_surface_colors(path: str, gdf: geopandas.geodataframe.GeoDataFrame) → List[str]#

Loading surface colors from a QML file and storing the color values as list to be displayed with GeoPandas plots

Parameters

path (str) – Path to the qml file, e.g. qml_name='style.qml'
gdf (gpd.geodataframe.GeoDataFrame) – GeoDataFrame of which objects are supposed to be plotted, usually loaded from a polygon/line shape file

Returns

cols – List of color values for each surface

Return type

List[str]

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import geopandas as gpd
>>> gdf = gpd.read_file(filename='file.shp')

>>> # Loading surface colors
>>> colors = gg.utils.load_surface_colors(path='style.qml', gdf=gdf)
>>> colors
['#b35a2a', '#b35a2a', '#525252']

See also

build_style_dict: Building style dictionairy from loaded style file
parse_categorized_qml: Reading the contents of a QGIS Style file (qml)
create_surface_color_dict: Creating dict with colors for each formation

gemgis.utils.open_mpk(path_in: str)#

Read ArcGIS .mpk file and return vector and raster data.

Parameters

path_in (str) – Path to the .mpk file, e.g. path='file.mpk'

Returns

dict_vector_data (dict) – Dictionary containing the extracted vector data.
dict_raster_data (dict) – Dictionary containing the extracted raster data.

Example

gemgis.utils.parse_categorized_qml(qml_name: str) → tuple#

Parsing a QGIS style file to retrieve surface color values

Parameters

qml_name (str) – Path to the QML file, e.g. qml_name='style.qml'

Returns

column (str) – Variable indicating after which formation the objects were colored (i.e. 'formation')
classes (dict) – Dict containing the style attributes for all available objects

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> column, classes = gg.utils.parse_categorized_qml(qml_name='style.qml')
>>> column
'formation'

>>> # Inspecting classes
>>> classes
{'Sand1': {'border_width_map_unit_scale': '3x:0,0,0,0,0,0',
'color': '179,90,42,255',
'joinstyle': 'bevel',
'offset': '0,0',
'offset_map_unit_scale': '3x:0,0,0,0,0,0',
'offset_unit': 'MM',
'outline_color': '102,51,24,255',
'outline_style': 'solid',
'outline_width': '0.26',
'outline_width_unit': 'MM',
'style': 'solid'},....}

See also

build_style_dict: Building style dictionairy from loaded style file
load_surface_colors: Loading surface colors as list
create_surface_color_dict: Creating dict with colors for each formation

gemgis.utils.ray_trace_multiple_surfaces(surfaces: list, borehole_top: Union[numpy.ndarray, list], borehole_bottom: Union[numpy.ndarray, list], first_point: bool = False) → list#

Function to return the depth of multiple surfaces in one well using PyVista ray tracing

Parameters

surfaces (list) – List of calculated GemPy surfaces
borehole_top – Coordinates of the top of the well
borehole_bottom – Coordinates of the bottom of the well
first_point (bool) – Returns intersection of first point only

Returns

intersections – List of intersections

Return type

list

New in version 1.0.x.

gemgis.utils.ray_trace_one_surface(surface: Union[pyvista.core.pointset.PolyData, pyvista.core.pointset.UnstructuredGrid], origin: Union[numpy.ndarray, list], end_point: Union[numpy.ndarray, list], first_point: bool = False) → tuple#

Function to return the depth of one surface in one well using PyVista ray tracing

Parameters

surface (Union[pv.core.pointset.PolyData, pv.core.pointset.UnstructuredGrid]) – Calculated or clipped GemPy surface
origin – Coordinates of the top of the well
end_point – Coordinates of the bottom of the well
first_point (bool) – Returns intersection of first point only

Returns

intersection_points, intersection_cells – Location of the intersection points, Indices of the intersection cells

Return type

tuple

New in version 1.0.x.

gemgis.utils.read_csv_as_gdf(path: str, crs: Union[str, pyproj.crs.crs.CRS], x: str = 'X', y: str = 'Y', z: str = None, delimiter: str = ',') → geopandas.geodataframe.GeoDataFrame#

Reading CSV files as GeoDataFrame

Parameters

path (str) – Path of the CSV files, e.g. path='file.csv'
crs (Union[str, pyproj.crs.crs.CRS]) – CRS of the spatial data, e.g. crs='EPSG:4647'
x (str) – Name of the X column, e.g. x='X', default is 'X'
y (str) – Name of the Y column, e.g. y='Y', default is 'Y'
z (str) – Name of the Z column, e.g. z='Z', default is 'Z'
delimiter (str) – Delimiter of CSV file, e.g. delimiter=',', default is ‘,’

Returns

gdf – GeoDataFrame of the CSV data

Return type

gpd.geodataframe.GeoDataFrame

New in version 1.0.x.

Example

>>> # Loading Libraries and File as GeoDataFrame
>>> import gemgis as gg
>>> gdf = gg.utils.read_csv_as_gdf(path='file.csv')
>>> gdf
    id      formation   geometry
0   None    Ton         POINT (19.150 293.313)
1   None    Ton         POINT (61.934 381.459)
2   None    Ton         POINT (109.358 480.946)
3   None    Ton         POINT (157.812 615.999)
4   None    Ton         POINT (191.318 719.094)

gemgis.utils.rotate_gempy_input_data(extent: Union[numpy.ndarray, shapely.geometry.polygon.Polygon, geopandas.geodataframe.GeoDataFrame], interfaces: Union[pandas.core.frame.DataFrame, geopandas.geodataframe.GeoDataFrame], orientations: Union[pandas.core.frame.DataFrame, geopandas.geodataframe.GeoDataFrame], zmin: Union[float, int] = None, zmax: Union[float, int] = None, rotate_reverse_direction: bool = False, return_extent_gdf: bool = False, manual_rotation_angle: Union[float, int] = None)#

Function to rotate the GemPy Input Data horizontally or vertically

Parameters

extent (np.ndarray, shapely.geometry.Polygon, gpd.geodataframe.GeoDataFrame) – Extent of the Model
interfaces (pd.DataFrame, gpd.geodataframe.GeoDataFrame) – Interface points for the GemPy Model
orientations (pd.DataFrame, gpd.geodataframe.GeoDataFrame) – Orientations for the GemPy Model
zmin (float, int) – Lower Z limit of the GemPy Model, e.g. zmin=-1000, default is None
zmax (float, int) – Upper Z limit of the GemPy Model, e.g. zmax=1000, default is None
rotate_reverse_direction (bool) – Rotating the model the other direction. Options include: True or False, default set to False
return_extent_gdf (bool) – Returning the extent GeoDataFrame. Options include: True or False, default set to False
manual_rotation_angle (float, int) – Angle to manually rotate the data, e.g. manual_rotation_angle=45, default is None

Returns

extent (list) – New GemPy Model extent, e.g. extent=[0, 972, 0, 1069]
interfaces_rotated (pd.DataFrame, gpd.geodataframe.GeoDataFrame) – Rotated interfaces for the structural modeling in GemPy
orientations_rotated (pd.DataFrame, gpd.geodataframe.GeoDataFrame) – Rotated orientations for the structural modeling in GemPy

New in version 1.1.

gemgis.utils.save_zmap_grid(zmap_grid: list, path: str = 'ZMAP_Grid.dat')#

Function to save ZMAP Grid information to file

Parameters

zmap_grid (list) – List of strings containing the ZMAP Data
path (str) – Path and filename to store the ZMAP Grid, e.g. path='ZMAP_Grid.dat', default is 'ZMAP_Grid.dat'

New in version 1.0.x.

gemgis.utils.set_extent(minx: Union[int, float] = 0, maxx: Union[int, float] = 0, miny: Union[int, float] = 0, maxy: Union[int, float] = 0, minz: Union[int, float] = 0, maxz: Union[int, float] = 0, gdf: geopandas.geodataframe.GeoDataFrame = None) → List[Union[int, float]]#

Setting the extent for a model

Parameters

minx (Union[int, float]) – Value defining the left border of the model, e.g. minx=0, default is 0
maxx (Union[int, float]) – Value defining the right border of the model, e.g. max=972, default is 0
miny (Union[int, float]) – Value defining the upper border of the model, e.g. miny=0, default is 0
maxy (Union[int, float]) – Value defining the lower border of the model, e.g. maxy=1069, default is 0
minz (Union[int, float]) – Value defining the top border of the model, e.g. minz=0, default is 0
maxz (Union[int, float]) – Value defining the bottom border of the model, e.g. maxz=1000, default is 0
gdf (gpd.geodataframe.GeoDataFrame) – GeoDataFrame from which bounds the extent will be set, default is None

Returns

extent – List containing extent values

Return type

List[Union[int, float]]

New in version 1.0.x.

Example

>>> # Loading Libraries and setting the extent
>>> import gemgis as gg
>>> extent = gg.utils.set_extent(minx=0, maxx=972, miny=0, maxy=1069, minz=0, maxz=1000)
>>> extent
[0, 972, 0, 1069, 0, 1000]

gemgis.utils.set_resolution(x: int, y: int, z: int) → List[int]#

Setting the resolution for a model

Parameters

x (int) – Value defining the resolution in X direction, e.g. x=50
y (int) – Value defining the resolution in Y direction, e.g. y=50
z (int) – Value defining the resolution in Z direction, e.g. z=50

Returns

resolution – List containing resolution values

Return type

List[int]

New in version 1.0.x.

Example

>>> # Loading Libraries and setting the resolution
>>> import gemgis as gg
>>> res = gg.utils.set_resolution(x=50, y=50, z=50)
>>> res
[50, 50, 50]

gemgis.utils.show_number_of_data_points(geo_model)#

Adding the number of Interfaces and Orientations to the GemPy Surface dataframe

Parameters: geo_model (gp.core.model.Project) – GemPy geo_model object
Returns: geo_model.surfaces – DataFrame-like object containing surface information and number of data points
Return type: gempy.core.model.RestrictingWrapper

New in version 1.0.x.

Example

>>> # Loading Libraries and displaying surface DataFrame of a GemPy geo_model
>>> import gemgis as gg
>>> geo_model.surfaces
    surface     series          order_surfaces  color   id
0   Sand1       Strat_Series    1               #015482 1
1   Ton         Strat_Series    2               #9f0052 2
2   basement    Strat_Series    3               #ffbe00 3

>>> # Adding number of data points to DataFrame
>>> gg.utils.show_number_of_data_points(geo_model=geo_model)
    surface     series          order_surfaces  color   id  No. of Interfaces   No. of Orientations
0   Sand1       Strat_Series    1               #015482 1   95                  0
1   Ton         Strat_Series    2               #9f0052 2   36                  8
2   basement    Strat_Series    3               #ffbe00 3   0                   0

gemgis.utils.to_section_dict(gdf: geopandas.geodataframe.GeoDataFrame, section_column: str = 'section_name', resolution: List[int] = None) → dict#

Converting custom sections stored in Shape files to GemPy section_dicts

Parameters

gdf (gpd.geodataframe.GeoDataFrame) – GeoDataFrame containing the points or lines of custom sections
section_column (str) – String containing the name of the column containing the section names, e.g. section_column='section_name', default is 'section_name'
List[int] (resolution -) – List containing the x,y resolution of the custom section, e.g. resolution=[80,80]

Returns

section_dict – Dict containing the section names, coordinates and resolution

Return type

dict

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import geopandas as gpd
>>> gdf = gpd.read_file(filename='file.shp')
>>> gdf
    id      geometry                    Section
0       None    POINT (695.467 3.226)       Section1
1       None    POINT (669.284 1060.822)        Section1

>>> # Creating Section dict
>>> section_dict = gg.utils.to_section_dict(gdf=gdf, section_column='Section')
>>> section_dict
{'Section1': ([695.4667461080886, 3.2262250771374283],
[669.2840030245482, 1060.822026058724], [100, 80])}

gemgis.utils.transform_location_coordinate(coordinates, crs: Union[str, pyproj.crs.crs.CRS]) → dict#

Transforming coordinates of GeoPy Location

Parameters

coordinates (geopy.location.Location) – GeoPy location object
crs (Union[str, pyproj.crs.crs.CRS]) – Name of the target crs, e.g. crs='EPSG:4647'

Returns

result_dict – Dict containing the location address and transformed coordinates

Return type

dict

New in version 1.0.x.

Changed in version 1.1.7.

Updated to use the latest pyproj transformer

Example

>>> # Loading Libraries and get location object
>>> import gemgis as gg
>>> location = gg.utils.get_location_coordinate(name='Aachen')
>>> location
Location(Aachen, Städteregion Aachen, Nordrhein-Westfalen, Deutschland, (50.776351, 6.083862, 0.0))

>>> # Transforming location coordinates
>>> result_dict = gg.utils.transform_location_coordinate(coordinates=location, crs='EPSG:4647')
>>> result_dict
{'Aachen, Städteregion Aachen, Nordrhein-Westfalen, Deutschland': (32294411.33488576, 5629009.357074926)}

See also

get_location_coordinate: Get GeoPy Location Object
create_polygon_from_location: Create Shapely Polygon from GeoPy Location Object bounds
get_locations: Get location information for a list of city names

gemgis.vector module#

Contributors: Alexander Jüstel, Arthur Endlein Correia, Florian Wellmann, Marius Pischke

gemgis.vector.calculate_angle(linestring: shapely.geometry.linestring.LineString) → float#

Calculating the angle of a LineString to the vertical

Parameters: linestring (shapely.geometry.linestring.LineString) – Shapely LineString consisting of two vertices, e.g. linestring = LineString([(0, 0), (10, 10), (20, 20)])
Returns: angle – Angle of a LineString to the vertical
Return type: float

New in version 1.0.x.

Example

>>> # Loading Libraries and creating LineString
>>> import gemgis as gg
>>> from shapely.geometry import LineString
>>> linestring = LineString([(0, 0), (20, 20)])
>>> linestring.wkt
'LINESTRING (0 0, 20 20)'

>>> # Calculating the strike angle of the LineString
>>> angle = gg.vector.calculate_angle(linestring=linestring)
>>> angle
135.0

See also

calculate_strike_direction_straight_linestring: Calculating the strike direction of a straight LineString
calculate_strike_direction_bent_linestring: Calculating the strike direction of a bent LineString
calculate_dipping_angle_linestring: Calculate the dipping angle of a LineString
calculate_dipping_angles_linestrings: Calculate the dipping angles of LineStrings

Note

The LineString must only consist of two points (start and end point)

gemgis.vector.calculate_azimuth(gdf: Union[geopandas.geodataframe.GeoDataFrame, List[shapely.geometry.linestring.LineString]]) → List[Union[int, float]]#

Calculating the azimuth for an orientation Geodataframe represented by LineStrings

Parameters: gdf (Union[gpd.geodataframe.GeoDataFrame, List[shapely.geometry.linestring.LineString]) – GeoDataFrame or list containing the LineStrings of orientations
Returns: azimuth_list – List containing the azimuth values of the orientation LineString
Return type: List[Union[float, int]]

New in version 1.0.x.

Example

>>> # Loading Libraries and creating LineString
>>> import gemgis as gg
>>> from shapely.geometry import LineString
>>> import geopandas as gpd
>>> linestring1 = LineString([(0, 0), (20, -20)])
>>> linestring1.wkt
'LINESTRING (0 0, 20 -20)'

>>> # Creating second LineString
>>> linestring2 = LineString([(0, 0), (20, -10)])
>>> linestring2.wkt
'LINESTRING (0 0, 20 -10)'

>>> # Creating GeoDataFrame from LineStrings
>>> gdf = gpd.GeoDataFrame(geometry=[linestring1, linestring2])
>>> gdf
    geometry
0       LINESTRING (0.0 0.0, 20.0 -20.0)
1       LINESTRING (0.0 0.0, 20.0 -10.0)

>>> # Calculating the azimuths of the LineStrings
>>> azimuths = gg.vector.calculate_azimuth(gdf=gdf)
>>> azimuths
[135.0, 116.56505117707799]

See also

create_linestring_from_points: Create LineString from points
create_linestring_gdf: Create GeoDataFrame with LineStrings from points
extract_orientations_from_map: Extracting orientations from a map
calculate_distance_linestrings: Calculating the distance between LineStrings
calculate_orientations_from_strike_lines: Calculating the orientations from strike lines

gemgis.vector.calculate_coordinates_for_linestring_on_cross_sections(linestring: shapely.geometry.linestring.LineString, interfaces: shapely.geometry.linestring.LineString)#

Calculating the coordinates of vertices for a LineString on a straight cross section provided as Shapely LineString

Parameters

linestring (shapely.geometry.linestring.LineString) – Shapely LineString containing the trace of a cross section on a map, e.g. linestring = LineString([(0, 0), (20, 20)])
interfaces (shapely.geometry.linestring.LineString) – Shapely LineString containing the interfaces points digitized on a cross section, e.g. interfaces = LineString([(2, -2), (5, -5)])

Returns

points – List of Shapely Points with real world coordinates of digitized points on cross section

Return type

List[shapely.geometry.point.Point]

New in version 1.0.x.

Example

>>> # Loading Libraries and creating LineString
>>> import gemgis as gg
>>> from shapely.geometry import Point, LineString
>>> linestring = LineString([(0, 0), (20, -20)])
>>> linestring.wkt
'LINESTRING (0 0, 20 -20)'

>>> # Creating second LineString
>>> interfaces = LineString([(2, -2), (5, -5)])
>>> interfaces.wkt
'LINESTRING (2 -2, 5 -5)'

>>> # Calculating coordinates for LineString on cross section
>>> points = gg.vector.calculate_coordinates_for_linestring_on_cross_sections(linestring=linestring, interfaces=interfaces)
>>> points
[<shapely.geometry.point.Point at 0x231e8dc4d60>,
<shapely.geometry.point.Point at 0x231e5d9b070>]

>>> # Inspecting the first element of the list
>>> points[0].wkt
'POINT (1.414213562373095 -1.414213562373095)'

>>> # Inspecting the second element of the list
>>> points[1].wkt
'POINT (3.535533905932737 -3.535533905932737)'

See also

calculate_coordinates_for_point_on_cross_section: Calculating the coordinates for a Point on a cross section
calculate_coordinates_for_linestrings_on_cross_sections: Calculating the coordinates for LineStrings on cross sections
extract_interfaces_coordinates_from_cross_section: Extracting the coordinates of interfaces from cross sections
extract_xyz_from_cross_sections: Extracting the X, Y, and Z coordinates of interfaces from cross sections

gemgis.vector.calculate_coordinates_for_linestrings_on_cross_sections(linestring: shapely.geometry.linestring.LineString, linestring_interfaces_list: List[shapely.geometry.linestring.LineString]) → List[shapely.geometry.point.Point]#

Calculating the coordinates of vertices for LineStrings on a straight cross section provided as Shapely LineString

Parameters

linestring (shapely.geometry.linestring.LineString) – Shapely LineString containing the trace of a cross section on a map, e.g. linestring = LineString([(0, 0), (10, 10), (20, 20)])
linestring_interfaces_list (List[shapely.geometry.linestring.LineString]) – List containing Shapely LineStrings representing interfaces on cross sections

Returns

points – List containing Shapely Points with real world coordinates of the digitized interfaces on the cross section

Return type

List[shapely.geometry.point.Point]

New in version 1.0.x.

Example

>>> # Loading Libraries and creating LineString
>>> import gemgis as gg
>>> from shapely.geometry import Point, LineString
>>> linestring = LineString([(0, 0), (20, -20)])
>>> linestring.wkt
'LINESTRING (0 0, 20 -20)'

>>> # Creating second LineString
>>> interfaces = LineString([(2, -2), (5, -5)])
>>> interfaces.wkt
'LINESTRING (2 -2, 5 -5)'

>>> # Creating list of LineStrings
>>> linestring_interfaces_list = [interfaces, interfaces]

>>> # Calculating coordinates for LineStrings on cross section
>>> points = gg.vector.calculate_coordinates_for_linestrings_on_cross_sections(linestring=linestring, linestring_interfaces_list=linestring_interfaces_list)
>>> points
[<shapely.geometry.point.Point at 0x231e8019730>,
 <shapely.geometry.point.Point at 0x231e801e400>,
 <shapely.geometry.point.Point at 0x231e80192e0>,
 <shapely.geometry.point.Point at 0x231e80191f0>]

>>> # Inspecting the first element of the list
>>> points[0].wkt
'POINT (1.414213562373095 -1.414213562373095)'

>>> # Inspecting the second element of the list
>>> points[1].wkt
'POINT (3.535533905932737 -3.535533905932737)'

>>> # Inspecting the third element of the list
>>> points[2].wkt
'POINT (1.414213562373095 -1.414213562373095)'

>>> # Inspecting the fourth element of the list
>>> points[3].wkt
'POINT (3.535533905932737 -3.535533905932737)'

See also

calculate_coordinates_for_point_on_cross_section: Calculating the coordinates for a Point on a cross section
calculate_coordinates_for_linestring_on_cross_sections: Calculating the coordinates for one LineString on cross sections
extract_interfaces_coordinates_from_cross_section: Extracting the coordinates of interfaces from cross sections
extract_xyz_from_cross_sections: Extracting the X, Y, and Z coordinates of interfaces from cross sections

gemgis.vector.calculate_coordinates_for_point_on_cross_section(linestring: shapely.geometry.linestring.LineString, point: Union[shapely.geometry.point.Point, Tuple[float, float]])#

Calculating the coordinates for one point digitized on a cross section provided as Shapely LineString

Parameters

linestring (shapely.geometry.linestring.LineString) – Shapely LineString containing the trace of a cross section on a map, e.g. linestring = LineString([(0, 0), (20, 20)])
point (Union[shapely.geometry.point.Point, Tuple[float, float]]) – Shapely object or tuple of X and Y coordinates digitized on a cross section e.g. point = Point(5, 0)

Returns

point – Shapely Point with real world X and Y coordinates extracted from cross section LineString on Map

Return type

shapely.geometry.point.Point

New in version 1.0.x.

Example

>>> # Loading Libraries and creating LineString
>>> import gemgis as gg
>>> from shapely.geometry import Point, LineString
>>> linestring = LineString([(0, 0), (20, -20)])
>>> linestring.wkt
'LINESTRING (0 0, 20 -20)'

>>> # Creating Point
>>> point = Point(5, 0)
>>> point.wkt
'POINT (5 0)'

>>> # Calculating real world coordinates for point on cross section
>>> point_xy = gg.vector.calculate_coordinates_for_point_on_cross_section(linestring=linestring, point=point)
>>> point_xy.wkt
'POINT (3.535533905932737 -3.535533905932737)'

See also

calculate_coordinates_for_linestring_on_cross_sections: Calculating the coordinates for a LineString on a cross section
calculate_coordinates_for_linestrings_on_cross_sections: Calculating the coordinates for LineStrings on cross sections
extract_interfaces_coordinates_from_cross_section: Extracting the coordinates of interfaces from cross sections
extract_xyz_from_cross_sections: Extracting the X, Y, and Z coordinates of interfaces from cross sections

gemgis.vector.calculate_dipping_angle_linestring(linestring: shapely.geometry.linestring.LineString)#

Calculating the dipping angle of a LineString digitized on a cross section

Parameters: linestring (shapely.geometry.linestring.LineString) – Shapely LineString digitized on a cross section, e.g. linestring = LineString([(0, 0), (20, 20)])
Returns: dip – Dipping angle of the LineString
Return type: float

New in version 1.0.x.

Example

>>> # Loading Libraries and creating LineString
>>> import gemgis as gg
>>> from shapely.geometry import LineString
>>> linestring = LineString([(0, 0), (20, -20)])
>>> linestring.wkt
'LINESTRING (0 0, 20 -20)'

>>> # Creating dipping angle from LineString
>>> angle = gg.vector.calculate_dipping_angle_linestring(linestring=linestring)
>>> angle
45.0

See also

calculate_angle: Calculating the angle of a LineString
calculate_strike_direction_straight_linestring: Calculating the strike direction of a straight LineString
calculate_strike_direction_bent_linestring: Calculating the strike direction of a bent LineString
calculate_dipping_angles_linestrings: Calculate the dipping angles of LineStrings

Note

The LineString must only consist of two points (start and end point)

gemgis.vector.calculate_dipping_angles_linestrings(linestring_list: Union[geopandas.geodataframe.GeoDataFrame, List[shapely.geometry.linestring.LineString]])#

Calculating the dipping angles of LineStrings digitized on a cross section

Parameters: linestring_list (Union[gpd.geodataframe.GeoDataFrame, List[shapely.geometry.linestring.LineString]]) – GeoDataFrame containing LineStrings or list of LineStrings
Returns: dipping_angles – List containing the dipping angles of LineStrings
Return type: List[float]

New in version 1.0.x.

Example

>>> # Loading Libraries and creating LineString
>>> import gemgis as gg
>>> from shapely.geometry import LineString
>>> linestring = LineString([(0, 0), (20, -20)])
>>> linestring.wkt
'LINESTRING (0 0, 20 -20)'

>>> # Creating list of LineStrings
>>> linestring_list = [linestring, linestring]

>>> # Calculating dipping angles for LineStrings
>>> angles = gg.vector.calculate_dipping_angles_linestrings(linestring_list=linestring_list)
>>> angles
[45.0, 45.0]

See also

calculate_angle: Calculating the angle of a LineString
calculate_strike_direction_straight_linestring: Calculating the strike direction of a straight LineString
calculate_strike_direction_bent_linestring: Calculating the strike direction of a bent LineString
calculate_dipping_angle_linestring: Calculate the dipping angle of a LineString

Note

The LineString must only consist of two points (start and end point)

gemgis.vector.calculate_distance_linestrings(ls1: shapely.geometry.linestring.LineString, ls2: shapely.geometry.linestring.LineString) → float#

Calculating the minimal distance between two LineStrings

Parameters

ls1 (shapely.geometry.linestring.LineString) – LineString 1, e.g. ls1 = LineString([(0, 0), (10, 10), (20, 20)])
ls2 (shapely.geometry.linestring.LineString) – LineString 2, e.g. ls2 = LineString([(0, 0), (10, 10), (20, 20)])

Returns

distance – Minimum distance between two Shapely LineStrings

Return type

float

New in version 1.0.x.

Example

>>> # Loading Libraries and creating LineStrings
>>> import gemgis as gg
>>> from shapely.geometry import LineString
>>> linestring1 = LineString([(0, 0), (20, 20)])
>>> linestring1.wkt
'LINESTRING (0 0, 20 20)'

>>> # Creating second LineString
>>> linestring2 = LineString([(0, 10), (20, 30)])
>>> linestring2.wkt
'LINESTRING (0 10, 20 30)'

>>> # Calculating distance between LineStrings
>>> distance = gg.vector.calculate_distance_linestrings(ls1=linestring1, ls2=linestring2)
>>> distance
7.0710678118654755

See also

calculate_azimuth: Calculating the azimuth for orientations on a map
create_linestring_from_points: Create LineString from points
create_linestring_gdf: Create GeoDataFrame with LineStrings from points
extract_orientations_from_map: Extracting orientations from a map
calculate_orientations_from_strike_lines: Calculating the orientations from strike lines

gemgis.vector.calculate_midpoint_linestring(linestring: shapely.geometry.linestring.LineString) → shapely.geometry.point.Point#

Calculating the midpoint of a LineString with two vertices

Parameters: linestring (shapely.geometry.linestring.LineString) – LineString consisting of two vertices from which the midpoint will be extracted, e.g. linestring = LineString([(0, 0), (20, 20)])
Returns: point – Shapely Point representing the midpoint of the LineString
Return type: shapely.geometry.point.Point

New in version 1.0.x.

Example

>>> # Loading Libraries and creating LineString
>>> import gemgis as gg
>>> from shapely.geometry import Point, LineString
>>> linestring = LineString([(0, 0), (20, -20)])
>>> linestring.wkt
'LINESTRING (0 0, 20 -20)'

>>> # Calculating the midpoint of a LineString
>>> midpoint = gg.vector.calculate_midpoint_linestring(linestring=linestring)
>>> midpoint.wkt
'POINT (10 -10)'

See also

calculate_midpoints_linestrings: Calculating the midpoints of LineStrings

Note

The LineString must only consist of two points (start and end point)

gemgis.vector.calculate_midpoints_linestrings(linestring_gdf: Union[geopandas.geodataframe.GeoDataFrame, List[shapely.geometry.linestring.LineString]]) → List[shapely.geometry.point.Point]#

Calculating the midpoints of LineStrings with two vertices each

Parameters: linestring_gdf (Union[gpd.geodataframe.GeoDataFrame, List[shapely.geometry.linestring.LineString]]) – GeoDataFrame containing LineStrings or list of LineStrings of which the midpoints will be calculated
Returns: midpoint_list – List of Shapely Points representing the midpoints of the provided LineStrings
Return type: List[shapely.geometry.point.Point]

New in version 1.0.x.

Example

>>> # Loading Libraries and creating LineString
>>> import gemgis as gg
>>> from shapely.geometry import Point, LineString
>>> linestring = LineString([(0, 0), (20, -20)])
>>> linestring.wkt
'LINESTRING (0 0, 20 -20)'

>>> # Creating list of LineStrings
>>> linestring_list = [linestring, linestring]

>>> # Calculating midpoints from LineStrings
>>> midpoints = gg.vector.calculate_midpoints_linestrings(linestring_gdf=linestring_list)
>>> midpoints
[<shapely.geometry.point.Point at 0x231ea982880>,
 <shapely.geometry.point.Point at 0x231ea982700>]

>>> # Inspecting the first element of the list
>>> midpoints[0].wkt
'POINT (10 -10)'

>>> # Inspecting the second element of the list
>>> midpoints[1].wkt
'POINT (10 -10)'

See also

calculate_midpoint_linestring: Calculating the midpoint of one LineString

gemgis.vector.calculate_orientation_for_three_point_problem(gdf: geopandas.geodataframe.GeoDataFrame) → geopandas.geodataframe.GeoDataFrame#

Calculating the orientation for a three point problem

Parameters: gdf (gpd.geodataframe.GeoDataFrame) – GeoDataFrame containing the three points and respective altitudes
Returns: orientation – GeoDataFrame containing the calculated orientation value
Return type: gpd.geodataframe.GeoDataFrame

New in version 1.0.x.

Example

>>> # Loading Libraries
>>> import gemgis as gg
>>> import geopandas as gpd
>>> points = gpd.read_file(filename='points.shp')
>>> points
    id  formation   Z   geometry
0   None    Coal    200 POINT (1842.732 602.462)
1   None    Coal    400 POINT (1696.262 1775.038)
2   None    Coal    600 POINT (104.302 1770.385)

>>> # Calculating Orientation
>>> orientation = gg.vector.calculate_orientation_for_three_point_problem(gdf=points)
>>> orientation
    Z       formation   azimuth dip     polarity    X       Y       geometry
0   400.0   Coal        140.84  11.29   1           1214.43 1382.63 POINT (1214.432 1382.628)

gemgis.vector.calculate_orientation_from_bent_cross_section(profile_linestring: shapely.geometry.linestring.LineString, orientation_linestring: shapely.geometry.linestring.LineString) → list#

Calculating the orientation of a LineString on a bent cross section provided as Shapely LineString

Parameters

profile_linestring (shapely.geometry.linestring.LineString) – Shapely LineString containing the trace of a cross section on a map e.g. profile_linestring = LineString([(0, 0), (5, 10), (20, 20)])
orientation_linestring (shapely.geometry.linestring.LineString) – Shapely LineString representing an orientation measurement on the cross section, e.g. orientation_linestring = LineString([(2, -2), (5, -5)])

Returns

orientation – List containing a Shapely Point with X and Y coordinates, the Z value, dip, azimuth and polarity values

Return type

list

New in version 1.0.x.

Example

>>> # Loading Libraries and creating LineString
>>> import gemgis as gg
>>> from shapely.geometry import LineString
>>> profile_linestring = LineString([(0, 0), (5, 10), (20, 20)])
>>> profile_linestring.wkt
'LINESTRING (0 0, 5 10, 20 20)'

>>> # Creating second LineString
>>> orientation_linestring = LineString([(2, -2), (5, -5)])
>>> orientation_linestring.wkt
'LINESTRING (2 -2, 5 -5)'

>>> # Calculating the orientation from a bent cross section
>>> orientations = gg.vector.calculate_orientation_from_bent_cross_section(profile_linestring=profile_linestring, orientation_linestring=orientation_linestring)
>>> orientations
[<shapely.geometry.point.Point at 0x231e7f00820>, -3.5, 45.0, 26.565051177078004, 1]

>>> # Inspecting the Point object of the list
>>> orientations[0].wkt
'POINT (1.565247584249853 3.130495168499706)'

See also

calculate_orientation_from_cross_section: Calculating the orientation of a LineString on a cross section
calculate_orientations_from_cross_section: Calculating orientations for LineStrings on a cross section
extract_orientations_from_cross_sections: Calculating the orientations for LineStrings on cross sections

gemgis.vector.calculate_orientation_from_cross_section(profile_linestring: shapely.geometry.linestring.LineString, orientation_linestring: shapely.geometry.linestring.LineString) → list#

Calculating the orientation for one LineString on one cross sections

Parameters

profile_linestring (shapely.geometry.linestring.LineString) – Shapely LineString containing the trace of a cross section on a map, e.g. profile_linestring = LineString([(0, 0), (20, 20)])
orientation_linestring (shapely.geometry.linestring.LineString) – Shapely LineString representing an orientation measurement on the cross section e.g. orientation_linestring = LineString([(2, -2), (5, -5)])

Returns

orientation – List containing a Shapely Point with X and Y coordinates, the Z value, dip, azimuth and polarity values

Return type

list

New in version 1.0.x.

Example

>>> # Loading Libraries and creating LineString
>>> import gemgis as gg
>>> from shapely.geometry import LineString
>>> profile_linestring = LineString([(0, 0), (20, 20)])
>>> profile_linestring.wkt
'LINESTRING (0 0, 20 20)'

>>> # Creating second LineString
>>> orientation_linestring = LineString([(2, -2), (5, -5)])
>>> orientation_linestring.wkt
'LINESTRING (2 -2, 5 -5)'

>>> # Calculating orientation orientation from cross section
>>> orientations = gg.vector.calculate_orientation_from_cross_section(profile_linestring=profile_linestring, orientation_linestring=orientation_linestring)
>>> orientations
[<shapely.geometry.point.Point at 0x231e79a5370>, -3.5, 45.0, 45.0, 1]

>>> # Inspecting the Point object of the list
>>> orientations[0].wkt
'POINT (2.474873734152916 2.474873734152916)'

See also

calculate_orientation_from_bent_cross_section: Calculating the orientation of a LineString on a bent cross section
calculate_orientations_from_cross_section: Calculating orientations for LineStrings on a cross section
extract_orientations_from_cross_sections: Calculating the orientations for LineStrings on cross sections

gemgis.vector.calculate_orientations_from_cross_section(profile_linestring: shapely.geometry.linestring.LineString, orientation_linestrings: Union[geopandas.geodataframe.GeoDataFrame, List[shapely.geometry.linestring.LineString]], extract_coordinates: bool = True) → geopandas.geodataframe.GeoDataFrame#

Calculating orientations from a cross sections using multiple LineStrings

Parameters

profile_linestring (shapely.geometry.linestring.LineString) – Shapely LineString containing the trace of a cross section on a map, e.g. profile_linestring = LineString([(0, 0), (5, 10), (20, 20)])
orientations_linestrings (Union[gpd.geodataframe.GeoDataFrame, List[shapely.geometry.linestring.LineString]]) – GeoDataFrame or list containing multiple orientation LineStrings
extract_coordinates (bool) – Variable to extract the X and Y coordinates from point objects. Options include: True or False, default set to True

Returns

gdf – GeoDataFrame containing the Shapely Points with X, Y coordinates, the Z value, dips, azimuths and polarities

Return type

gpd.geodataframe.GeoDataFrame

New in version 1.0.x.

Example

>>> # Loading Libraries and creating LineString
>>> import gemgis as gg
>>> from shapely.geometry import LineString
>>> profile_linestring = LineString([(0, 0), (5, 10), (20, 20)])
>>> profile_linestring.wkt
'LINESTRING (0 0, 5 10, 20 20)'

>>> # Creating second LineString
>>> orientation_linestring = LineString([(2, -2), (5, -5)])
>>> orientation_linestring.wkt
'LINESTRING (2 -2, 5 -5)'

>>> # Creating List of LineStrings
>>> orientations_list = [orientation_linestring, orientation_linestring]

>>> # Calculating orientations from cross sections
>>> orientations = gg.vector.calculate_orientations_from_cross_section(profile_linestring=profile_linestring, orientation_linestrings=orientations_list)
>>> orientations
    X       Y       Z       dip     azimuth polarity    geometry
0   1.57    3.13    -3.50   45.00   26.57   1.00        POINT (1.56525 3.13050)
1   1.57    3.13    -3.50   45.00   26.57   1.00        POINT (1.56525 3.13050)

See also

calculate_orientation_from_cross_section: Calculating the orientation of a LineString on a cross section
calculate_orientation_from_bent_cross_section: Calculating orientations of a LineStrings on a bent cross section
extract_orientations_from_cross_sections: Calculating the orientations for LineStrings on cross sections

gemgis.vector.calculate_orientations_from_strike_lines(gdf: geopandas.geodataframe.GeoDataFrame) → geopandas.geodataframe.GeoDataFrame#

Calculating orientations based on LineStrings representing strike lines

Parameters: gdf (gpd.geodataframe.GeoDataFrame) – GeoDataFrame containing LineStrings representing strike lines
Returns: gdf_orient – GeoDataFrame containing the location of orientation measurements and their associated orientation values
Return type: gpd.geodataframe.GeoDataFrame

New in version 1.0.x.

Changed in version 1.1.7.

Fixing indexing issue.

Example

>>> # Loading Libraries and creating LineString
>>> import gemgis as gg
>>> from shapely.geometry import LineString
>>> import geopandas as gpd
>>> linestring1 = LineString([(0, 0), (20, 20)])
>>> linestring1.wkt
'LINESTRING (0 0, 20 20)'

>>> # Create second LineString
>>> linestring2 = LineString([(0, 10), (20, 30)])
>>> linestring2.wkt
'LINESTRING (0 10, 20 30)'

>>> # Creating GeoDataFrame from LineStrings
>>> gdf = gpd.GeoDataFrame(geometry=[linestring1, linestring2])
>>> gdf['Z'] = [100,200]
>>> gdf['id'] = [1,2]
>>> gdf
    geometry                            Z   id
0       LINESTRING (0.0 0.0, 20.0 20.0)     100 1
1       LINESTRING (0.0 10.0, 20.0 30.0)    200 2

>>> # Calculating orientations strike lines
>>> orientations = gg.vector.calculate_orientations_from_strike_lines(gdf=gdf)
>>> orientations
    dip     azimuth     Z           geometry            polarity        X           Y
0       85.96   135.00  150.00  POINT (10.0 15.0)       1.00        10.00       15.00

See also

calculate_azimuth: Calculating the azimuth for orientations on a map
create_linestring_from_points: Create LineString from points
create_linestring_gdf: Create GeoDataFrame with LineStrings from points
extract_orientations_from_map: Extracting orientations from a map
calculate_distance_linestrings: Calculating the distance between two LineStrings

gemgis.vector.calculate_strike_direction_bent_linestring(linestring: shapely.geometry.linestring.LineString) → List[float]#

Calculating the strike direction of a LineString with multiple elements

Parameters: linestring (linestring: shapely.geometry.linestring.LineString) – Shapely LineString containing more than two vertices, e.g. linestring = LineString([(0, 0), (10, 10), (20, 20)])
Returns: angles_splitted_linestrings – List containing the strike angles of each line segment of the original
Return type: List[float]

New in version 1.0.x.

Example

>>> # Loading Libraries and creating LineString
>>> import gemgis as gg
>>> from shapely.geometry import LineString
>>> linestring = LineString([(0, 0), (10, 10), (20, 20)])
>>> linestring.wkt
'LINESTRING (0 0, 10 10, 20 20)'

>>> # Calculating the strike angles for LineString elements
>>> angles = gg.vector.calculate_strike_direction_bent_linestring(linestring=linestring)
>>> angles
[45.0, 45.0]

See also

calculate_angle: Calculating the angle of a LineString
calculate_strike_direction_straight_linestring: Calculating the strike direction of a straight LineString
calculate_dipping_angle_linestring: Calculate the dipping angle of a LineString
calculate_dipping_angles_linestrings: Calculate the dipping angles of LineStrings

gemgis.vector.calculate_strike_direction_straight_linestring(linestring: shapely.geometry.linestring.LineString) → float#

Function to calculate the strike direction of a straight Shapely LineString. The strike will always be calculated from start to end point

Parameters: linestring (shapely.geometry.linestring.LineString) – Shapely LineString representing the surface trace of a straight geological profile, e.g. linestring = LineString([(0, 0), (10, 10), (20, 20)])
Returns: angle – Strike angle calculated from start to end point for a straight Shapely LineString
Return type: float

New in version 1.0.x.

Example

>>> # Loading Libraries and creating LineString
>>> import gemgis as gg
>>> from shapely.geometry import LineString
>>> linestring = LineString([(0, 0), (20, 20)])
>>> linestring.wkt
'LINESTRING (0 0, 20 20)'

>>> # Calculating the strike angle of the LineString
>>> angle = gg.vector.calculate_strike_direction_straight_linestring(linestring=linestring)
>>> angle
45.0

See also

calculate_angle: Calculating the angle of a LineString
calculate_strike_direction_bent_linestring: Calculating the strike direction of a bent LineString
calculate_dipping_angle_linestring: Calculate the dipping angle of a LineString
calculate_dipping_angles_linestrings: Calculate the dipping angles of LineStrings

Note

The LineString must only consist of two points (start and end point)

gemgis.vector.clip_by_bbox(gdf: geopandas.geodataframe.GeoDataFrame, bbox: List[Union[int, float]], reset_index: bool = True, drop_index: bool = True, drop_id: bool = True, drop_points: bool = True, drop_level0: bool = True, drop_level1: bool = True) → geopandas.geodataframe.GeoDataFrame#

Clipping vector data contained in a GeoDataFrame to a provided bounding box/extent

Parameters

gdf (gpd.geodataframe.GeoDataFrame) – GeoDataFrame containing vector data that will be clipped to a provided bounding box/extent
bbox (List[Union[float, int]]) – Bounding box of minx, maxx, miny, maxy values to clip the GeoDataFrame, , e.g. bbox=[0, 972, 0, 1069]
reset_index (bool) – Variable to reset the index of the resulting GeoDataFrame. Options include: True or False, default set to True
drop_level0 (bool) – Variable to drop the level_0 column. Options include: True or False, default set to True
drop_level1 (bool) – Variable to drop the level_1 column. Options include: True or False, default set to True
drop_index (bool) – Variable to drop the index column. Options include: True or False, default set to True
drop_id (bool) – Variable to drop the id column. Options include: True or False, default set to True
drop_points (bool) – Variable to drop the points column. Options include: True or False, default set to True

Returns

gdf – GeoDataFrame containing vector data clipped by a bounding box

Return type

gpd.geodataframe.GeoDataFrame

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import geopandas as gpd
>>> gdf = gpd.read_file(filename='file.shp')
>>> gdf
    id  geometry
0       None    POINT (281.526 902.087)
1       None    POINT (925.867 618.577)
2       None    POINT (718.131 342.799)
3       None    POINT (331.011 255.684)
4       None    POINT (300.083 600.535)

>>> # Returning the length of the original gdf
>>> len(gdf)
50

>>> # Defining bounding box
>>> bbox = [0,972, 0, 1069]

>>> # Clipping data by bounding box
>>> gdf_clipped = gg.vector.clip_by_bbox(gdf=gdf, bbox=bbox)
>>> gdf_clipped
    geometry            X       Y
0       POINT (281.526 902.087) 281.53  902.09
1       POINT (925.867 618.577) 925.87  618.58
2       POINT (718.131 342.799) 718.13  342.80
3       POINT (331.011 255.684) 331.01  255.68
4       POINT (300.083 600.535) 300.08  600.54

>>> # Returning the length of the clipped gdf
>>> len(gdf_clipped)
25

See also

clip_by_polygon: Clipping vector data with a Shapely Polygon

gemgis.vector.clip_by_polygon(gdf: geopandas.geodataframe.GeoDataFrame, polygon: shapely.geometry.polygon.Polygon, reset_index: bool = True, drop_index: bool = True, drop_id: bool = True, drop_points: bool = True, drop_level0: bool = True, drop_level1: bool = True) → geopandas.geodataframe.GeoDataFrame#

Clipping vector data contained in a GeoDataFrame to a provided bounding box/extent

Parameters

gdf (gpd.geodataframe.GeoDataFrame) – GeoDataFrame containing vector data that will be clipped to a provided bounding box/extent
polygon (polygon: shapely.geometry.polygon) – Shapely Polygon defining the extent of the data, e.g. polygon = Polygon([[0, 0], [10, 0], [10, 10], [0, 10], [0, 0]])
reset_index (bool) – Variable to reset the index of the resulting GeoDataFrame. Options include: True or False, default set to True
drop_level0 (bool) – Variable to drop the level_0 column. Options include: True or False, default set to True
drop_level1 (bool) – Variable to drop the level_1 column. Options include: True or False, default set to True
drop_index (bool) – Variable to drop the index column. Options include: True or False, default set to True
drop_id (bool) – Variable to drop the id column. Options include: True or False, default set to True
drop_points (bool) – Variable to drop the points column. Options include: True or False, default set to True

Returns

gdf – GeoDataFrame containing vector data clipped by a bounding box

Return type

gpd.geodataframe.GeoDataFrame

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import geopandas as gpd
>>> gdf = gpd.read_file(filename='file.shp')
>>> gdf
    id  geometry
0       None    POINT (281.526 902.087)
1       None    POINT (925.867 618.577)
2       None    POINT (718.131 342.799)
3       None    POINT (331.011 255.684)
4       None    POINT (300.083 600.535)

>>> # Returning the length of the original gdf
>>> len(gdf)
50

>>> # Creating Shapely Polygon
>>> from shapely.geometry import Polygon
>>> polygon = Polygon([(0,0),(972, 0), (972,1069), (0, 1069)])
>>> polygon.wkt
'POLYGON ((0 0, 972 0, 972 1069, 0 1069, 0 0))'

>>> # Clipping data by the polygon
>>> gdf_clipped = gg.vector.clip_by_polygon(gdf=gdf, polygon=polygon)
>>> gdf_clipped
    geometry            X       Y
0       POINT (281.526 902.087) 281.53  902.09
1       POINT (925.867 618.577) 925.87  618.58
2       POINT (718.131 342.799) 718.13  342.80
3       POINT (331.011 255.684) 331.01  255.68
4       POINT (300.083 600.535) 300.08  600.54

>>> # Returning the length of the clipped gdf
>>> len(gdf_clipped)
25

See also

clip_by_bbox: Clipping vector data with a bbox

gemgis.vector.create_bbox(extent: List[Union[int, float]]) → shapely.geometry.polygon.Polygon#

Creating a rectangular polygon from the provided bounding box values, with counter-clockwise order by default.

Parameters: extent (List[Union[int, float]]) – List of minx, maxx, miny, maxy values, e.g. extent=[0, 972, 0, 1069]
Returns: bbox – Rectangular polygon based on extent
Return type: shapely.geometry.polygon.Polygon

New in version 1.0.x.

Example

>>> # Loading Libraries
>>> import gemgis as gg

>>> # Defining extent
>>> extent = [0, 972, 0, 1069]

>>> # Creating bounding box
>>> bbox = gg.vector.create_bbox(extent=extent)
>>> bbox.wkt
'POLYGON ((972 0, 972 1069, 0 1069, 0 0, 972 0))'

gemgis.vector.create_buffer(geom_object: shapely.geometry.base.BaseGeometry, distance: Union[float, int]) → shapely.geometry.polygon.Polygon#

Creating a buffer around a Shapely LineString or a Point

Parameters

geom_object (shapely.geometry.base.BaseGeometry) – Shapely LineString or Point, e.g. geom_object=Point(0, 0)
distance (float, int) – Distance of the buffer around the geometry object, e.g. distance=10

Returns

polygon – Polygon representing the buffered area around a geometry object

Return type

shapely.geometry.polygon.Polygon

New in version 1.0.x.

Example

>>> # Loading Libraries and creating Point
>>> import gemgis as gg
>>> from shapely.geometry import Point
>>> point = Point(0,0)
>>> point.wkt
'POINT (0 0)'

>>> # Creating Buffer around Point
>>> point_buffered = gg.vector.create_buffer(geom_object=point, distance=10)
>>> point_buffered.wkt
'POLYGON ((100 0, 99.5184726672197 -9.801714032956051, 98.07852804032305 -19.50903220161281, 95.69403357322089
-29.02846772544621, 92.38795325112869 -38.26834323650894, 88.19212643483553...))'

See also

create_unified_buffer: Creating a unified buffer around Shapely LineStrings or Points

gemgis.vector.create_hexagon(center: shapely.geometry.point.Point, radius: Union[int, float])#

Function to create one hexagon

Parameters

center (shapely.geometry.Point) – Shapely Point representing the center of the hexagon
radius (int, float) – Radius of the hexagon

Returns

geometry.Polygon(hex_coords) – Shapley Polygon in the shape of a hexagon

Return type

shapely.geometry.Polygon

New in version 1.0.x.

Changed in version 1.1.3: Optimized creation of hexagon

See also

create_hexagon_grid: Creating a hexagon grid

gemgis.vector.create_hexagon_grid(gdf: geopandas.geodataframe.GeoDataFrame, radius: Union[int, float], crop_gdf: bool = True)#

Function to create a grid of hexagons based on a GeoDataFrame containing Polygons and a radius provided for the single hexagons

Parameters

gdf (gpd.GeoDataFrame) – GeoDataFrame containing the polygons for which a hexagon grid is created
radius (int, float) – Radius of the hexagon
crop_gdf (bool) – Boolean to define if the resulting GeoDataFrame should be cropped to the extend of the provided GeoDataFrame Options include: True or False, default set to True

Returns

hex_gdf – GeoDataFrame containing the hexagon grid

Return type

gpd.GeoDataFrame

New in version 1.0.x.

Changed in version 1.1.3: Optimized creation of hexagon

See also

create_hexagon: Creating one hexagon based on a given center and radius

gemgis.vector.create_linestring_from_points(gdf: geopandas.geodataframe.GeoDataFrame, formation: str, altitude: Union[int, float]) → shapely.geometry.linestring.LineString#

Creating a LineString object from a GeoDataFrame containing surface points at a given altitude and for a given formation

Parameters

gdf (gpd.geodataframe.GeoDataFrame) – GeoDataFrame containing the points of intersections between topographic contours and layer boundaries
formation (str) – Name of the formation, e.g. formation='Layer1'
altitude (Union[int, float]) – Value of the altitude of the points, e.g. altitude=100

Returns

linestring – LineString containing a LineString object

Return type

shapely.geometry.linestring.LineString

New in version 1.0.x.

Example

>>> # Loading Libraries and creating points
>>> import gemgis as gg
>>> from shapely.geometry import Point
>>> import geopandas as gpd
>>> point1 = Point(0,0)
>>> point2 = Point (10,10)

>>> # Creating GeoDataFrame from points and adding additional information
>>> gdf = gpd.GeoDataFrame(geometry=[point1, point2])
>>> gdf['formation'] = 'Layer1'
>>> gdf['Z'] = 100
>>> gdf
    geometry            formation   Z
0   POINT (0.0 0.0)     Layer1      100
1   POINT (10.0 10.0)   Layer1      100

>>> # Creating LineString from Points
>>> linestring = gg.vector.create_linestring_from_points(gdf=gdf, formation='Layer1', altitude=100)
>>> linestring.wkt
'LINESTRING (0 0, 10 10)'

See also

calculate_azimuth: Calculating the azimuth for orientations on a map
create_linestring_gdf: Create GeoDataFrame with LineStrings from points
extract_orientations_from_map: Extracting orientations from a map
calculate_distance_linestrings: Calculating the distance between LineStrings
calculate_orientations_from_strike_lines: Calculating the orientations from strike lines

gemgis.vector.create_linestring_from_xyz_points(points: Union[numpy.ndarray, geopandas.geodataframe.GeoDataFrame], nodata: Union[int, float] = 9999.0, xcol: str = 'X', ycol: str = 'Y', zcol: str = 'Z', drop_nan: bool = True) → shapely.geometry.linestring.LineString#

Create LineString from an array or GeoDataFrame containing X, Y, and Z coordinates of points.

Parameters

points (Union[np.ndarray, gpd.geodataframe.GeoDataFrame]) – NumPy Array or GeoDataFrame containing XYZ points.
nodata (Union[int, float])) – Nodata value to filter out points outside a designated area, e.g. nodata=9999.0, default is 9999.0.
xcol (str) – Name of the X column in the dataset, e.g. xcol='X', default is 'X'.
ycol (str) – Name of the Y column in the dataset, e.g. ycol='Y', default is 'Y'.
zcol (str) – Name of the Z column in the dataset, e.g. zcol='Z', default is 'Z'.
drop_nan (bool) – Boolean argument to drop points that contain a nan value as Z value. Options include True and False, default is True.

Returns

line – LineString Z constructed from provided point values

Return type

shapely.geometry.linestring.LineString

New in version 1.0.x.

Changed in version 1.1: Adding argument drop_nan and code to drop coordinates that contain nan values as Z coordinates.

Example

>>> # Loading Libraries and creating points
>>> import gemgis as gg
>>> import numpy as np
>>> points = np.array([[3.23, 5.69, 2.03],[3.24, 5.68, 2.02],[3.25, 5.67, 1.97],[3.26, 5.66, 1.95]])

>>> # Creating LineStrings from points
>>> linestring = gg.vector.create_linestring_from_xyz_points(points=points)
>>> linestring.wkt
'LINESTRING Z (3.23 5.69 2.03, 3.24 5.68 2.02, 3.25 5.67 1.97, 3.26 5.66 1.95)'

gemgis.vector.create_linestring_gdf(gdf: geopandas.geodataframe.GeoDataFrame) → geopandas.geodataframe.GeoDataFrame#

Creating LineStrings from Points

Parameters: gdf (gpd.geodataframe.GeoDataFrame) – GeoDataFrame containing the points of intersections between topographic contours and layer boundaries
Returns: gdf_linestring – GeoDataFrame containing LineStrings
Return type: gpd.geodataframe.GeoDataFrame

New in version 1.0.x.

Example

>>> # Loading Libraries and creating Points
>>> import gemgis as gg
>>> from shapely.geometry import Point
>>> import geopandas as gpd
>>> point1 = Point(0,0)
>>> point2 = Point (10,10)

>>> # Creating GeoDataFrame from points and adding additional information
>>> gdf = gpd.GeoDataFrame(geometry=[point1, point2])
>>> gdf['formation'] = 'Layer1'
>>> gdf['Z'] = 100
>>> gdf['id'] = 1
>>> gdf
    geometry            formation   Z   id
0   POINT (0.0 0.0)     Layer1      100 1
1   POINT (10.0 10.0)   Layer1      100 1

>>> # Creating LineString GeoDataFrame
>>> linestring_gdf = gg.vector.create_linestring_gdf(gdf=gdf)
>>> linestring_gdf
    index formation     Z       id      geometry
0   0     Layer1        100     1       LINESTRING (0.00000 0.00000, 10.00000 10.00000)

See also

calculate_azimuth: Calculating the azimuth for orientations on a map
create_linestring_from_points: Create LineString from points
extract_orientations_from_map: Extracting orientations from a map
calculate_distance_linestrings: Calculating the distance between LineStrings
calculate_orientations_from_strike_lines: Calculating the orientations from strike lines

gemgis.vector.create_linestrings_from_contours(contours: pyvista.core.pointset.PolyData, return_gdf: bool = True, crs: Union[str, pyproj.crs.crs.CRS] = None) → Union[List[shapely.geometry.linestring.LineString], geopandas.geodataframe.GeoDataFrame]#

Creating LineStrings from PyVista Contour Lines and save them as list or GeoDataFrame

Parameters

contours (pv.core.pointset.PolyData) – PyVista PolyData dataset containing contour lines extracted from a mesh
return_gdf (bool) – Variable to create GeoDataFrame of the created list of Shapely Objects. Options include: True or False, default set to True
crs (Union[str, pyproj.crs.crs.CRS]) – Name of the CRS provided to reproject coordinates of the GeoDataFrame, e.g. crs='EPSG:4647'

Returns

linestrings – List of LineStrings or GeoDataFrame containing the contours that were converted

Return type

Union[List[shapely.geometry.linestring.LineString], gpd.geodataframe.GeoDataFrame]

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import pyvista as pv
>>> contours = pv.read('file.vtk')
>>> contours
Header
PolyData    Information
N Cells     36337
N Points    36178
X Bounds    3.233e+07, 3.250e+07
Y Bounds    5.704e+06, 5.798e+06
Z Bounds    -2.400e+03, 3.500e+02
N Arrays    1
Data Arrays
Name        Field   Type    N Comp  Min         Max
Depth [m]   Points  float64 1       -2.400e+03  3.500e+02

>>> # Extracting LineStrings from contours
>>> gdf = gg.vector.create_linestrings_from_contours(contours=contours)
>>> gdf
    geometry                                            Z
0   LINESTRING Z (32409587.930 5780538.824 -2350.0...   -2350.00
1   LINESTRING Z (32407304.336 5777048.086 -2050.0...   -2050.00
2   LINESTRING Z (32408748.977 5778005.047 -2200.0...   -2200.00
3   LINESTRING Z (32403693.547 5786613.994 -2400.0...   -2400.00
4   LINESTRING Z (32404738.664 5782672.480 -2350.0...   -2350.00

gemgis.vector.create_linestrings_from_xyz_points(gdf: geopandas.geodataframe.GeoDataFrame, groupby: str, nodata: Union[int, float] = 9999.0, xcol: str = 'X', ycol: str = 'Y', zcol: str = 'Z', dem: Union[numpy.ndarray, rasterio.io.DatasetReader] = None, extent: List[Union[int, float]] = None, return_gdf: bool = True, drop_nan: bool = True) → Union[List[shapely.geometry.linestring.LineString], geopandas.geodataframe.GeoDataFrame]#

Creating LineStrings from a GeoDataFrame containing X, Y, and Z coordinates of vertices of multiple LineStrings

Parameters

gdf (gpd.geodataframe.GeoDataFrame) – GeoDataFrame containing extracted X, Y, and Z coordinates of LineStrings
groupby (str) – Name of a unique identifier the LineStrings can be separated from each other, e.g. groupby='Object_ID'
nodata (Union[int, float])) – Nodata value to filter out points outside a designated area, e.g. nodata=9999.0, default is 9999.0
xcol (str) – Name of the X column in the dataset, e.g. xcol='X', default is 'X'
ycol (str) – Name of the Y column in the dataset, e.g. ycol='Y', default is 'Y'
zcol (str) – Name of the Z column in the dataset, e.g. zcol='Z', default is 'Z'
dem (Union[np.ndarray, rasterio.io.DatasetReader]) – NumPy ndarray or rasterio object containing the height values, default value is None in case geometries contain Z values
extent (List[Union[float, int]]) – Values for minx, maxx, miny and maxy values to define the boundaries of the raster, e.g. extent=[0, 972, 0, 1069]
return_gdf (bool) – Variable to either return the data as GeoDataFrame or as list of LineStrings. Options include: True or False, default set to True
drop_nan (bool) – Boolean argument to drop points that contain a nan value as Z value. Options include True and False, default is True

Returns

linestrings – List of LineStrings or GeoDataFrame containing the LineStrings with Z component

Return type

Union[List[shapely.geometry.linestring.LineString], gpd.geodataframe.GeoDataFrame]

New in version 1.0.x.

Changed in version 1.1: Removed manual dropping of additional columns. Now automatically drops unnecessary coloumns. Adding argument drop_nan and code to drop coordinates that contain nan values as Z coordinates.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import geopandas as gpd
>>> gdf = gpd.read_file(filename='file.shp')
>>> gdf

>>> # Creating LineStrings with Z component from gdf
>>> gdf_linestring = gg.vector.create_linestrings_from_xyz_points(gdf=gdf, groupby='ABS')
>>> gdf_linestring

gemgis.vector.create_polygons_from_faces(mesh: pyvista.core.pointset.PolyData, crs: Union[str, pyproj.crs.crs.CRS], return_gdf: bool = True) → Union[List[shapely.geometry.polygon.Polygon], geopandas.geodataframe.GeoDataFrame]#

Extracting faces from PyVista PolyData as Shapely Polygons

Parameters

mesh (pv.core.pointset.PolyData) – PyVista PolyData dataset
crs – Name of the CRS provided to reproject coordinates of the GeoDataFrame, e.g. crs='EPSG:4647'

Returns

polygons – Triangular Shapely Polygons representing the faces of the mesh

Return type

Union[List[shapely.geometry.polygon.Polygon], gpd.geodataframe.GeoDataFrame]

New in version 1.0.x.

Example

>>> # Importing Libraries and File
>>> import gemgis as gg
>>> import pyvista as pv
>>> mesh = pv.read(filename='mesh.vtk')
>>> mesh
Header
PolyData    Information
N Cells     29273
N Points    40343
X Bounds    2.804e+05, 5.161e+05
Y Bounds    5.640e+06, 5.833e+06
Z Bounds    -8.067e+03, 1.457e+02
N Arrays    1
Data Arrays
Name        Field   Type    N Comp  Min         Max
Depth [m]   Points  float64 1       -8.067e+03  1.457e+02

>>> # Create polygons from mesh faces
>>> polygons = gg.vector.create_polygons_from_faces(mesh=mesh)
>>> polygons
    geometry
0   POLYGON Z ((297077.414 5677487.262 -838.496, 2...
1   POLYGON Z ((298031.070 5678779.547 -648.688, 2...
2   POLYGON Z ((297437.539 5676992.094 -816.608, 2...
3   POLYGON Z ((298031.070 5678779.547 -648.688, 2...
4   POLYGON Z ((295827.680 5680951.574 -825.328, 2...

gemgis.vector.create_unified_buffer(geom_object: Union[geopandas.geodataframe.GeoDataFrame, List[shapely.geometry.base.BaseGeometry]], distance: Union[numpy.ndarray, List[Union[int, float]], float, int]) → shapely.geometry.multipolygon.MultiPolygon#

Creating a unified buffer around Shapely LineStrings or Points

Parameters

geom_object (Union[gpd.geodataframe.GeoDataFrame, List[shapely.geometry.base.BaseGeometry]]) – GeoDataFrame or List of Shapely objects
distance (Union[np.ndarray, List[Union[float, int]], Union[float, int]]) – Distance of the buffer around the geometry object, e.g. distance=10

Returns

polygon – Polygon representing the buffered area around a geometry object

Return type

shapely.geometry.multipolygon.MultiPolygon

New in version 1.0.x.

Example

>>> # Loading Libraries and creating Point
>>> import gemgis as gg
>>> from shapely.geometry import Point
>>> point1 = Point(0,0)
>>> point1.wkt
'POINT (0 0)'

>>> # Creating Point
>>> point2 = Point(20,20)
>>> point2.wkt
'POINT (20 20)'

>>> # Creating list of points
>>> point_list = [point1, point2]

>>> # Creating unified buffer
>>> unified_buffer = gg.vector.create_unified_buffer(geom_object=point_list, distance=10)
>>> unified_buffer
'MULTIPOLYGON (((10 0, 9.95184726672197 -0.980171403295605, 9.807852804032306 -1.950903220161281, 9.56940335732209
-2.902846772544621, 9.23879532511287 -3.826834323650894,...)))'

See also

create_buffer: Creating a buffer around a Shapely LineString or Point

gemgis.vector.create_voronoi_polygons(gdf: geopandas.geodataframe.GeoDataFrame) → geopandas.geodataframe.GeoDataFrame#

Function to create Voronoi Polygons from Point GeoDataFrame using the SciPy Spatial Voronoi class (https://docs.scipy.org/doc/scipy/reference/generated/scipy.spatial.Voronoi.html#scipy.spatial.Voronoi)

Parameters: gdf (gpd.geodataframe.GeoDataFrame) – GeoDataFrame containing the Shapely Points
Returns: gdf_polygons – GeoDataFrame containing the valid Voronoi Polygons
Return type: gpd.geodataframe.GeoDataFrame

New in version 1.1.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import geopandas as gpd
>>> gdf = gpd.read_file('file.shp')
>>> gdf_polygons = gg.vector.create_voronoi_polygons(gdf=gdf)

gemgis.vector.explode_geometry_collection(collection: shapely.geometry.collection.GeometryCollection) → List[shapely.geometry.base.BaseGeometry]#

Exploding a Shapely Geometry Collection to a List of Base Geometries

Parameters: collection (shapely.geometry.collection.GeometryCollection) – Shapely Geometry Collection consisting of different Base Geometries
Returns: collection_exploded – List of Base Geometries from the original Geometry Collection
Return type: List[shapely.geometry.base.BaseGeometry]

New in version 1.0.x.

Example

>>> # Loading Libraries and creating Geometry Collection
>>> import gemgis as gg
>>> from shapely.geometry import LineString
>>> a = LineString([(0, 0), (1, 1), (1,2), (2,2)])
>>> b = LineString([(0, 0), (1, 1), (2,1), (2,2)])
>>> collection = a.intersection(b)
>>> collection.wkt
'GEOMETRYCOLLECTION (POINT (2 2), LINESTRING (0 0, 1 1))'

>>> # Exploding Geometry collection into single Base Geometries
>>> collection_exploded = gg.vector.explode_geometry_collection(collection=collection)
>>> collection_exploded
[<shapely.geometry.point.Point at 0x1faf63ccac0>,
<shapely.geometry.linestring.LineString at 0x1faf63ccb80>]

>>> # Inspecting the first element of the list
>>> collection_exploded[0].wkt
'POINT (2 2)'

>>> # Inspecting the second element of the list
>>> collection_exploded[1].wkt
'LINESTRING (0 0, 1 1)'

See also

explode_geometry_collections: Exploding a GeoDataFrame containing different Base Geometries

gemgis.vector.explode_geometry_collections(gdf: geopandas.geodataframe.GeoDataFrame, reset_index: bool = True, drop_level0: bool = True, drop_level1: bool = True, remove_points: bool = True) → geopandas.geodataframe.GeoDataFrame#

Exploding Shapely Geometry Collections stored in GeoDataFrames to different Shapely Base Geometries

Parameters

gdf (gpd.geodataframe.GeoDataFrame) – GeoDataFrame created from vector data containing elements of geom_type GeometryCollection
reset_index (bool) – Variable to reset the index of the resulting GeoDataFrame. Options include: True or False, default set to True
drop_level0 (bool) – Variable to drop the level_0 column. Options include: True or False, default set to True
drop_level1 (bool) – Variable to drop the level_1 column. Options include: True or False, default set to True
remove_points (bool) – Variable to remove points from exploded GeoDataFrame. Options include: True or False, default set to True

Returns

gdf – GeoDataFrame containing different geometry types

Return type

gpd.geodataframe.GeoDataFrame

New in version 1.0.x.

Example

>>> # Loading Libraries and creating Geometries
>>> import gemgis as gg
>>> from shapely.geometry import LineString, Polygon
>>> import geopandas as gpd
>>> a = LineString([(0, 0), (1, 1), (1,2), (2,2)])
>>> b = LineString([(0, 0), (1, 1), (2,1), (2,2)])
>>> collection = a.intersection(b)
>>> polygon = Polygon([(0, 0), (10, 0), (10, 10), (0, 10)])

>>> # Creating GeoDataFrame from Base Geometries
>>> gdf = gpd.GeoDataFrame(geometry=[a, b, collection, polygon])
>>> gdf
    geometry
0       LINESTRING (0.00000 0.00000, 1.00000 1.00000, ...
1       LINESTRING (0.00000 0.00000, 1.00000 1.00000, ...
2       GEOMETRYCOLLECTION (POINT (2.00000 2.00000), L...
3       POLYGON ((0.00000 0.00000, 10.00000 0.00000, 1..

>>> # Explode Geometry Collection into single Base Geometries
>>> gdf_exploded = gg.vector.explode_geometry_collections(gdf=gdf)
>>> gdf_exploded
    geometry
0       LINESTRING (0.00000 0.00000, 1.00000 1.00000, ...
1       LINESTRING (0.00000 0.00000, 1.00000 1.00000, ...
2       LINESTRING (0.00000 0.00000, 1.00000 1.00000)
3       POLYGON ((0.00000 0.00000, 10.00000 0.00000, 1...

See also

explode_geometry_collection: Exploding a Shapely Geometry Collection Object into a list of Base Geometries

gemgis.vector.explode_linestring(linestring: shapely.geometry.linestring.LineString) → List[shapely.geometry.point.Point]#

Exploding a LineString to its vertices, also works for LineStrings with Z components

Parameters: linestring (shapely.geometry.linestring.LineString) – Shapely LineString from which vertices are extracted, e.g. linestring = LineString([(0, 0), (10, 10), (20, 20)])
Returns: points_list – List of extracted Shapely Points
Return type: List[shapely.geometry.point.Point]

New in version 1.0.x.

Example

>>> # Loading Libraries and creating LineString
>>> import gemgis as gg
>>> from shapely.geometry import LineString
>>> linestring = LineString([(0, 0), (10, 10), (20, 20)])
>>> linestring.wkt
'LINESTRING (0 0, 10 10, 20 20)'

>>> # Exploding LineString into single points
>>> linestring_exploded = gg.vector.explode_linestring(linestring=linestring)
>>> linestring_exploded
[<shapely.geometry.point.Point at 0x20118cb27f0>,
<shapely.geometry.point.Point at 0x20118cb28b0>,
<shapely.geometry.point.Point at 0x20118cb26d0>]

>>> # Inspecting the first element of the list
>>> linestring_exploded[0].wkt
'POINT (0 0)'

>>> # Inspecting the second element of the list
>>> linestring_exploded[1].wkt
'POINT (10 10)'

>>> # Inspecting the third element of the list
>>> linestring_exploded[2].wkt
'POINT (20 20)'

See also

explode_linestring_to_elements: Exploding a LineString with more than two vertices into single LineStrings

gemgis.vector.explode_linestring_to_elements(linestring: shapely.geometry.linestring.LineString) → List[shapely.geometry.linestring.LineString]#

Separating a LineString into its single elements and returning a list of LineStrings representing these elements, also works for LineStrings with Z components

Parameters: linestring (linestring: shapely.geometry.linestring.LineString) – Shapely LineString containing more than two vertices, e.g. linestring = LineString([(0, 0), (10, 10), (20, 20)])
Returns: splitted_linestrings – List containing the separate elements of the original LineString stored as LineStrings
Return type: List[shapely.geometry.linestring.LineString]

New in version 1.0.x.

Example

>>> # Loading Libraries and creating LineString
>>> import gemgis as gg
>>> from shapely.geometry import LineString
>>> linestring = LineString([(0, 0), (10, 10), (20, 20)])
>>> linestring.wkt
'LINESTRING (0 0, 10 10, 20 20)'

>>> # Exploding LineString into single elements
>>> linestring_exploded = gg.vector.explode_linestring_to_elements(linestring=linestring)
>>> linestring_exploded
[<shapely.geometry.linestring.LineString at 0x201448a2100>,
<shapely.geometry.linestring.LineString at 0x20144b5e610>]

>>> # Inspecting the first element of the list
>>> linestring_exploded[0].wkt
'LINESTRING (0 0, 10 10)'

>>> # Inspecting the second element of the list
>>> linestring_exploded[1].wkt
'LINESTRING (10 10, 20 20)'

See also

explode_linestring: Exploding a LineString into its single vertices

gemgis.vector.explode_multilinestring(multilinestring: shapely.geometry.multilinestring.MultiLineString) → List[shapely.geometry.linestring.LineString]#

Exploding a MultiLineString into a list of LineStrings

Parameters: multilinestring (shapely.geometry.multilinestring.MultiLineString) – Shapely MultiLineString consisting of multiple LineStrings, e.g. multilinestring = MultiLineString([((0, 0), (1, 1)), ((-1, 0), (1, 0))])
Returns: splitted_multilinestring – List of Shapely LineStrings
Return type: List[shapely.geometry.linestring.LineString]

New in version 1.0.x.

Example

>>> # Loading Libraries and creating MultiLineString
>>> import gemgis as gg
>>> from shapely.geometry import MultiLineString
>>> coords = [((0, 0), (1, 1)), ((-1, 0), (1, 0))]
>>> lines = MultiLineString(coords)
>>> lines.wkt
'MULTILINESTRING ((0 0, 1 1), (-1 0, 1 0))'

>>> lines_splitted = gg.vector.explode_multilinestrings(multilinestring=lines)
>>> lines_splitted
[<shapely.geometry.linestring.LineString at 0x2014a5f0ee0>,
<shapely.geometry.linestring.LineString at 0x20149dda430>]

>>> # Inspecting the first element of the list
>>> lines_splitted[0].wkt
'LINESTRING (0 0, 1 1)'

>>> # Inspecting the second element of the list
>>> lines_splitted[1].wkt
'LINESTRING (-1 0, 1 0)'

See also

explode_multilinestrings: Exploding a GeoDataFrame containing MultiLineStrings into a GeoDataFrame containing LineStrings only

gemgis.vector.explode_multilinestrings(gdf: geopandas.geodataframe.GeoDataFrame, reset_index: bool = True, drop_level0: bool = True, drop_level1: bool = True) → geopandas.geodataframe.GeoDataFrame#

Exploding Shapely MultiLineStrings stored in a GeoDataFrame to Shapely LineStrings

Parameters

gdf (gpd.geodataframe.GeoDataFrame) – GeoDataFrame created from vector data containing elements of geom_type MultiLineString
reset_index (bool) – Variable to reset the index of the resulting GeoDataFrame. Options include: True or False, default set to True
drop_level0 (bool) – Variable to drop the level_0 column. Options include: True or False, default set to True
drop_level1 (bool) – Variable to drop the level_1 column. Options include: True or False, default set to True

Returns

gdf – GeoDataFrame containing LineStrings

Return type

gpd.geodataframe.GeoDataFrame

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import geopandas as gpd
>>> gdf = gpd.read_file(filename='file.shp')
>>> gdf
    geometry
0   MULTILINESTRING ((0.0 0.0, 1.0 1.0))
1   MULTILINESTRING ((0.0 0.0, 1.0 1.0))

>>> # Exploding MultiLineStrings into single LineStrings
>>> gdf_linestrings = gg.vector.explode_multilinestrings(gdf=gdf, reset_index=True)
>>> gdf_linestrings
    geometry
0       LINESTRING (0.0 0.0, 1.0 1.0)
1       LINESTRING (-1.0 0.0, 1.0 0.0)
2       LINESTRING (0.0 0.0, 1.0 1.0)
3       LINESTRING (-1.0 0.0, 1.0 0.0)

See also

explode_multilinestring: Exploding a MultiLineString into a list of single LineStrings

gemgis.vector.explode_polygon(polygon: shapely.geometry.polygon.Polygon) → List[shapely.geometry.point.Point]#

Exploding Shapely Polygon to list of Points

Parameters: polygon (shapely.geometry.polygon.Polygon) – Shapely Polygon from which vertices are extracted, e.g. polygon = Polygon([(0, 0), (1, 1), (1, 0)])
Returns: point_list – List containing the vertices of a polygon as Shapely Points
Return type: List[shapely.geometry.point.Point]

New in version 1.0.x.

Example

>>> # Loading Libraries and creating Polygon
>>> import gemgis as gg
>>> from shapely.geometry import Polygon
>>> polygon = Polygon([(0, 0), (1, 1), (1, 0)])
>>> polygon.wkt
'POLYGON ((0 0, 1 1, 1 0, 0 0))'

>>> # Exploding Polygon into single Points
>>> polygon_exploded = gg.vector.explode_polygon(polygon=polygon)
>>> polygon_exploded
[<shapely.geometry.point.Point at 0x201459734f0>,
<shapely.geometry.point.Point at 0x20145973670>,
<shapely.geometry.point.Point at 0x20145973640>,
<shapely.geometry.point.Point at 0x201459732e0>]

>>> # Inspecting the first element of the list
>>> polygon_exploded[0].wkt
'POINT (0 0)'

>>> # Inspecting the second element of the list
>>> polygon_exploded[1].wkt
'POINT (1 1)'

See also

explode_polygons: Exploding a GeoDataFrame containing Polygons into a GeoDataFrame containing LineStrings

gemgis.vector.explode_polygons(gdf: geopandas.geodataframe.GeoDataFrame) → geopandas.geodataframe.GeoDataFrame#

Converting a GeoDataFrame containing elements of geom_type Polygons to a GeoDataFrame with LineStrings

Parameters: gdf (gpd.geodataframe.GeoDataFrame) – GeoDataFrame created from vector data containing elements of geom_type Polygon
Returns: gdf_linestrings – GeoDataFrame containing elements of type MultiLineString and LineString
Return type: gpd.geodataframe.GeoDataFrame

New in version 1.0.x.

Example

>>> # Loading Libraries and creating Polygon
>>> import gemgis as gg
>>> import geopandas as gpd
>>> gdf = gpd.read_file(filename='file.shp')
>>> gdf
    geometry
0       POLYGON ((0.0 0.0, 1.0 1.0, 1.0 0.0, 0.0 0.0))
1       POLYGON ((0.0 0.0, 1.0 1.0, 1.0 0.0, 0.0 0.0))

>>> # Exploding Polygons into LineStrings
>>> gdf_exploded = gg.vector.explode_polygons(gdf=gdf)
>>> gdf_exploded
    geometry
0       LINESTRING (0.0 0.0, 1.0 1.0, 1.0 0.0, 0.0 0.0)
1       LINESTRING (0.0 0.0, 1.0 1.0, 1.0 0.0, 0.0 0.0)

See also

explode_polygon: Exploding a Polygon into single Points

gemgis.vector.extract_interfaces_coordinates_from_cross_section(linestring: shapely.geometry.linestring.LineString, interfaces_gdf: geopandas.geodataframe.GeoDataFrame, extract_coordinates: bool = True) → geopandas.geodataframe.GeoDataFrame#

Extracting coordinates of interfaces digitized on a cross section

Parameters

linestring (shapely.geometry.linestring.LineString) – Shapely LineString containing the trace of a cross section on a map, e.g. linestring = LineString([(0, 0), (20, 20)])
interfaces_gdf (gpd.geodataframe.GeoDataFrame) – GeoDataFrame containing the LineStrings of interfaces digitized on a cross section

Returns

gdf – GeoDataFrame containing the extracted coordinates, depth/elevation data and additional columns

Return type

gpd.geodataframe.GeoDataFrame

New in version 1.0.x.

Example

>>> # Loading Libraries and creating LineString
>>> import gemgis as gg
>>> from shapely.geometry import Point, LineString
>>> import geopandas as gpd
>>> linestring = LineString([(0, 0), (20, -20)])
>>> linestring.wkt
'LINESTRING (0 0, 20 -20)'

>>> # Creating second LineString
>>> interfaces = LineString([(2, -2), (5, -5)])
>>> interfaces.wkt
'LINESTRING (2 -2, 5 -5)'

>>> # Creating GeoDataFrame from LineString
>>> gdf = gpd.GeoDataFrame(geometry=[interfaces, interfaces])
>>> gdf
    geometry
0   LINESTRING (2.0 -2.0, 5.0 -5.0)
1   LINESTRING (2.0 -2.0, 5.0 -5.0)

>>> # Extracting interfaces coordinates from cross sections
>>> gdf_points = gg.vector.extract_interfaces_coordinates_from_cross_section(linestring=linestring, interfaces_gdf=gdf)
>>> gdf_points
    geometry                    X       Y       Z
0   POINT (1.41421 -1.41421)    1.41    -1.41   -2.00
1   POINT (3.53553 -3.53553)    3.54    -3.54   -5.00
2   POINT (1.41421 -1.41421)    1.41    -1.41   -2.00
3   POINT (3.53553 -3.53553)    3.54    -3.54   -5.00

See also

calculate_coordinates_for_point_on_cross_section: Calculating the coordinates for a Point on a cross section
calculate_coordinates_for_linestring_on_cross_sections: Calculating the coordinates for one LineString on cross sections
calculate_coordinates_for_linestrings_on_cross_sections: Calculating the coordinates for LineStrings on cross sections
extract_xyz_from_cross_sections: Extracting the X, Y, and Z coordinates of interfaces from cross sections

gemgis.vector.extract_orientations_from_cross_sections(profile_gdf: geopandas.geodataframe.GeoDataFrame, orientations_gdf: geopandas.geodataframe.GeoDataFrame, profile_name_column: str = 'name') → geopandas.geodataframe.GeoDataFrame#

Calculating orientations digitized from cross sections

Parameters

profile_gdf (gpd.geodataframe.GeoDataFrame) – GeoDataFrame containing the different profile traces as LineStrings
orientations_gdf (gpd.geodataframe.GeoDataFrame) – GeoDataFrame containing the orientation LineStrings for different profiles and formations
profile_name_column (str) – Name of the profile column, e.g. profile_name_column='name', default is 'name'

Returns

gdf – GeoDataFrame containing the orientation and location data for orientations digitized on cross sections

Return type

gpd.geodataframe.GeoDataFrame

New in version 1.0.x.

Example

>>> # Loading Libraries and creating LineString
>>> import gemgis as gg
>>> from shapely.geometry import Point, LineString
>>> import geopandas as gpd
>>> linestring = LineString([(0, 0), (20, -20)])
>>> linestring.wkt
'LINESTRING (0 0, 20 -20)'

>>> # Creating GeoDataFrame from LineString and adding profile names
>>> profile_gdf = gpd.GeoDataFrame(geometry=[linestring, linestring])
>>> profile_gdf['name'] = ['Profile2', 'Profile1']
>>> profile_gdf
    geometry                            name
0   LINESTRING (0.0 0.0, 20.0 -20.0)    Profile2
1   LINESTRING (0.0 0.0, 20.0 -20.0)    Profile1

>>> # Creating second LineString
>>> orientation_linestring = LineString([(2, -2), (5, -5)])
>>> orientation_linestring.wkt
'LINESTRING (2 -2, 5 -5)'

>>> # Creating GeoDataFrame from LineString and adding profile names
>>> orientations_gdf = gpd.GeoDataFrame(geometry=[orientation_linestring, orientation_linestring])
>>> orientations_gdf
    geometry                        name
0   LINESTRING (2.0 -2.0, 5.0 -5.0) Profile2
1   LINESTRING (2.0 -2.0, 5.0 -5.0) Profile1

>>> # Extract orientations from cross sections
>>> orientations = gg.vector.extract_orientations_from_cross_sections(profile_gdf=profile_gdf, orientations_gdf=orientations_gdf)
>>> orientations
    X       Y       Z       dip     azimuth     polarity    geometry                    name
0   2.47    -2.47   -3.50   45.00   135.00      1.00        POINT (2.47487 -2.47487)    Profile2
1   2.47    -2.47   -3.50   45.00   135.00      1.00        POINT (2.47487 -2.47487)    Profile1

gemgis.vector.extract_orientations_from_map(gdf: geopandas.geodataframe.GeoDataFrame, dz: str = 'dZ') → geopandas.geodataframe.GeoDataFrame#

Calculating orientations from LineStrings

Parameters

gdf (gpd.geodataframe.GeoDataFrame) – GeoDataFrame containing the orientation LineStrings
dz (str) – Name of the height difference column, e.g. dz='dZ'

Returns

gdf – GeoDataFrame containing the orientation values

Return type

gpd.geodataframe.GeoDataFrame

New in version 1.0.x.

Example

>>> # Loading Libraries and creating LineString
>>> import gemgis as gg
>>> from shapely.geometry import LineString
>>> import geopandas as gpd
>>> linestring1 = LineString([(0, 0), (20, -20)])
>>> linestring1.wkt
'LINESTRING (0 0, 20 -20)'

>>> # Creating second LineString
>>> linestring2 = LineString([(0, 0), (20, -10)])
>>> linestring2.wkt
'LINESTRING (0 0, 20 -10)'

>>> # Creating GeoDataFrame from LineStrings
>>> gdf = gpd.GeoDataFrame(geometry=[linestring1, linestring2])
>>> gdf['dZ'] = [100, 200]
>>> gdf
    geometry                            dz
0   LINESTRING (0.0 0.0, 20.0 -20.0)    100
1   LINESTRING (0.0 0.0, 20.0 -10.0)    200

>>> # Extracting orientations from map
>>> orientations = gg.vector.extract_orientations_from_map(gdf=gdf)
>>> orientations
    geometry            azimuth dip     X       Y       polarity
0   POINT (10.0 -10.0)  135.00  74.21   10.00   -10.00  1
1   POINT (10.0 -5.0)   116.57  83.62   10.00   -5.00   1

See also

calculate_azimuth: Calculating the azimuth for orientations on a map
create_linestring_from_points: Create LineString from points
create_linestring_gdf: Create GeoDataFrame with LineStrings from points
calculate_distance_linestrings: Calculating the distance between LineStrings
calculate_orientations_from_strike_lines: Calculating the orientations from strike lines

gemgis.vector.extract_xy(gdf: geopandas.geodataframe.GeoDataFrame, reset_index: bool = True, drop_index: bool = True, drop_id: bool = True, drop_points: bool = True, drop_level0: bool = True, drop_level1: bool = True, overwrite_xy: bool = True, target_crs: Union[str, pyproj.crs.crs.CRS] = None, bbox: Optional[Sequence[float]] = None, remove_total_bounds: bool = False, threshold_bounds: Union[float, int] = 0.1) → geopandas.geodataframe.GeoDataFrame#

Extracting X and Y coordinates from a GeoDataFrame (Points, LineStrings, MultiLineStrings, Polygons, Geometry Collections) and returning a GeoDataFrame with X and Y coordinates as additional columns

Parameters

gdf (gpd.geodataframe.GeoDataFrame) – GeoDataFrame created from vector data such as Shapely Points, LineStrings, MultiLineStrings or Polygons or data loaded from disc with GeoPandas (i.e. Shape File)
reset_index (bool) – Variable to reset the index of the resulting GeoDataFrame. Options include: True or False, default set to True
drop_level0 (bool) – Variable to drop the level_0 column. Options include: True or False, default set to True
drop_level1 (bool) – Variable to drop the level_1 column. Options include: True or False, default set to True
drop_index (bool) – Variable to drop the index column. Options include: True or False, default set to True
drop_id (bool) – Variable to drop the id column. Options include: True or False, default set to True
drop_points (bool) – Variable to drop the points column. Options include: True or False, default set to True
overwrite_xy (bool) – Variable to overwrite existing X and Y values. Options include: True or False, default set to False
target_crs (Union[str, pyproj.crs.crs.CRS]) – Name of the CRS provided to reproject coordinates of the GeoDataFrame, e.g. target_crs='EPSG:4647'
bbox (list) – Values (minx, maxx, miny, maxy) to limit the extent of the data, e.g. bbox=[0, 972, 0, 1069]
remove_total_bounds (bool) – Variable to remove the vertices representing the total bounds of a GeoDataFrame consisting of Polygons Options include: True or False, default set to False
threshold_bounds (Union[float, int]) – Variable to set the distance to the total bound from where vertices are being removed, e.g. threshold_bounds=10, default set to 0.1

Returns

gdf – GeoDataFrame with appended x, y columns and Point geometry features

Return type

gpd.geodataframe.GeoDataFrame

New in version 1.0.x.

Changed in version 1.1: If a GeoDataFrame contains LineStrings and MultiLineStrings, the index of the exploded GeoDataFrame will now be reset. Not resetting the index will cause index errors later on.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import geopandas as gpd
>>> gdf = gpd.read_file(filename='file.shp')
>>> gdf
    id      formation   geometry
0       None    Ton             POINT (19.150 293.313)
1       None    Ton             POINT (61.934 381.459)
2       None    Ton             POINT (109.358 480.946)
3       None    Ton             POINT (157.812 615.999)
4       None    Ton             POINT (191.318 719.094)

>>> # Extracting X and Y Coordinates from Shapely Base Geometries
>>> gdf_xy = gg.vector.extract_xy(gdf=gdf, reset_index=False)
>>> gdf_xy
    formation   geometry                X       Y
0       Ton             POINT (19.150 293.313)  19.15   293.31
1       Ton             POINT (61.934 381.459)  61.93   381.46
2       Ton             POINT (109.358 480.946) 109.36  480.95
3       Ton             POINT (157.812 615.999) 157.81  616.00
4       Ton             POINT (191.318 719.094) 191.32  719.09

See also

extract_xy_points: Extracting X and Y coordinates from a GeoDataFrame containing Shapely Points
extract_xy_linestring: Extracting X and Y coordinates from a GeoDataFrame containing Shapely LineStrings and saving the X and Y coordinates as lists for each LineString
extract_xy_linestrings: Extracting X and Y coordinates from a GeoDataFrame containing Shapely LineStrings

Note

GeoDataFrames that contain multiple types of geometries are currently not supported. Please use gdf = gdf.explode().reset_index(drop=True) to create a GeoDataFrame with only one type of geometries

gemgis.vector.extract_xy_from_polygon_intersections(gdf: geopandas.geodataframe.GeoDataFrame, extract_coordinates: bool = False, drop_index: bool = True) → geopandas.geodataframe.GeoDataFrame#

Calculating the intersections between Polygons; the table must be sorted by stratigraphic age

Parameters

gdf (gpd.geodataframe.GeoDataFrame) – GeoDataFrame containing Polygons of a geological map ordered by their stratigraphic age
extract_coordinates (bool) – Variable to extract X and Y coordinates from resulting Shapely Objects. Options include: True or False, default set to False
drop_index (bool) – Variable to drop the index column. Options include: True or False, default set to True

Returns

intersections – GeoDataFrame containing the intersections of the polygons of a geological map

Return type

gpd.geodataframe.GeoDataFrame

New in version 1.0.x.

Example

>>> # Loading Libraries and creating Polygon
>>> import gemgis as gg
>>> from shapely.geometry import Polygon
>>> import geopandas as gpd
>>> polygon1 = Polygon([[0, 0], [10, 0], [10, 10], [0, 10], [0, 0]])
>>> polygon1.wkt
'POLYGON ((0 0, 10 0, 10 10, 0 10, 0 0))'

>>> # Creating second Polygon
>>> polygon2 = Polygon([[10, 0], [20, 0], [20, 10], [10, 10], [10, 0]])
>>> polygon2.wkt
'POLYGON ((10 0, 20 0, 20 10, 10 10, 10 0))'

>>> # Creating GeoDataFrame from polygons and adding formation names
>>> gdf = gpd.GeoDataFrame(geometry=[polygon1, polygon2])
>>> gdf['formation'] = ['Formation1', 'Formation2']
>>> gdf
    geometry                                    formation
0   POLYGON (((0 0, 10 0, 10 10, 0 10, 0 0))    Formation1
1   POLYGON ((10 0, 20 0, 20 10, 10 10, 10 0))  Formation2

>>> # Extracting X an Y coordinates from polygon intersections
>>> intersection = gg.vector.extract_xy_from_polygon_intersections(gdf=gdf)
>>> intersection
    formation   geometry
0   Formation1  LINESTRING (10.0 0.0, 10.0 10.0)

See also

intersection_polygon_polygon: Intersecting a polygon with a polygon
intersections_polygon_polygons: Intersecting a polygons with multiple polygons
intersections_polygons_polygons: Intersecting multiple polygons with multiple polygons

gemgis.vector.extract_xy_linestring(gdf: geopandas.geodataframe.GeoDataFrame, target_crs: Union[str, pyproj.crs.crs.CRS] = None, bbox: Optional[Sequence[float]] = None) → geopandas.geodataframe.GeoDataFrame#

Extracting the coordinates of Shapely LineStrings within a GeoDataFrame and storing the X and Y coordinates in lists per LineString

Parameters

gdf (gpd.geodataframe.GeoDataFrame) – GeoDataFrame created from vector data containing elements of geom_type LineString
target_crs (Union[str, pyproj.crs.crs.CRS]) – Name of the CRS provided to reproject coordinates of the GeoDataFrame, e.g. target_crs='EPSG:4647'
bbox (Optional[Sequence[float]]) – Values (minx, maxx, miny, maxy) to limit the extent of the data, e.g. bbox=[0, 972, 0, 1069]

Returns

gdf – GeoDataFrame containing the additional X and Y columns with lists of X and Y coordinates

Return type

gpd.geodataframe.GeoDataFrame

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import geopandas as gpd
>>> gdf = gpd.read_file(filename='file.shp')
>>> gdf
    id      formation   geometry
0       None    Sand1       LINESTRING (0.256 264.862, 10.593 276.734, 17....
1       None    Ton         LINESTRING (0.188 495.787, 8.841 504.142, 41.0...
2       None    Ton         LINESTRING (970.677 833.053, 959.372 800.023, ...

>>> # Extracting X and Y Coordinates from LineString Objects
>>> gdf_xy = gg.vector.extract_xy_linestring(gdf=gdf)
>>> gdf_xy
    id      formation   geometry                                                X                                                       Y
0       None    Sand1       LINESTRING (0.256 264.862, 10.593 276.734, 17....   [0.256327195431048, 10.59346813871597, 17.1349...       [264.86214748436396, 276.73370778641777, 289.0...
1       None    Ton         LINESTRING (0.188 495.787, 8.841 504.142, 41.0...   [0.1881868620686138, 8.840672956663411, 41.092...       [495.787213546976, 504.1418419288791, 546.4230...
2       None    Ton         LINESTRING (970.677 833.053, 959.372 800.023, ...   [970.6766251230017, 959.3724321757514, 941.291...       [833.052616499831, 800.0232029873156, 754.8012...

See also

extract_xy_linestrings: Extracting X and Y coordinates from a GeoDataFrame containing Shapely LineStrings
extract_xy_points: Extracting X and Y coordinates from a GeoDataFrame containing Shapely Points
extract_xy: Extracting X and Y coordinates from Vector Data

gemgis.vector.extract_xy_linestrings(gdf: geopandas.geodataframe.GeoDataFrame, reset_index: bool = True, drop_id: bool = True, drop_index: bool = True, drop_points: bool = True, drop_level0: bool = True, drop_level1: bool = True, overwrite_xy: bool = False, target_crs: Union[str, pyproj.crs.crs.CRS] = None, bbox: Optional[Sequence[float]] = None) → geopandas.geodataframe.GeoDataFrame#

Extracting X and Y coordinates from a GeoDataFrame (LineStrings) and returning a GeoDataFrame with X and Y coordinates as additional columns

Parameters

gdf (gpd.geodataframe.GeoDataFrame) – GeoDataFrame created from vector data containing elements of geom_type LineString
reset_index (bool) – Variable to reset the index of the resulting GeoDataFrame. Options include: True or False, default set to True
drop_id (bool) – Variable to drop the id column. Options include: True or False, default set to True
drop_index (bool) – Variable to drop the index column. Options include: True or False, default set to True
drop_points (bool) – Variable to drop the points column. Options include: True or False, default set to True
drop_level0 (bool) – Variable to drop the level_0 column. Options include: True or False, default set to True
drop_level1 (bool) – Variable to drop the level_1 column. Options include: True or False, default set to True
overwrite_xy (bool) – Variable to overwrite existing X and Y values. Options include: True or False, default set to False
target_crs (Union[str, pyproj.crs.crs.CRS]) – Name of the CRS provided to reproject coordinates of the GeoDataFrame, e.g. target_crs='EPSG:4647'
bbox (Optional[Sequence[float]]) – Values (minx, maxx, miny, maxy) to limit the extent of the data, e.g. bbox=[0, 972, 0, 1069]

Returns

gdf – GeoDataFrame with appended X and Y coordinates as additional columns and optional columns

Return type

gpd.geodataframe.GeoDataFrame

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import geopandas as gpd
>>> gdf = gpd.read_file(filename='file.shp')
>>> gdf
    id      formation   geometry
0       None    Sand1       LINESTRING (0.256 264.862, 10.593 276.734, 17....
1       None    Ton         LINESTRING (0.188 495.787, 8.841 504.142, 41.0...
2       None    Ton         LINESTRING (970.677 833.053, 959.372 800.023, ...

>>> # Extracting X and Y Coordinates from LineString Objects
>>> gdf_xy = gg.vector.extract_xy_linestrings(gdf=gdf, reset_index=False)
>>> gdf_xy
    formation   geometry                X       Y
0       Sand1           POINT (0.256 264.862)   0.26    264.86
1       Sand1           POINT (10.593 276.734)  10.59   276.73
2       Sand1           POINT (17.135 289.090)  17.13   289.09
3       Sand1           POINT (19.150 293.313)  19.15   293.31
4       Sand1           POINT (27.795 310.572)  27.80   310.57

See also

extract_xy_points: Extracting X and Y coordinates from a GeoDataFrame containing Shapely Points
extract_xy_linestring: Extracting X and Y coordinates from a GeoDataFrame containing Shapely LineStrings and saving the X and Y coordinates as lists for each LineString
extract_xy: Extracting X and Y coordinates from Vector Data

Note

The function was adapted to also extract Z coordinates from LineStrings

gemgis.vector.extract_xy_points(gdf: geopandas.geodataframe.GeoDataFrame, reset_index: bool = True, drop_id: bool = True, drop_index: bool = True, overwrite_xy: bool = False, target_crs: Union[str, pyproj.crs.crs.CRS] = None, bbox: Optional[Sequence[float]] = None) → geopandas.geodataframe.GeoDataFrame#

Extracting X and Y coordinates from a GeoDataFrame (Points) and returning a GeoDataFrame with X and Y coordinates as additional columns

Parameters

gdf (gpd.geodataframe.GeoDataFrame) – GeoDataFrame created from vector data containing elements of geom_type Point
reset_index (bool) – Variable to reset the index of the resulting GeoDataFrame. Options include: True or False, default set to True
drop_id (bool) – Variable to drop the id column. Options include: True or False, default set to True
drop_index (bool) – Variable to drop the index column. Options include: True or False, default set to True
overwrite_xy (bool) – Variable to overwrite existing X and Y values. Options include: True or False, default set to False
target_crs (Union[str, pyproj.crs.crs.CRS]) – Name of the CRS provided to reproject coordinates of the GeoDataFrame, e.g. target_crs='EPSG:4647'
bbox (list) – Values (minx, maxx, miny, maxy) to limit the extent of the data, e.g. bbox=[0, 972, 0, 1069]

Returns

gdf – GeoDataFrame with appended X and Y coordinates as new columns and optional columns

Return type

gpd.geodataframe.GeoDataFrame

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import geopandas as gpd
>>> gdf = gpd.read_file(filename='file.shp')
>>> gdf
    id      formation       geometry
0   None    Ton             POINT (19.150 293.313)
1   None    Ton             POINT (61.934 381.459)
2   None    Ton             POINT (109.358 480.946)
3   None    Ton             POINT (157.812 615.999)
4   None    Ton             POINT (191.318 719.094)

>>> # Extracting X and Y Coordinates from Point Objects
>>> gdf_xy = gg.vector.extract_xy_points(gdf=gdf, reset_index=False)
>>> gdf_xy
    formation       geometry                X       Y
0   Ton             POINT (19.150 293.313)  19.15   293.31
1   Ton             POINT (61.934 381.459)  61.93   381.46
2   Ton             POINT (109.358 480.946) 109.36  480.95
3   Ton             POINT (157.812 615.999) 157.81  616.00
4   Ton             POINT (191.318 719.094) 191.32  719.09

See also

extract_xy_linestring: Extracting X and Y coordinates from a GeoDataFrame containing Shapely LineStrings and saving the X and Y coordinates as lists for each LineString
extract_xy_linestrings: Extracting X and Y coordinates from a GeoDataFrame containing Shapely LineStrings
extract_xy: Extracting X and Y coordinates from Vector Data

gemgis.vector.extract_xyz(gdf: geopandas.geodataframe.GeoDataFrame, dem: Union[numpy.ndarray, rasterio.io.DatasetReader] = None, minz: float = None, maxz: float = None, extent: List[Union[int, float]] = None, reset_index: bool = True, drop_index: bool = True, drop_id: bool = True, drop_points: bool = True, drop_level0: bool = True, drop_level1: bool = True, target_crs: Union[str, pyproj.crs.crs.CRS, rasterio.crs.CRS] = None, bbox: Optional[Sequence[float]] = None, remove_total_bounds: bool = False, threshold_bounds: Union[float, int] = 0.1) → geopandas.geodataframe.GeoDataFrame#

Extracting X and Y coordinates from a GeoDataFrame (Points, LineStrings, MultiLineStrings Polygons) and Z values from a NumPy nd.array or a Rasterio object and returning a GeoDataFrame with X, Y, and Z coordinates as additional columns

Parameters

gdf (gpd.geodataframe.GeoDataFrame) – GeoDataFrame created from vector data containing Shapely Points, LineStrings, MultiLineStrings or Polygons
dem (Union[np.ndarray, rasterio.io.DatasetReader]) – NumPy ndarray or Rasterio object containing the height values, default value is None in case geometries contain Z values
minz (float) – Value defining the minimum elevation of the data that needs to be returned, e.g. minz=50, default None
maxz (float) – Value defining the maximum elevation of the data that needs to be returned, e.g. maxz=500, default None
extent (List[Union[float,int]]) – List containing the extent of the np.ndarray, must be provided in the same CRS as the gdf, e.g. extent=[0, 972, 0, 1069]
reset_index (bool) – Variable to reset the index of the resulting GeoDataFrame. Options include: True or False, default set to True
drop_level0 (bool) – Variable to drop the level_0 column. Options include: True or False, default set to True
drop_level1 (bool) – Variable to drop the level_1 column. Options include: True or False, default set to True
drop_index (bool) – Variable to drop the index column. Options include: True or False, default set to True
drop_id (bool) – Variable to drop the id column. Options include: True or False, default set to True
drop_points (bool) – Variable to drop the points column. Options include: True or False, default set to True
target_crs (Union[str, pyproj.crs.crs.CRS, rasterio.crs.CRS]) – Name of the CRS provided to reproject coordinates of the GeoDataFrame, e.g. target_crs='EPSG:4647'
bbox (list) – Values (minx, maxx, miny, maxy) to limit the extent of the data, e.g. bbox=[0, 972, 0, 1069]
remove_total_bounds (bool) – Variable to remove the vertices representing the total bounds of a GeoDataFrame consisting of Polygons Options include: True or False, default set to False
threshold_bounds (Union[float, int]) – Variable to set the distance to the total bound from where vertices are being removed, e.g. threshold_bounds=10, default set to 0.1

Returns

gdf – GeoDataFrame containing the X, Y, and Z coordinates as additional columns

Return type

gpd.geodataframe.GeoDataFrame

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import geopandas as gpd
>>> import rasterio
>>> gdf = gpd.read_file(filename='file.shp')
>>> gdf
    id      formation   geometry
0       None    Ton             POINT (19.150 293.313)
1       None    Ton             POINT (61.934 381.459)
2       None    Ton             POINT (109.358 480.946)
3       None    Ton             POINT (157.812 615.999)
4       None    Ton             POINT (191.318 719.094)

>>> # Loading raster file
>>> dem = rasterio.open(fp='dem.tif')
>>> dem
<open DatasetReader name='dem.tif' mode='r'>

>>> # Extracting X, Y, and Z Coordinates from Shapely Base Geometries and DEM
>>> gdf_xyz = gg.vector.extract_xyz(gdf=gdf, dem=dem, reset_index=reset_index)
>>> gdf_xyz
    formation   geometry                X       Y       Z
0   Ton         POINT (19.150 293.313)  19.15   293.31  364.99
1       Ton             POINT (61.934 381.459)  61.93   381.46  400.34
2       Ton             POINT (109.358 480.946) 109.36  480.95  459.55
3       Ton             POINT (157.812 615.999) 157.81  616.00  525.69
4       Ton             POINT (191.318 719.094) 191.32  719.09  597.63

See also

extract_xyz_array: Extracting X, Y, and Z coordinates from a GeoDataFrame and Digital Elevation Model as array
extract_xyz_rasterio: Extracting X, Y, and Z coordinates from a GeoDataFrame and Digital Elevation as rasterio object

gemgis.vector.extract_xyz_array(gdf: geopandas.geodataframe.GeoDataFrame, dem: numpy.ndarray, extent: List[float], minz: float = None, maxz: float = None, reset_index: bool = True, drop_index: bool = True, drop_id: bool = True, drop_points: bool = True, drop_level0: bool = True, drop_level1: bool = True, target_crs: Union[str, pyproj.crs.crs.CRS] = None, bbox: Optional[Sequence[float]] = None, remove_total_bounds: bool = False, threshold_bounds: Union[float, int] = 0.1) → geopandas.geodataframe.GeoDataFrame#

Extracting X and Y coordinates from a GeoDataFrame (Points, LineStrings, MultiLineStrings Polygons) and Z values from a NumPy nd.array and returning a GeoDataFrame with X, Y, and Z coordinates as additional columns

Parameters

gdf (gpd.geodataframe.GeoDataFrame) – GeoDataFrame created from vector data containing Shapely Points, LineStrings, MultiLineStrings or Polygons
dem (np.ndarray) – NumPy ndarray containing the height values
extent (list) – List containing the extent of the np.ndarray, must be provided in the same CRS as the gdf, e.g. extent=[0, 972, 0, 1069]
minz (float) – Value defining the minimum elevation the data needs to be returned, e.g. minz=50, default None
maxz (float) – Value defining the maximum elevation the data needs to be returned, e.g. maxz=500, default None
reset_index (bool) – Variable to reset the index of the resulting GeoDataFrame. Options include: True or False, default set to True
drop_level0 (bool) – Variable to drop the level_0 column. Options include: True or False, default set to True
drop_level1 (bool) – Variable to drop the level_1 column. Options include: True or False, default set to True
drop_index (bool) – Variable to drop the index column. Options include: True or False, default set to True
drop_id (bool) – Variable to drop the id column. Options include: True or False, default set to True
drop_points (bool) – Variable to drop the points column. Options include: True or False, default set to True
target_crs (Union[str, pyproj.crs.crs.CRS]) – Name of the CRS provided to reproject coordinates of the GeoDataFrame, e.g. target_crs='EPSG:4647'
bbox (list) – Values (minx, maxx, miny, maxy) to limit the extent of the data, e.g. bbox=[0, 972, 0, 1069]
remove_total_bounds (bool) – Variable to remove the vertices representing the total bounds of a GeoDataFrame consisting of Polygons Options include: True or False, default set to False
threshold_bounds (Union[float, int]) – Variable to set the distance to the total bound from where vertices are being removed, e.g. threshold_bounds=10, default set to 0.1

Returns

gdf – GeoDataFrame containing the X, Y, and Z coordinates

Return type

gpd.geodataframe.GeoDataFrame

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import geopandas as gpd
>>> import rasterio
>>> gdf = gpd.read_file(filename='file.shp')
>>> gdf
    id      formation   geometry
0       None    Ton             POINT (19.150 293.313)
1       None    Ton             POINT (61.934 381.459)
2       None    Ton             POINT (109.358 480.946)
3       None    Ton             POINT (157.812 615.999)
4       None    Ton             POINT (191.318 719.094)

>>> # Loading raster file
>>> dem = rasterio.open(fp='dem.tif')
>>> dem
<open DatasetReader name='dem.tif' mode='r'>

>>> # Defining the extent of the array
>>> extent = [0, 972, 0, 1069]

>>> # Extracting X, Y, and Z Coordinates from Shapely Base Geometries and array
>>> gdf_xyz = gg.vector.extract_xyz_array(gdf=gdf, dem=dem.read(1), extent=extent, reset_index=reset_index)
>>> gdf_xyz
    formation   geometry                X       Y       Z
0   Ton         POINT (19.150 293.313)  19.15   293.31  364.99
1       Ton             POINT (61.934 381.459)  61.93   381.46  400.34
2       Ton             POINT (109.358 480.946) 109.36  480.95  459.55
3       Ton             POINT (157.812 615.999) 157.81  616.00  525.69
4       Ton             POINT (191.318 719.094) 191.32  719.09  597.63

See also

extract_xyz_rasterio: Extracting X, Y, and Z coordinates from a GeoDataFrame and Digital Elevation Model as rasterio object
extract_xyz: Extracting X, Y, and Z coordinates from a GeoDataFrame and Digital Elevation Model

gemgis.vector.extract_xyz_from_cross_sections(profile_gdf: geopandas.geodataframe.GeoDataFrame, interfaces_gdf: geopandas.geodataframe.GeoDataFrame, profile_name_column: str = 'name') → geopandas.geodataframe.GeoDataFrame#

Extracting X, Y, and Z coordinates from cross sections and digitized interfaces

Parameters

profile_gdf (gpd.geodataframe.GeoDataFrame) – GeoDataFrame containing the traces (LineStrings) of cross sections on a map and a profile name
interfaces_gdf (gpd.geodataframe.GeoDataFrame) – GeoDataFrame containing the LineStrings of digitized interfaces, associated formation and the profile name
profile_name_column (str) – Name of the profile column, default is profile_name_column='name'

Returns

gdf – GeoDataFrame containing the X, Y, and Z information of all extracted digitized interfaces on cross sections

Return type

gpd.geodataframe.GeoDataFrame

New in version 1.0.x.

Example

>>> # Loading Libraries and creating LineString
>>> import gemgis as gg
>>> from shapely.geometry import Point, LineString
>>> import geopandas as gpd
>>> linestring = LineString([(0, 0), (20, -20)])
>>> linestring.wkt
'LINESTRING (0 0, 20 -20)'

>>> # Creating GeoDataFrame from LineString and ad Profile names
>>> profile_gdf = gpd.GeoDataFrame(geometry=[linestring, linestring])
>>> profile_gdf['name'] = ['Profile1', 'Profile2']
>>> profile_gdf
    geometry    name
0       LINESTRING (0.0 0.0, 20.0 -20.0)        Profile1
1       LINESTRING (0.0 0.0, 20.0 -20.0)        Profile2

>>> # Creating second LineString
>>> interfaces = LineString([(2, -2), (5, -5)])
>>> interfaces.wkt
'LINESTRING (2 -2, 5 -5)'

>>> # Creating GeoDataFrame from LineString and ad Profile names
>>> gdf = gpd.GeoDataFrame(geometry=[interfaces, interfaces])
>>> gdf['name'] = ['Profile1', 'Profile2']
>>> gdf
    geometry    name
0       LINESTRING (2.0 -2.0, 5.0 -5.0) Profile1
1       LINESTRING (2.0 -2.0, 5.0 -5.0) Profile2

>>> # Extracting X, Y, and Z coordinates from cross sections
>>> gdf_points = gg.vector.extract_xyz_from_cross_sections(profile_gdf=profile_gdf, interfaces_gdf=gdf)
>>> gdf_points
    name        geometry                        X       Y       Z
0       Profile1        POINT (1.41421 -1.41421)        1.41    -1.41   -2.00
1       Profile1        POINT (3.53553 -3.53553)        3.54    -3.54   -5.00
2       Profile2        POINT (1.41421 -1.41421)        1.41    -1.41   -2.00
3       Profile2        POINT (3.53553 -3.53553)        3.54    -3.54   -5.00

See also

calculate_coordinates_for_point_on_cross_section: Calculating the coordinates for a Point on a cross section
calculate_coordinates_for_linestring_on_cross_sections: Calculating the coordinates for one LineString on cross sections
calculate_coordinates_for_linestrings_on_cross_sections: Calculating the coordinates for LineStrings on cross sections
extract_interfaces_coordinates_from_cross_section: Extracting the coordinates of interfaces from cross sections

gemgis.vector.extract_xyz_linestrings(gdf: geopandas.geodataframe.GeoDataFrame, reset_index: bool = True, drop_index: bool = True) → geopandas.geodataframe.GeoDataFrame#

Extracting X, Y, and Z coordinates from a GeoDataFrame containing Shapely LineStrings with Z components

Parameters

gdf (gpd.geodataframe.GeoDataFrame) – GeoDataFrame containing Shapely LineStrings with X, Y, and Z components
reset_index (bool) – Variable to reset the index of the resulting GeoDataFrame. Options include: True or False, default set to True
drop_index (bool) – Variable to drop the index column. Options include: True or False, default set to True

Returns

gdf – GeoDataFrame containing Shapely Points with appended X, Y, and Z columns

Return type

gpd.geodataframe.GeoDataFrame

New in version 1.0.x.

Example

>>> # Loading Libraries and creating Shapely LineString
>>> import gemgis as gg
>>> from shapely.geometry import LineString
>>> import geopandas as gpd
>>> linestring = LineString(([1,2,3], [4,5,6]))
>>> linestring.wkt
'LINESTRING Z (1 2 3, 4 5 6)'

>>> # Creating GeoDataFrame from LineString
>>> gdf = gpd.GeoDataFrame(geometry=[linestring, linestring])
>>> gdf
    geometry
0   LINESTRING Z (1.00000 2.00000 3.00000, 4.00000...
1   LINESTRING Z (1.00000 2.00000 3.00000, 4.00000...

>>> # Extracting X, Y, and Z Coordinates from Point Objects
>>> gdf = gg.vector.extract_xyz_linestrings(gdf=gdf)
>>> gdf
    geometry                points          X       Y       Z
0   POINT (1.00000 2.00000) (1.0, 2.0, 3.0) 1.00    2.00    3.00
1   POINT (4.00000 5.00000) (4.0, 5.0, 6.0) 4.00    5.00    6.00
2   POINT (1.00000 2.00000) (1.0, 2.0, 3.0) 1.00    2.00    3.00
3   POINT (4.00000 5.00000) (4.0, 5.0, 6.0) 4.00    5.00    6.00

See also

extract_xyz_points: Extracting X and Y coordinates from a GeoDataFrame containing Shapely Points with Z components
extract_xyz_polygons: Extracting X and Y coordinates from a GeoDataFrame containing Shapely Polygons with Z component

gemgis.vector.extract_xyz_points(gdf: geopandas.geodataframe.GeoDataFrame) → geopandas.geodataframe.GeoDataFrame#

Extracting X, Y, and Z coordinates from a GeoDataFrame containing Shapely Points with Z components

Parameters: gdf (gpd.geodataframe.GeoDataFrame) – GeoDataFrame containing Shapely Points with X, Y, and Z components
Returns: gdf – GeoDataFrame containing Shapely Points with appended X, Y, and Z columns
Return type: gpd.geodataframe.GeoDataFrame

New in version 1.0.x.

Example

>>> # Loading Libraries and creating Shapely Point
>>> import gemgis as gg
>>> from shapely.geometry import Point
>>> import geopandas as gpd
>>> point = Point(1,2,4)
>>> point.wkt
'POINT Z (0 0 0)'

>>> # Creating GeoDataFrame from Point
>>> gdf = gpd.GeoDataFrame(geometry=[point, point])
>>> gdf
    geometry
0   POINT Z (0.00000 0.00000 0.00000)
1   POINT Z (0.00000 0.00000 0.00000)

>>> # Extracting X, Y, and Z Coordinates from Point Objects
>>> gdf = gg.vector.extract_xyz_points(gdf=gdf)
>>> gdf
    geometry                            X       Y       Z
0   POINT Z (1.00000 2.00000 3.00000)   1.00    2.00    3.00
1   POINT Z (1.00000 2.00000 3.00000)   1.00    2.00    3.00

See also

extract_xyz_linestrings: Extracting X and Y coordinates from a GeoDataFrame containing Shapely LineStrings with Z components
extract_xyz_polygons: Extracting X and Y coordinates from a GeoDataFrame containing Shapely Polygons with Z component

gemgis.vector.extract_xyz_polygons(gdf: geopandas.geodataframe.GeoDataFrame, reset_index: bool = True, drop_index: bool = True) → geopandas.geodataframe.GeoDataFrame#

Extracting X, Y, and Z coordinates from a GeoDataFrame containing Shapely Polygons with Z components

Parameters

gdf (gpd.geodataframe.GeoDataFrame) – GeoDataFrame containing Shapely Polygons with X, Y, and Z components
reset_index (bool) – Variable to reset the index of the resulting GeoDataFrame. Options include: True or False, default set to True
drop_index (bool) – Variable to drop the index column. Options include: True or False, default set to True

Returns

gdf – GeoDataFrame containing Shapely Points with appended X, Y, and Z columns

Return type

gpd.geodataframe.GeoDataFrame

New in version 1.0.x.

Example

>>> # Loading Libraries and creating Shapely Polygon
>>> import gemgis as gg
>>> from shapely.geometry import Polygon
>>> import geopandas as gpd
>>> polygon = Polygon([[0, 0, 1], [1, 0, 1], [1, 1, 1], [0, 1, 1], [0, 0, 1]])
>>> polygon.wkt
'POLYGON Z ((0 0 1, 1 0 1, 1 1 1, 0 1 1, 0 0 1))'

>>> # Creating GeoDataFrame from LineString
>>> gdf = gpd.GeoDataFrame(geometry=[polygon, polygon])
>>> gdf
    geometry
0       POLYGON Z ((0.00000 0.00000 1.00000, 1.00000 0...
1       POLYGON Z ((0.00000 0.00000 1.00000, 1.00000 0...

>>> # Extracting X, Y, and Z Coordinates from Point Objects
>>> gdf = gg.vector.extract_xyz_polygons(gdf=gdf)
>>> gdf
    geometry                points          X       Y       Z
0   POINT (0.00000 0.00000) [0.0, 0.0, 1.0] 0.00    0.00    1.00
1   POINT (1.00000 0.00000) [1.0, 0.0, 1.0] 1.00    0.00    1.00
2   POINT (1.00000 1.00000) [1.0, 1.0, 1.0] 1.00    1.00    1.00
3   POINT (0.00000 1.00000) [0.0, 1.0, 1.0] 0.00    1.00    1.00

See also

extract_xyz_points: Extracting X and Y coordinates from a GeoDataFrame containing Shapely Points with Z component
extract_xyz_linestrings: Extracting X and Y coordinates from a GeoDataFrame containing Shapely LineStrings with Z components

gemgis.vector.extract_xyz_rasterio(gdf: geopandas.geodataframe.GeoDataFrame, dem: rasterio.io.DatasetReader, minz: float = None, maxz: float = None, reset_index: bool = True, drop_index: bool = True, drop_id: bool = True, drop_points: bool = True, drop_level0: bool = True, drop_level1: bool = True, target_crs: Union[str, pyproj.crs.crs.CRS, rasterio.crs.CRS] = None, bbox: Optional[Sequence[float]] = None, remove_total_bounds: bool = False, threshold_bounds: Union[float, int] = 0.1) → geopandas.geodataframe.GeoDataFrame#

Extracting X and Y coordinates from a GeoDataFrame (Points, LineStrings, MultiLineStrings Polygons) and z values from a rasterio object and returning a GeoDataFrame with X, Y, and Z coordinates as additional columns

Parameters

gdf (gpd.geodataframe.GeoDataFrame) – GeoDataFrame created from vector data containing Shapely Points, LineStrings, MultiLineStrings or Polygons
dem (rasterio.io.DatasetReader) – Rasterio object containing the height values
minz (float) – Value defining the minimum elevation the data needs to be returned, e.g. minz=50, default None
maxz (float) – Value defining the maximum elevation the data needs to be returned, e.g. maxz=500, default None
reset_index (bool) – Variable to reset the index of the resulting GeoDataFrame, default True
drop_level0 (bool) – Variable to drop the level_0 column. Options include: True or False, default set to True
drop_level1 (bool) – Variable to drop the level_1 column. Options include: True or False, default set to True
drop_index (bool) – Variable to drop the index column. Options include: True or False, default set to True
drop_id (bool) – Variable to drop the id column. Options include: True or False, default set to True
drop_points (bool) – Variable to drop the points column. Options include: True or False, default set to True
target_crs (Union[str, pyproj.crs.crs.CRS, rasterio.crs.CRS]) – Name of the CRS provided to reproject coordinates of the GeoDataFrame, e.g. target_crs='EPSG:4647'
bbox (list) – Values (minx, maxx, miny, maxy) to limit the extent of the data, e.g. bbox=[0, 972, 0, 1069]
remove_total_bounds (bool) – Variable to remove the vertices representing the total bounds of a GeoDataFrame consisting of Polygons Options include: True or False, default set to False
threshold_bounds (Union[float, int]) – Variable to set the distance to the total bound from where vertices are being removed, e.g. threshold_bounds=10, default set to 0.1

Returns

gdf – GeoDataFrame containing the X, Y, and Z coordinates

Return type

gpd.geodataframe.GeoDataFrame

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import geopandas as gpd
>>> import rasterio
>>> gdf = gpd.read_file(filename='file.shp')
>>> gdf
    id      formation   geometry
0       None    Ton             POINT (19.150 293.313)
1       None    Ton             POINT (61.934 381.459)
2       None    Ton             POINT (109.358 480.946)
3       None    Ton             POINT (157.812 615.999)
4       None    Ton             POINT (191.318 719.094)

>>> # Loading raster file
>>> dem = rasterio.open(fp='dem.tif')
>>> dem
<open DatasetReader name='dem.tif' mode='r'>

>>> # Extracting X, Y, and Z Coordinates from Shapely Base Geometries and raster
>>> gdf_xyz = gg.vector.extract_xyz_rasterio(gdf=gdf, dem=dem, reset_index=reset_index)
>>> gdf_xyz
    formation   geometry                X       Y       Z
0   Ton         POINT (19.150 293.313)  19.15   293.31  364.99
1       Ton             POINT (61.934 381.459)  61.93   381.46  400.34
2       Ton             POINT (109.358 480.946) 109.36  480.95  459.55
3       Ton             POINT (157.812 615.999) 157.81  616.00  525.69
4       Ton             POINT (191.318 719.094) 191.32  719.09  597.63

See also

extract_xyz_array: Extracting X, Y, and Z coordinates from a GeoDataFrame and Digital Elevation Model as array
extract_xyz: Extracting X, Y, and Z coordinates from a GeoDataFrame and Digital Elevation Model

gemgis.vector.interpolate_raster(gdf: geopandas.geodataframe.GeoDataFrame, value: str = 'Z', method: str = 'nearest', n: int = None, res: int = 1, extent: List[Union[int, float]] = None, seed: int = None, **kwargs) → numpy.ndarray#

Interpolating a raster/digital elevation model from point or line Shape file

Parameters

gdf (gpd.geodataframe.GeoDataFrame) – GeoDataFrame containing vector data of geom_type Point or Line containing the Z values of an area
value (str) – Value to be interpolated, e.g. value='Z', default is 'Z'
method (string) – Method used to interpolate the raster. Options include: 'nearest', 'linear', 'cubic', 'rbf'
res (int) – Resolution of the raster in X and Y direction, e.g. res=50
seed (int) – Seed for the drawing of random numbers, e.g. seed=1
n (int) – Number of samples used for the interpolation, e.g. n=100
extent (List[Union[float, int]]) – Values for minx, maxx, miny and maxy values to define the boundaries of the raster, e.g. extent=[0, 972, 0, 1069]
**kwargs (optional keyword arguments) – For kwargs for rbf and griddata see: https://docs.scipy.org/doc/scipy/reference/interpolate.html

Returns

array – Array representing the interpolated raster/digital elevation model

Return type

np.ndarray

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import geopandas as gpd
>>> gdf = gpd.read_file(filename='file.shp')
>>> gdf
    id  Z       geometry
0       None    400     LINESTRING (0.741 475.441, 35.629 429.247, 77....
1       None    300     LINESTRING (645.965 0.525, 685.141 61.866, 724...
2       None    400     LINESTRING (490.292 0.525, 505.756 40.732, 519...
3       None    600     LINESTRING (911.433 1068.585, 908.856 1026.831...
4       None    700     LINESTRING (228.432 1068.585, 239.772 1017.037...

>>> # Interpolating vector data
>>> raster = gg.vector.interpolate_raster(gdf=gdf, method='rbf')
>>> raster[:2]
array([[393.56371914, 393.50838517, 393.45386851, ..., 396.15856133,
    398.11421775, 400.06334288],
   [393.41982945, 393.36494645, 393.31088433, ..., 396.20694282,
    398.16690286, 400.12027997]])

gemgis.vector.intersection_polygon_polygon(polygon1: shapely.geometry.polygon.Polygon, polygon2: shapely.geometry.polygon.Polygon) → Union[shapely.geometry.linestring.LineString, shapely.geometry.polygon.Polygon]#

Calculating the intersection between to Shapely Polygons

Parameters

polygon1 (shapely.geometry.polygon.Polygon) – First polygon used for intersecting, e.g. polygon1=Polygon([[0, 0], [10, 0], [10, 10], [0, 10], [0, 0]])
polygon2 (shapely.geometry.polygon.Polygon) – Second polygon used for intersecting, e.g. polygon2=Polygon([[0, 0], [10, 0], [10, 10], [0, 10], [0, 0]])

Returns

intersection – Intersected geometry as Shapely Object

Return type

Union[shapely.geometry.linestring.LineString, shapely.geometry.polygon.Polygon]

New in version 1.0.x.

Example

>>> # Loading Libraries
>>> import gemgis as gg
>>> from shapely.geometry import Polygon
>>> polygon1 = Polygon([[0, 0], [10, 0], [10, 10], [0, 10], [0, 0]])
>>> polygon1.wkt
'POLYGON ((0 0, 10 0, 10 10, 0 10, 0 0))'

>>> # Creating second Polygon
>>> polygon2 = Polygon([[10, 0], [20, 0], [20, 10], [10, 10], [10, 0]])
>>> polygon2.wkt
'POLYGON ((10 0, 20 0, 20 10, 10 10, 10 0))'

>>> # Calculating the intersection between two polygons
>>> intersection = gg.vector.intersection_polygon_polygon(polygon1=polygon1, polygon2=polygon2)
>>> intersection.wkt
'LINESTRING (10 0, 10 10)'

See also

intersections_polygon_polygons: Intersecting a polygon with mutiple polygons
intersections_polygons_polygons: Intersecting multiple polygons with multiple polygons
extract_xy_from_polygon_intersections: Extracting intersections between multiple polygons

gemgis.vector.intersections_polygon_polygons(polygon1: shapely.geometry.polygon.Polygon, polygons2: Union[geopandas.geodataframe.GeoDataFrame, List[shapely.geometry.polygon.Polygon]]) → List[shapely.geometry.base.BaseGeometry]#

Calculating the intersections between one polygon and a list of polygons

Parameters

polygon1 (shapely.geometry.polygon.Polygon) – First polygon used for intersecting, e.g. polygon1=Polygon([[0, 0], [10, 0], [10, 10], [0, 10], [0, 0]])
polygons2 (Union[gpd.geodataframe.GeoDataFrame, List[shapely.geometry.polygon.Polygon]]) – List of polygons as list or GeoDataFrame to get intersected

Returns

intersections – List of intersected geometries

Return type

List[shapely.geometry.base.BaseGeometry]

New in version 1.0.x.

Example

>>> # Loading Libraries and creating Polygon
>>> import gemgis as gg
>>> from shapely.geometry import Polygon
>>> polygon1 = Polygon([[0, 0], [10, 0], [10, 10], [0, 10], [0, 0]])
>>> polygon1.wkt
'POLYGON ((0 0, 10 0, 10 10, 0 10, 0 0))'

>>> # Creating second Polygon
>>> polygon2 = Polygon([[10, 0], [20, 0], [20, 10], [10, 10], [10, 0]])
>>> polygon2.wkt
'POLYGON ((10 0, 20 0, 20 10, 10 10, 10 0))'

>>> # Creating list of polygons
>>> polygons2 = [polygon2, polygon2]

>>> # Calculating the intersections between a polygon with polygons
>>> intersection = gg.vector.intersections_polygon_polygons(polygon1=polygon1, polygons2=polygons2)
>>> intersection
[<shapely.geometry.linestring.LineString at 0x231eaf22100>,
<shapely.geometry.linestring.LineString at 0x231eab22970>]

>>> # Inspecting the first element of the list
>>> intersection[0].wkt
'LINESTRING (10 0, 10 10)'

>>> # Creating the second element of the list
>>> intersection[1].wkt
'LINESTRING (10 0, 10 10)'

See also

intersection_polygon_polygon: Intersecting a polygon with a polygon
intersections_polygons_polygons: Intersecting multiple polygons with multiple polygons
extract_xy_from_polygon_intersections: Extracting intersections between multiple polygons

gemgis.vector.intersections_polygons_polygons(polygons1: Union[geopandas.geodataframe.GeoDataFrame, List[shapely.geometry.polygon.Polygon]], polygons2: Union[geopandas.geodataframe.GeoDataFrame, List[shapely.geometry.polygon.Polygon]]) → List[shapely.geometry.base.BaseGeometry]#

Calculating the intersections between a list of Polygons

Parameters

polygons1 (Union[gpd.geodataframe.GeoDataFrame, List[shapely.geometry.polygon.Polygon]]) – List of Polygons or GeoDataFrame containing Polygons to be intersected
polygons2 (Union[gpd.geodataframe.GeoDataFrame, List[shapely.geometry.polygon.Polygon]]) – List of Polygons or GeoDataFrame containing Polygons to be intersected

Returns

intersections – List of intersected geometries

Return type

List[shapely.geometry.base.BaseGeometry]

New in version 1.0.x.

Example

>>> # Loading Libraries and creating Polygon
>>> import gemgis as gg
>>> from shapely.geometry import Polygon
>>> polygon1 = Polygon([[0, 0], [10, 0], [10, 10], [0, 10], [0, 0]])
>>> polygon1.wkt
'POLYGON ((0 0, 10 0, 10 10, 0 10, 0 0))'

>>> # Creating list of polygons
>>> polygons1 = [polygon1, polygon1]

>>> # Creating second polygon
>>> polygon2 = Polygon([[10, 0], [20, 0], [20, 10], [10, 10], [10, 0]])
>>> polygon2.wkt
'POLYGON ((10 0, 20 0, 20 10, 10 10, 10 0))'

>>> # Creating list of polygons
>>> polygons2 = [polygon2, polygon2]

>>> # Calculating intersections between polygons and polygons
>>> intersection = gg.vector.intersections_polygons_polygons(polygons1=polygons1, polygons2=polygons2)
>>> intersection
[<shapely.geometry.linestring.LineString at 0x231eaf4dd90>,
<shapely.geometry.linestring.LineString at 0x231ec6e8df0>,
 <shapely.geometry.linestring.LineString at 0x231eaf4dc70>,
 <shapely.geometry.linestring.LineString at 0x231eaf4dd00>]

>>> # Inspecting the first element of the list
>>> intersection[0].wkt
'LINESTRING (10 0, 10 10)'

>>> # Inspecting the second element of the list
>>> intersection[1].wkt
'LINESTRING (10 0, 10 10)'

>>> # Inspecting the third element of the list
>>> intersection[2].wkt
'LINESTRING (10 0, 10 10)'

>>> # Inspecting the fourth element of the list
>>> intersection[3].wkt
'LINESTRING (10 0, 10 10)'

See also

intersection_polygon_polygon: Intersecting a polygon with a polygon
intersections_polygon_polygons: Intersecting a polygons with multiple polygons
extract_xy_from_polygon_intersections: Extracting intersections between multiple polygons

gemgis.vector.load_gpx(path: str, layer: Union[int, str] = 'tracks') → Collection#

Loading a GPX file as collection

Parameters

path (str) – Path to the GPX file, e.g. path='file.gpx'
layer (Union[int, str]) – The integer index or name of a layer in a multi-layer dataset, e.g. layer='tracks', default is tracks

Returns

gpx – Collection containing the GPX data

Return type

dict

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> gpx = gg.vector.load_gpx(path='file.gpx', layer='tracks')
>>> gpx
<open Collection 'file.gpx:tracks', mode 'r' at 0x24f1c90ffa0>

See also

load_gpx_as_dict: Loading a GPX file as dict
load_gpx_as_geometry: Loading a GPX file as Shapely BaseGeometry

gemgis.vector.load_gpx_as_dict(path: str, layer: Union[int, str] = 'tracks') → Collection#

Loading a GPX file as dict

Parameters

path (str) – Path to the GPX file, e.g. path='file.gpx'
layer (Union[int, str]) – The integer index or name of a layer in a multi-layer dataset, e.g. layer='tracks', default is tracks

Returns

gpx_dict – Dict containing the GPX data

Return type

dict

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> gpx = gg.vector.load_gpx_as_dict(path='file.gpx', layer='tracks')
>>> gpx
{'type': 'Feature',
 'id': '0',
 'properties': OrderedDict([('name',
               'First half marathon distance of the year'),
              ('cmt', None),
              ('desc', None),
              ('src', None),
              ('link1_href', None),
              ('link1_text', None),
              ('link1_type', None),
              ('link2_href', None),
              ('link2_text', None),
              ('link2_type', None),
              ('number', None),
              ('type', '9')]),
 'geometry': {'type': 'MultiLineString',
  'coordinates': [[(8.496285, 52.705566),
    (8.49627, 52.705593),
    (8.496234, 52.705629),...]]}}

See also

load_gpx_as: Loading a GPX file as Collection
load_gpx_as_geometry: Loading a GPX file as Shapely BaseGeometry

gemgis.vector.load_gpx_as_geometry(path: str, layer: Union[int, str] = 'tracks') → shapely.geometry.base.BaseGeometry#

Loading a GPX file as Shapely Geometry

Parameters

path (str) – Path to the GPX file, e.g. path='file.gpx'
layer (Union[int, str]) – The integer index or name of a layer in a multi-layer dataset, e.g. layer='tracks', default is tracks

Returns

shape – Shapely BaseGeometry containing the geometry data of the GPX file

Return type

shapely.geometry.base.BaseGeometry

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> gpx = gg.vector.load_gpx_as_geometry(path='file.gpx', layer='tracks')
>>> gpx.wkt
'MULTILINESTRING ((8.496285 52.705566, 8.496270000000001 52.705593, 8.496233999999999 52.705629, 8.496205
52.705664, 8.496181 52.705705, 8.496171 52.705754,...)

See also

load_gpx: Loading a GPX file as Collection
load_gpx_as_dict: Loading a GPX file as dict

gemgis.vector.remove_interfaces_within_fault_buffers(fault_gdf: geopandas.geodataframe.GeoDataFrame, interfaces_gdf: geopandas.geodataframe.GeoDataFrame, distance: Union[int, float] = None, remove_empty_geometries: bool = True, extract_coordinates: bool = True) → Tuple[geopandas.geodataframe.GeoDataFrame, geopandas.geodataframe.GeoDataFrame]#

Function to create a buffer around a GeoDataFrame containing fault data and removing interface points that are located within this buffer

Parameters

fault_gdf (gpd.geodataframe.GeoDataFrame) – GeoDataFrame containing the fault data
interfaces_gdf (gpd.geodataframe.GeoDataFrame) – GeoDataFrame containing the interface point data
distance (float, int) – Distance of the buffer around the geometry object, e.g. distance=10
remove_empty_geometries (bool) – Variable to remove empty geometries, Options include: True or False default True
extract_coordinates (bool) – Variable to extract X and Y coordinates from resulting Shapely Objects, Options include: True or False default True

Returns

gdf_out (gpd.geodataframe.GeoDataFrame) – GeoDataFrame containing the vertices located outside the fault buffer
gdf_in (gpd.geodataframe.GeoDataFrame) – GeoDataFrame containing the vertices located inside the fault buffer

New in version 1.0.x.

Example

>>> # Loading Libraries
>>> import gemgis as gg
>>> import geopandas as gpd
>>> from shapely.geometry import Point, LineString

>>> # Creating first Point
>>> point1 = Point(0, 0)
>>> point1.wkt
'POINT (0 0)'

>>> # Creating second Point
>>> point2 = Point(5, 0)
>>> point2.wkt
'POINT (5 0)'

>>> # Creating GeoDataFrame from Points
>>> fault_gdf = gpd.GeoDataFrame(geometry=[point1, point2])

>>> # Creating first LineString
>>> linestring1 = LineString([(0, 0), (10, 10), (20, 20)])
>>> linestring1.wkt
'LINESTRING (0 0, 10 10, 20 20)'

>>> # Creating second LineString
>>> linestring2 = LineString([(10, 0), (20, 10), (30, 20)])
>>> linestring2.wkt
'LINESTRING (0 0, 10 10, 20 20)'

>>> # Creating GeoDataFrame from LineStrings
>>> buffer_objects_gdf = gpd.GeoDataFrame(geometry=[linestring1, linestring2])

>>> # Removing interfaces within fault buffers
>>> result_out, result_in = gg.vector.remove_interfaces_within_fault_buffers(fault_gdf=fault_gdf, interfaces_gdf=buffer_objects_gdf, distance=10)

>>> # Inspecting the Base Geometries that remain outside
>>> result_out
    geometry                    X       Y
0       POINT (7.07107 7.07107)         7.07    7.07
1       POINT (10.00000 10.00000)       10.00   10.00
2       POINT (20.00000 20.00000)       20.00   20.00
3       POINT (10.00000 0.00000)        10.00   0.00
4       POINT (20.00000 10.00000)       20.00   10.00
5       POINT (30.00000 20.00000)       30.00   20.00

>>> # Inspecting the Base Geometries that remain inside
>>> result_in
    geometry            X       Y
0       POINT (0.00000 0.00000) 0.00    0.00
1       POINT (7.07107 7.07107) 7.07    7.07

See also

remove_object_within_buffer: Removing one object from one buffered object
remove_objects_within_buffer: Removing several objects from one buffered object

gemgis.vector.remove_object_within_buffer(buffer_object: shapely.geometry.base.BaseGeometry, buffered_object: shapely.geometry.base.BaseGeometry, distance: Union[int, float] = None, buffer: bool = True) → Tuple[shapely.geometry.base.BaseGeometry, shapely.geometry.base.BaseGeometry]#

Removing object from a buffered object by providing a distance

Parameters

buffer_object (shapely.geometry.base.BaseGeometry) – Shapely object for which a buffer will be created, e.g. buffer_object=Point(0, 0)
buffered_object (shapely.geometry.base.BaseGeometry) – Shapely object that will be removed from the buffer, e.g. buffered_object=LineString([(0, 0), (10, 10), (20, 20)])
distance (Union[float, int]) – Distance of the buffer around the geometry object, e.g. distance=10, default is None
buffer (bool) – Variable to create a buffer. Options include: True or False, default set to True

Returns

result_out (shapely.geometry.base.BaseGeometry) – Shapely object that remains after the buffering (outside the buffer)
result_in (shapely.geometry.base.BaseGeometry) – Shapely object that was buffered (inside the buffer)

New in version 1.0.x.

Example

>>> # Loading Libraries and creating Point
>>> import gemgis as gg
>>> from shapely.geometry import Point, LineString
>>> point = Point(0, 0)
>>> point.wkt
'POINT (0 0)'

>>> # Creating LineString
>>> linestring = LineString([(0, 0), (10, 10), (20, 20)])
>>> linestring.wkt
'LINESTRING (0 0, 10 10, 20 20)'

>>> # Removing object within buffer
>>> result_out, result_in = gg.vector.remove_object_within_buffer(buffer_object=point, buffered_object=linestring, distance=10)

>>> # Inspecting the Base Geometry that remains outside
>>> result_out.wkt
'LINESTRING (7.071067811865473 7.071067811865473, 10 10, 20 20)'

>>> # Inspecting the Base Geometry that remains inside
>>> result_in.wkt
'LINESTRING (0 0, 7.071067811865473 7.071067811865473)'

See also

remove_objects_within_buffer: Removing several objects from one buffered object
remove_interfaces_within_fault_buffers: Removing interfaces of layer boundaries within fault line buffers

gemgis.vector.remove_objects_within_buffer(buffer_object: shapely.geometry.base.BaseGeometry, buffered_objects_gdf: Union[geopandas.geodataframe.GeoDataFrame, List[shapely.geometry.base.BaseGeometry]], distance: Union[int, float] = None, return_gdfs: bool = False, remove_empty_geometries: bool = False, extract_coordinates: bool = False, buffer: bool = True) → Tuple[Union[List[shapely.geometry.base.BaseGeometry], geopandas.geodataframe.GeoDataFrame], Union[List[shapely.geometry.base.BaseGeometry], geopandas.geodataframe.GeoDataFrame]]#

Removing objects from a buffered object by providing a distance

Parameters

buffer_object (shapely.geometry.base.BaseGeometry) – Shapely object for which a buffer will be created, e.g. buffer_object=Point(0, 0)
buffered_object_gdf (Union[gpd.geodataframe.GeoDataFrame, List[shapely.geometry.base.BaseGeometry]]) – GeoDataFrame or List of Base Geometries containing Shapely objects that will be buffered by the buffer object
distance (float, int) – Distance of the buffer around the geometry object, e.g. distance=10
return_gdfs (bool) – Variable to create GeoDataFrames of the created list of Shapely Objects. Options include: True or False, default set to False
remove_empty_geometries (bool) – Variable to remove empty geometries. Options include: True or False, default set to False
extract_coordinates (bool) – Variable to extract X and Y coordinates from resulting Shapely Objects. Options include: True or False, default set to False
buffer (bool) – Variable to create a buffer. Options include: True or False, default set to True

Returns

result_out (list, gpd.geodataframe.GeoDataFrame) – List or GeoDataFrame of Shapely objects that remain after the buffering (outside the buffer)
result_in (list, gpd.geodataframe.GeoDataFrame) – List or GeoDataFrame of Shapely objects that was buffered (inside the buffer)

New in version 1.0.x.

Example

>>> # Loading Libraries and creating Point
>>> import gemgis as gg
>>> from shapely.geometry import Point, LineString
>>> point = Point(0, 0)
>>> point.wkt
'POINT (0 0)'

>>> # Creating first LineString
>>> linestring1 = LineString([(0, 0), (10, 10), (20, 20)])
>>> linestring1.wkt
'LINESTRING (0 0, 10 10, 20 20)'

>>> # Creating second LineString
>>> linestring2 = LineString([(10, 0), (20, 10), (30, 20)])
>>> linestring2.wkt
'LINESTRING (0 0, 10 10, 20 20)'

>>> # Create list of buffer objects
>>> buffer_objects = [linestring1, linestring2]

>>> # Removing objects within buffer
>>> result_out, result_in = gg.vector.remove_objects_within_buffer(buffer_object=point, buffered_object_gdf=buffer_objects, distance=10)

>>> # Inspecting the Base Geometries that remain outside
>>> result_out
[<shapely.geometry.linestring.LineString at 0x2515421e4f0>,
<shapely.geometry.linestring.LineString at 0x2515421e3d0>]

>>> # Inspecting the Base Geometries that remain inside
>>> result_in
[<shapely.geometry.linestring.LineString at 0x2515421e310>,
<shapely.geometry.linestring.LineString at 0x2515421e6a0>]

See also

remove_object_within_buffer: Removing one object from one buffered object
remove_interfaces_within_fault_buffers: Removing interfaces of layer boundaries within fault line buffers

gemgis.vector.set_dtype(gdf: geopandas.geodataframe.GeoDataFrame, dip: str = 'dip', azimuth: str = 'azimuth', formation: str = 'formation', polarity: str = 'polarity', x: str = 'X', y: str = 'Y', z: str = 'Z') → geopandas.geodataframe.GeoDataFrame#

Checking and setting the dtypes of the input data GeoDataFrame

Parameters

gdf (gpd.geodataframe.GeoDataFrame) – GeoDataFrame containing the input vector data with uncorrected dtypes
dip (str) – Name of the column containing the dip data, e.g dip='dip'
azimuth (str) – Name of the column containing the azimuth data, e.g azimuth='azimuth'
formation (str) – Name of the column containing the formation data, e.g formation='formation'
polarity (str) – Name of the column containing the polarity data, e.g polarity='polarity'
x (str) – Name of the column containing the x coordinates, e.g x='X'
y (str) – Name of the column containing the y coordinates, e.g y='Y'
z (str) – Name of the column containing the z coordinates, e.g z='Z'

Returns

gdf – GeoDataFrame containing the input vector data with corrected dtypes

Return type

gpd.geodataframe.GeoDataFrame

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import geopandas as gpd
>>> gdf = gpd.read_file(filename='file.shp')

>>> # Setting the data types
>>> gdf_dtypes = gg.vector.set_dtype(gdf=gdf)

gemgis.vector.sort_by_stratigraphy(gdf: geopandas.geodataframe.GeoDataFrame, stratigraphy: List[str], formation_column: str = 'formation') → geopandas.geodataframe.GeoDataFrame#

Sorting a GeoDataFrame by a provided list of Stratigraphic Units

Parameters

gdf (gpd.geodataframe.GeoDataFrame) – GeoDataFrame containing the unsorted input polygons
stratigraphy (List[str]) – List containing the stratigraphic units sorted by age, e.g. stratigraphy=['Layer1' , 'Layer2']
formation_column (str) – Name of the formation column, default is formation, e.g. formation_colum='formation'

Returns

gdf_sorted – GeoDataFrame containing the sorted input polygons

Return type

gpd.geodataframe.GeoDataFrame

New in version 1.0.x.

Example

>>> # Loading Libraries and creating Polygon
>>> import gemgis as gg
>>> from shapely.geometry import Polygon
>>> import geopandas as gpd
>>> polygon1 = Polygon([(0, 0), (1, 1), (1, 0)])
>>> polygon1.wkt
'POLYGON ((0 0, 1 1, 1 0, 0 0))'

>>> # Creating second polygon
>>> polygon2 = Polygon([(0, 0), (2, 2), (2, 0)])
>>> polygon2.wkt
'POLYGON ((0 0, 2 2, 2 0, 0 0))'

>>> # Creating GeoDataFrame from polygons
>>> gdf = gpd.GeoDataFrame(geometry=[polygon1, polygon2])
>>> gdf['formation'] = ['Layer2', 'Layer1']
>>> gdf
    geometry                                            formation
0   POLYGON ((0.00000 0.00000, 1.00000 1.00000, 1....   Layer2
1   POLYGON ((10.00000 0.00000, 20.00000 0.00000, ...   Layer1

>>> # Creating stratigraphy list
>>> stratigraphy = ['Layer1' , 'Layer2']

>>> # Sorting GeoDataFrame by stratigraphy
>>> gdf_sorted = gg.vector.sort_by_stratigraphy(gdf=gdf, stratigraphy=stratigraphy)
>>> gdf_sorted
    geometry                                            formation
0   POLYGON ((10.00000 0.00000, 20.00000 0.00000, ...   Layer1
1   POLYGON ((0.00000 0.00000, 1.00000 1.00000, 1....   Layer2

gemgis.vector.subtract_geom_objects(geom_object1: shapely.geometry.base.BaseGeometry, geom_object2: shapely.geometry.base.BaseGeometry) → shapely.geometry.base.BaseGeometry#

Subtracting Shapely geometry objects from each other and returning the left over object

Parameters

geom_object1 (shapely.geometry.base.BaseGeometry) – Shapely object from which other object will be subtracted, e.g. geom_object1 = Polygon([[0, 0], [10, 0], [10, 10], [0, 10], [0, 0]])
geom_object2 (shapely.geometry.base.BaseGeometry) – Shapely object which will be subtracted from other object e.g. geom_object2 = Polygon([[5, 0], [15, 0], [15, 10], [5, 10], [5, 0]])

Returns

result – Shapely object from which the second object was subtracted

Return type

shapely.geometry.base.BaseGeometry

New in version 1.0.x.

Example

>>> # Loading Libraries and creating Polygon
>>> import gemgis as gg
>>> from shapely.geometry import Polygon
>>> polygon1 = Polygon([[0, 0], [10, 0], [10, 10], [0, 10], [0, 0]])
>>> polygon1.wkt
'POLYGON ((0 0, 10 0, 10 10, 0 10, 0 0))'

>>> # Creating second Polygon
>>> polygon2 = Polygon([[5, 0], [15, 0], [15, 10], [5, 10], [5, 0]])
>>> polygon2.wkt
'POLYGON ((5 0, 15 0, 15 10, 5 10, 5 0))'

>>> # Subtracting geometries from each other
>>> difference = gg.vector.subtract_geom_objects(geom_object1=polygon1, geom_object2=polygon2)
>>> difference.wkt
'POLYGON ((5 0, 0 0, 0 10, 5 10, 5 0))'

gemgis.vector.unify_linestrings(linestrings: Union[List[shapely.geometry.linestring.LineString], geopandas.geodataframe.GeoDataFrame], crs: Union[str, pyproj.crs.crs.CRS] = None, return_gdf: bool = True) → Union[List[shapely.geometry.linestring.LineString], geopandas.geodataframe.GeoDataFrame]#

Unifying adjacent LineStrings to form LineStrings with multiple vertices

Parameters

linestrings (Union[List[shapely.geometry.linestring.LineString], gpd.geodataframe.GeoDataFrame]) – LineStrings consisting of two vertices representing extracted contour lines
crs (Union[str, pyproj.crs.crs.CRS]) – Name of the CRS provided to reproject coordinates of the GeoDataFrame, e.g. crs='EPSG:4647'
return_gdf (bool) – Variable to either return the data as GeoDataFrame or as list of LineStrings. Options include: True or False, default set to True

Returns

linestrings_merged – Merged Shapely LineStrings

Return type

Union[List[shapely.geometry.linestring.LineString], gpd.geodataframe.GeoDataFrame]

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import geopandas as gpd
>>> linestrings = gpd.read_file(filename='file.shp')
>>> linestrings
    geometry                                            Z
0   LINESTRING Z (32409587.930 5780538.824 -2350.0...   -2350.00
1   LINESTRING Z (32407304.336 5777048.086 -2050.0...   -2050.00
2   LINESTRING Z (32408748.977 5778005.047 -2200.0...   -2200.00
3   LINESTRING Z (32403693.547 5786613.994 -2400.0...   -2400.00
4   LINESTRING Z (32404738.664 5782672.480 -2350.0...   -2350.00

>>> # Merging linestrings
>>> polygons_linestrings = gg.vector.unify_linestrings(linestrings=linestrings)
>>> polygons_linestrings
    geometry
0   LINESTRING Z (32331825.641 5708789.973 -200.00...
1   LINESTRING Z (32334315.359 5723032.766 -250.00...
2   LINESTRING Z (32332516.312 5722028.768 -250.00...
3   LINESTRING Z (32332712.750 5721717.561 -250.00...
4   LINESTRING Z (32332516.312 5722028.768 -250.00...

gemgis.vector.unify_polygons(polygons: Union[List[shapely.geometry.polygon.Polygon], geopandas.geodataframe.GeoDataFrame], crs: Union[str, pyproj.crs.crs.CRS] = None, return_gdf: bool = True) → Union[List[shapely.geometry.polygon.Polygon], geopandas.geodataframe.GeoDataFrame]#

Unifying adjacent triangular polygons to form larger objects

Parameters

polygons (Union[List[shapely.geometry.polygon.Polygon], gpd.geodataframe.GeoDataFrame]) – Triangular Shapely Polygons representing the faces of the mesh
crs (Union[str, pyproj.crs.crs.CRS]) – Name of the CRS provided to reproject coordinates of the GeoDataFrame, e.g. crs='EPSG:4647'
return_gdf (bool) – Variable to either return the data as GeoDataFrame or as list of LineStrings. Options include: True or False, default set to True

Returns

polygons_merged – Merged Shapely Polygons

Return type

Union[List[shapely.geometry.polygon.Polygon], gpd.geodataframe.GeoDataFrame]

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import geopandas as gpd
>>> polygons = gpd.read_file(filename='file.shp')
>>> polygons
    geometry
0   POLYGON Z ((297077.414 5677487.262 -838.496, 2...
1   POLYGON Z ((298031.070 5678779.547 -648.688, 2...
2   POLYGON Z ((297437.539 5676992.094 -816.608, 2...
3   POLYGON Z ((298031.070 5678779.547 -648.688, 2...
4   POLYGON Z ((295827.680 5680951.574 -825.328, 2...

>>> # Merging polygons
>>> polygons_merged = gg.vector.unify_polygons(polygons=polygons)
>>> polygons_merged
    geometry
0   POLYGON Z ((396733.222 5714544.109 -186.252, 3...
1   POLYGON Z ((390252.635 5712409.037 -543.142, 3...
2   POLYGON Z ((391444.965 5710989.453 -516.000, 3...
3   POLYGON Z ((388410.007 5710903.900 -85.654, 38...
4   POLYGON Z ((384393.963 5714293.104 -614.106, 3...

gemgis.visualization module#

Contributors: Alexander Jüstel, Arthur Endlein Correia, Florian Wellmann, Marius Pischke

gemgis.visualization.add_row_to_boreholes(df_groups: List[pandas.core.frame.DataFrame]) → List[pandas.core.frame.DataFrame]#

Adding additional row to each borehole for further processing for 3D visualization

Parameters: df_groups (List[pd.DataFrame]) – List of Pandas DataFrames containing the borehole data
Returns: df_groups – List of Pandas DataFrames with additional row
Return type: List[pd.DataFrame]

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import pandas as pd
>>> df = pd.read_csv('file.csv')
>>> df
    Unnamed: 0  Index   Name                            X           Y           Z       Altitude    Depth   formation       geometry
0   2091        GD1017  ForschungsbohrungMünsterland1   32386176.36 5763283.15  27.00   107.00      5956.00 OberCampanium   POINT (32386176.36 5763283.15)
1   2092        GD1017  ForschungsbohrungMünsterland1   32386176.36 5763283.15  -193.00 107.00      5956.00 UnterCampanium  POINT (32386176.36 5763283.15)

>>> # Adding row to DataFrames
>>> grouped = df.groupby(['Index'])
>>> df_groups = [grouped.get_group(x) for x in grouped.groups]
>>> list_df = gg.visualization.add_row_to_boreholes(df_groups)
>>> list_df[0]
    Unnamed: 0  Index   Name                            X           Y           Z       Altitude    Depth   formation       geometry
0   NaN         GD1017  ForschungsbohrungMünsterland1   32386176.36 5763283.15  27.00   107.00      5956.00                 NaN
0   2091        GD1017  ForschungsbohrungMünsterland1   32386176.36 5763283.15  27.00   107.00      5956.00 OberCampanium   POINT (32386176.36 5763283.15)
1   2092        GD1017  ForschungsbohrungMünsterland1   32386176.36 5763283.15  -193.00 107.00      5956.00 UnterCampanium  POINT (32386176.36 5763283.15)

See also

create_lines_from_points: Creating lines from points
create_borehole_tube: Creating borehole tube
create_borehole_tubes: Creating tubes from lines
create_borehole_labels: Creating labels for boreholes
create_boreholes_3d: Creating PyVista objects for plotting

gemgis.visualization.calculate_vector(dip: Union[float, int], azimuth: Union[float, int]) → numpy.ndarray#

Calculating the plunge vector of a borehole section

Parameters

dip (Union[float, int]) – Dipping value of a borehole segment, e.g. dip=90
azimuth (Union[float, int]) – Dipping direction of a borehole segment, e.g. azimuth=20

Returns

vector – Plunging/dipping vector of a borehole segment

Return type

np.ndarray

New in version 1.0.x.

Example

>>> # Loading Libraries and define dip and azimuth
>>> import gemgis as gg
>>> dip = 90
>>> azimuth = 20

>>> # Calculating plunging vector
>>> vector = gg.visualization.calculate_vector(dip=dip, azimuth=azimuth)
>>> vector
array([[ 0.364824  ],
[-0.18285081],
[ 0.91294525]])

gemgis.visualization.clip_seismic_data(seismic_data, cdp_start: Optional[int] = None, cdp_end: Optional[int] = None) → pandas.core.frame.DataFrame#

Clipping seismic data loaded with segysak to CDP defined start and end CDP values

Parameters

seismic_data (xarray.core.dataset.Dataset) – seismic data loaded with the segysak package
cdp_start (Union[int, type(None)]) – Value for the start CDP number, e.g. cdp_start=100, default is 'None'
cdp_end (Union[int, type(None)]) – Value for the end CDP number, e.g. cdp_start=200, default is 'None'

Returns

df_seismic_data_selection – DataFrame containing the clipped seismic data

Return type

pd.DataFrame

New in version 1.0.x.

gemgis.visualization.convert_to_rgb(array: numpy.ndarray) → numpy.ndarray#

Converting array values to RGB values

Parameters: array (np.ndarray) – Array containing the different bands of a raster
Returns: array_stacked – Array with converted array values to RGB values
Return type: np.ndarray

New in version 1.0.x.

Example

>>> # Loading Libraries and showing predefined array
>>> import gemgis as gg
>>> import numpy as np
>>> array
array([[0.3647059 , 0.3647059 , 0.49411765],
[0.40784314, 0.40784314, 0.52156866],
[0.8901961 , 0.8901961 , 0.91764706],
...,
[0.59607846, 0.69803923, 0.8       ],
[0.627451  , 0.7372549 , 0.7882353 ],
[0.80784315, 0.78431374, 0.70980394]], dtype=float32)

>>> # Inspecting shape of array
>>> array.shape
(2000, 2800, 3)

>>> # Converting to RGB array
>>> array_stacked = gg.visualization.convert_to_rgb(array=array)
>>> array_stacked
array([[[ 93,  93, 126],
[104, 104, 133],
[227, 227, 234],
...,
[152, 178, 204],
[160, 188, 201],
[206, 200, 181]],
[[247, 246, 248],
[241, 240, 246],
[243, 241, 241],
...,
[150, 177, 205],
[175, 187, 177],
[232, 228, 219]]], dtype=uint8)

>>> # Inspecting shape of array
>>> array_stacked.shape
(2000, 2800, 3)

See also

read_raster: Reading Digital Elevation Model as xarray
drape_array_over_dem: Draping an array of the Digital Elevation Model

gemgis.visualization.create_borehole_labels(df: Union[pandas.core.frame.DataFrame, geopandas.geodataframe.GeoDataFrame]) → pyvista.core.pointset.PolyData#

Create labels for borehole plots.

Parameters: df (Union[pd.DataFrame, gpd.geodataframe.GeoDataFrame]) – (Geo-)DataFrame containing the borehole data.
Returns: borehole_locations – Borehole locations with labels.
Return type: pv.core.pointset.PolyData

New in version 1.0.x.

Changed in version 1.1.1: Fixed a ValueError that was introduced with pandas>2.0.0.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import pandas as pd
>>> df = pd.read_csv('file.csv')
>>> df
    Unnamed: 0  Index   Name                            X           Y           Z       Altitude    Depth   formation       geometry
0   2091        GD1017  ForschungsbohrungMünsterland1   32386176.36 5763283.15  27.00   107.00      5956.00 OberCampanium   POINT (32386176.36 5763283.15)
1   2092        GD1017  ForschungsbohrungMünsterland1   32386176.36 5763283.15  -193.00 107.00      5956.00 UnterCampanium  POINT (32386176.36 5763283.15)

>>> # Creating borehole labels
>>> labels = gg.visualization.create_borehole_labels(df=df)
>>> labels
Header
PolyData    Information
N Cells     2
N Points    2
X Bounds    3.239e+07, 3.240e+07
Y Bounds    5.753e+06, 5.763e+06
Z Bounds    6.000e+01, 1.070e+02
N Arrays    1
Data Arrays
Name    Field   Type    N Comp  Min Max
Labels  Points          1       nan nan

See also

add_row_to_boreholes: Adding a row to each borehole for later processing.
create_lines_from_points: Creating lines from points.
create_borehole_tube: Creating borehole tube.
create_borehole_tubes: Creating tubes from lines.
create_boreholes_3d: Creating PyVista objects for plotting.

gemgis.visualization.create_borehole_tube(df: pandas.core.frame.DataFrame, line: pyvista.core.pointset.PolyData, radius: Union[float, int]) → pyvista.core.pointset.PolyData#

Creating a tube from a line for the 3D visualization of boreholes

Parameters

df (pd.DataFrame) – DataFrame containing the borehole data
line (pv.core.pointset.PolyData) – PyVista line object
radius (Union[float,int]) – Radius of the tube, e.g. 'radius=10'

Returns

tube – PolyData Object representing the borehole tube

Return type

pv.core.pointset.PolyData

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import pandas as pd
>>> df = pd.read_csv('file.csv')
>>> df
    Unnamed: 0  Index   Name                            X           Y           Z       Altitude    Depth   formation       geometry
0   2091        GD1017  ForschungsbohrungMünsterland1   32386176.36 5763283.15  27.00   107.00      5956.00 OberCampanium   POINT (32386176.36 5763283.15)
1   2092        GD1017  ForschungsbohrungMünsterland1   32386176.36 5763283.15  -193.00 107.00      5956.00 UnterCampanium  POINT (32386176.36 5763283.15)

>>> # Adding row to DataFrames
>>> grouped = df.groupby(['Index'])
>>> df_groups = [grouped.get_group(x) for x in grouped.groups]
>>> list_df = gg.visualization.add_row_to_boreholes(df_groups)
>>> list_df[0]
    Unnamed: 0  Index   Name                            X           Y           Z       Altitude    Depth   formation       geometry
0   NaN         GD1017  ForschungsbohrungMünsterland1   32386176.36 5763283.15  27.00   107.00      5956.00                 NaN
0   2091        GD1017  ForschungsbohrungMünsterland1   32386176.36 5763283.15  27.00   107.00      5956.00 OberCampanium   POINT (32386176.36 5763283.15)
1   2092        GD1017  ForschungsbohrungMünsterland1   32386176.36 5763283.15  -193.00 107.00      5956.00 UnterCampanium  POINT (32386176.36 5763283.15)

>>> # Creating Lines from points
>>> line = gg.visualization.create_lines_from_points(df=list_df[0])
>>> line
PolyData    Information
N Cells     39
N Points    20
X Bounds    3.239e+07, 3.239e+07
Y Bounds    5.763e+06, 5.763e+06
Z Bounds    -5.849e+03, 1.070e+02
N Arrays    0

>>> # Creating Tubes from lines
>>> tube = gg.visualization.create_borehole_tube(df=list_df[0], line=line, radius=100)
>>> tube
Header
PolyData    Information
N Cells     418
N Points    1520
X Bounds    3.239e+07, 3.239e+07
Y Bounds    5.762e+06, 5.764e+06
Z Bounds    -5.849e+03, 1.070e+02
N Arrays    2
Data Arrays
Name        Field   Type    N Comp  Min         Max
scalars     Points  int32   1       0.000e+00   1.900e+01
TubeNormals Points  float32 3       -1.000e+00  1.000e+00

See also

add_row_to_boreholes: Adding a row to each borehole for later processing
create_lines_from_points: Creating lines from points
create_borehole_tubes: Creating tubes from lines
create_borehole_labels: Creating labels for boreholes
create_boreholes_3d: Creating PyVista objects for plotting

gemgis.visualization.create_borehole_tubes(df: pandas.core.frame.DataFrame, min_length: Union[float, int], radius: Union[int, float] = 10) → Tuple[List[pyvista.core.pointset.PolyData], List[pandas.core.frame.DataFrame]]#

Creating PyVista Tubes for plotting boreholes in 3D

Parameters

df (pd.DataFrame) – DataFrame containing the extracted borehole data
min_length (Union[float, int]) – Length defining the minimum depth of boreholes to be plotted, e.g. min_length=1000
radius (Union[int, float]) – Radius of the boreholes plotted with PyVista, e.g. radius=100 default is 10 m

Returns

tubes (List[pv.core.pointset.PolyData]) – List of PyVista PolyData Objects
df_groups (List[pd.DataFrame]) – List of DataFrames containing the borehole data

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import pandas as pd
>>> df = pd.read_csv('file.csv')
>>> df
    Unnamed: 0  Index   Name                            X           Y           Z       Altitude    Depth   formation       geometry
0   2091        GD1017  ForschungsbohrungMünsterland1   32386176.36 5763283.15  27.00   107.00      5956.00 OberCampanium   POINT (32386176.36 5763283.15)
1   2092        GD1017  ForschungsbohrungMünsterland1   32386176.36 5763283.15  -193.00 107.00      5956.00 UnterCampanium  POINT (32386176.36 5763283.15)

>>> # Creating borehole tubes
>>> tubes, df_groups = gg.visualization.create_borehole_tubes(df=df, min_length=1000, radius=100)
>>> tubes[0]
Header
PolyData    Information
N Cells     418
N Points    1520
X Bounds    3.239e+07, 3.239e+07
Y Bounds    5.762e+06, 5.764e+06
Z Bounds    -5.849e+03, 1.070e+02
N Arrays    2
Data Arrays
Name        Field   Type    N Comp  Min         Max
scalars     Points  int32   1       0.000e+00   1.900e+01
TubeNormals Points  float32 3       -1.000e+00  1.000e+00

See also

add_row_to_boreholes: Adding a row to each borehole for later processing
create_lines_from_points: Creating lines from points
create_borehole_tube: Creating borehole tube
create_borehole_labels: Creating labels for boreholes
create_boreholes_3d: Creating PyVista objects for plotting

gemgis.visualization.create_boreholes_3d(df: pandas.core.frame.DataFrame, min_length: Union[float, int], color_dict: dict, radius: Union[float, int] = 10) → Tuple[List[pyvista.core.pointset.PolyData], pyvista.core.pointset.PolyData, List[pandas.core.frame.DataFrame]]#

Plotting boreholes in 3D

Parameters

df (pd.DataFrame) – DataFrame containing the extracted borehole data
min_length (Union[float, int]) – Value defining the minimum depth of boreholes to be plotted, e.g. min_length=1000
color_dict (dict) – Dict containing the surface colors of the model
radius (Union[float, int]) – Values of the radius of the boreholes plotted with PyVista, e.g. radius=100, default is 10

Returns

tubes (List[pv.core.pointset.PolyData]) – List of PyVista tubes
labels (pv.core.pointset.PolyData) – PyVista PolyData with Borehole Labels
df_groups (List[pd.DataFrame]) – List containing DataFrames

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import pandas as pd
>>> df = pd.read_csv('file.csv')
>>> df
    Unnamed: 0  Index   Name                            X           Y           Z       Altitude    Depth   formation       geometry
0   2091        GD1017  ForschungsbohrungMünsterland1   32386176.36 5763283.15  27.00   107.00      5956.00 OberCampanium   POINT (32386176.36 5763283.15)
1   2092        GD1017  ForschungsbohrungMünsterland1   32386176.36 5763283.15  -193.00 107.00      5956.00 UnterCampanium  POINT (32386176.36 5763283.15)

>>> # Creating tubes
>>> tubes, labels, df_groups = gg.visualization.create_boreholes_3d(df=df, min_length=10, color_dict=color_dict, radius=1000)
>>> tubes
Information
MultiBlock  Values
N Blocks    2
X Bounds    32385176.360, 32404939.830
Y Bounds    5751889.550, 5764283.150
Z Bounds    -5849.000, 107.000
Blocks
Index   Name        Type
0       Block-00    PolyData
1       Block-01    PolyData

>>> # Inspecting labels
>>> labels
        Header
PolyData    Information
N Cells     2
N Points    2
X Bounds    3.239e+07, 3.240e+07
Y Bounds    5.753e+06, 5.763e+06
Z Bounds    6.000e+01, 1.070e+02
N Arrays    1
Data Arrays
Name    Field   Type    N Comp  Min Max
Labels  Points          1       nan nan

See also

add_row_to_boreholes: Adding a row to each borehole for later processing
create_lines_from_points: Creating lines from points
create_borehole_tube: Creating borehole tube
create_borehole_tubes: Creating tubes from lines
create_borehole_labels: Creating labels for boreholes

gemgis.visualization.create_delaunay_mesh_from_gdf(gdf: geopandas.geodataframe.GeoDataFrame, z: str = 'Z') → pyvista.core.pointset.PolyData#

Creating a delaunay triangulated mesh from surface contour lines

Parameters: gdf (gpd.geodataframe.GeoDataFrame) – GeoDataFrame containing LineStrings representing surface contours
Returns: mesh – Mesh representing the triangulated mesh
Return type: pv.core.pointset.PolyData

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import geopandas as gpd
>>> gdf = gpd.read_file(filename='file.shp')
>>> gdf
    OBJECTID    Z       EINHEIT         Shape_Leng  geometry
0   1.00        -2450   gg_kru_b_l_Z50m 3924.67     LINESTRING (32403313.109 5785053.637, 32402917...
1   2.00        -2400   gg_kru_b_l_Z50m 26332.90    LINESTRING (32410198.859 5781110.785, 32409807...
2   3.00        -2350   gg_kru_b_l_Z50m 31104.28    LINESTRING (32409587.930 5780538.824, 32408824...
3   4.00        -2300   gg_kru_b_l_Z50m 35631.73    LINESTRING (32408977.008 5779966.863, 32408808...
4   5.00        -2250   gg_kru_b_l_Z50m 41702.52    LINESTRING (32407319.922 5779788.672, 32407246...

>>> # Creating PolyData from isolines
>>> mesh = gg.visualization.create_delaunay_mesh_from_gdf(gdf=gdf)
>>> mesh
Header
PolyData    Information
N Cells     45651
N Points    23009
X Bounds    3.233e+07, 3.250e+07
Y Bounds    5.702e+06, 5.798e+06
Z Bounds    -2.450e+03, 4.000e+02
N Arrays    1
Data Arrays
Name        Field   Type    N Comp  Min         Max
Depth [m]   Points  float64 1       -2.450e+03  4.000e+02

See also

create_polydata_from_msh: Creating PolyData dataset from Leapfrog mesh file
create_polydata_from_ts: Creating PolyData dataset from GoCAD Tsurface file
create_polydata_from_dxf: Creating PolyData dataset from DXF object

gemgis.visualization.create_dem_3d(dem: Union[rasterio.io.DatasetReader, numpy.ndarray], extent: List[Union[int, float]] = None, res: int = 1) → pyvista.core.pointset.StructuredGrid#

Plotting the dem in 3D with PyVista

Parameters

dem (Union[rasterio.io.DatasetReader, np.ndarray]) – Rasterio object or NumPy array containing the height values
extent (List[Union[int, float]]) – List containing the bounds of the raster, e.g. extent=[0, 972, 0, 1069]
res (int) – Resolution of the meshgrid, e.g. resolution=1, default is 1

Returns

grid – Grid storing the elevation data

Return type

pyvista.core.pointset.StructuredGrid

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import rasterio
>>> raster = rasterio.open(fp='raster.tif')

>>> # Defining raster extent
>>> extent = [0, 972, 0, 1069]

>>> # Creating mesh from raster data
>>> grid = gg.visualization.create_dem_3d(dem=raster.read(1), extent=extent)
>>> grid
Header
            StructuredGrid  Information
N           Cells           1037028
N           Points          1039068
X           Bounds          0.000e+00, 9.710e+02
Y           Bounds          0.000e+00, 1.068e+03
Z           Bounds          2.650e+02, 7.300e+02
Dimensions                  1069, 972, 1
N Arrays                    1
Data Arrays
Name        Field   Type    N Comp  Min         Max
Elevation   Points  float64 1       2.656e+02   7.305e+02

See also

create_lines_3d_polydata: Creating a mesh from lines
create_points_3d: Creating a mesh from points

gemgis.visualization.create_depth_map(mesh: pyvista.core.pointset.PolyData, name: str = 'Depth [m]') → pyvista.core.pointset.PolyData#

Extracting the depth values of the vertices and add them as scalars to the mesh

Parameters

mesh (pv.core.pointset.PolyData) – PyVista PolyData dataset
name (str) – Name of the data array, e.g. name='Depth [m]', default is 'Depth [m]'

Returns

mesh – PyVista PolyData dataset with depth values as data array

Return type

pv.core.pointset.PolyData

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import pyvista as pv
>>> mesh = pv.read(filename='mesh.vtk')
>>> mesh
PolyData    Information
N Cells     4174
N Points    2303
X Bounds    9.720e+00, 9.623e+02
Y Bounds    1.881e+02, 9.491e+02
Z Bounds    3.050e+02, 7.250e+02
N Arrays    0

>>> # Creating depth map from surface
>>> mesh = gg.visualization.create_depth_map(mesh=mesh)
>>> mesh
Header
PolyData    Information
N Cells     4174
N Points    2303
X Bounds    9.720e+00, 9.623e+02
Y Bounds    1.881e+02, 9.491e+02
Z Bounds    3.050e+02, 7.250e+02
N Arrays    1
Data Arrays
Name        Field   Type    N Comp  Min         Max
Depth [m]   Points  float64 1       3.050e+02   7.250e+02

See also

create_depth_maps_from_gempy: Creating depth maps from GemPy Model Surfaces
create_thickness_maps: Creating thickness map from PolyData datasets
create_temperature_map: Creating temperature map from PolyData datasets

gemgis.visualization.create_depth_maps_from_gempy(geo_model, surfaces: Union[str, List[str]]) → Dict[str, List[Union[pyvista.core.pointset.PolyData, numpy.ndarray, List[str]]]]#

Creating depth map of model surfaces, adapted from https://github.com/cgre-aachen/gempy/blob/20550fffdd1ccb3c6a9a402bc162e7eed3dd7352/gempy/plot/vista.py#L440-L477

Parameters

geo_model (gp.core.model.Project) – Previously calculated GemPy Model
surfaces (Union[str, List[str]]) – Name of the surface or list with surface names of which the depth maps are created, e.g. surfaces=['Layer1', 'Layer2']

Returns

surfaces_poly – Dict containing the mesh data, depth data and color data for selected surfaces

Return type

Dict[str, List[Union[pv.core.pointset.PolyData, np.ndarray, List[str]]]]

New in version 1.0.x.

Changed in version 1.1.8: Ensure compatibility with GemPy>=3

Example

>>> # Loading Libraries and creating depth map
>>> import gemgis as gg
>>> dict_sand1 = gg.visualization.create_depth_maps(geo_model=geo_model, surfaces='Sand1')
>>> dict_sand1
{'Sand1':   [PolyData (0x2dd0f46c820)
N Cells:    4174
N Points:   2303
X Bounds:   9.720e+00, 9.623e+02
Y Bounds:   1.881e+02, 9.491e+02
Z Bounds:   3.050e+02, 7.250e+02
N Arrays:   1,
'#015482']}

See also

create_depth_map: Creating depth map from PolyData dataset
create_thickness_maps: Creating thickness map from PolyData datasets
create_temperature_map: Creating temperature map from PolyData datasets

gemgis.visualization.create_deviated_borehole_df(df_survey: pandas.core.frame.DataFrame, position: Union[numpy.ndarray, shapely.geometry.point.Point], depth: str = 'depth', dip: str = 'dip', azimuth: str = 'azimuth') → pandas.core.frame.DataFrame#

Creating Pandas DataFrame containing parameters to create 3D boreholes

Parameters

df_survey (pd.DataFrame) – Pandas DataFrame containing the survey data of one borehole
position (np.ndarray) – NumPy array containing the X, Y, and Z coordinates/the position of the borehole, e.g. position = np.array([12012.68053 , 30557.53476 , 2325.532416])
depth (str) – Name of the column that contains the depth values, e.g. depth='depth', default is 'depth'
dip (str) – Name of the column that contains the dip values, e.g. dip='dip', default is 'dip'
azimuth (str) – Name of the column that contains the azimuth values, e.g. azimuth='azimuth' default is 'azimuth'

Returns

df_survey – Pandas DataFrame containing parameters to create 3D boreholes

Return type

pd.DataFrame

New in version 1.0.x.

Changed in version 1.1.7.

Replace pandas append with concat.

Example

>>> # Loading Libraries and file
>>> import gemgis as gg
>>> import pandas as pd
>>> df_survey = pd.read_csv('survey.csv')
    holeid      depth   dip     azimuth
0   SonicS_006  0       90.00   20
1   SonicS_006  10      89.50   20
2   SonicS_006  20      89.00   20
3   SonicS_006  30      88.50   20
4   SonicS_006  40      88.00   20

>>> # Defining the position of the borehole at the surface
>>> position = np.array([12012.68053 , 30557.53476 ,  2325.532416])

>>> # Creating the survey DataFrame with additional parameters
>>> df_survey = gg.visualization.create_deviated_well_df(df_survey=df_survey,position=position)

gemgis.visualization.create_deviated_boreholes_3d(df_collar: pandas.core.frame.DataFrame, df_survey: pandas.core.frame.DataFrame, min_length: Union[float, int], radius: Union[float, int] = 10, collar_depth: str = 'Depth', survey_depth: str = 'Depth', index: str = 'Index', dip: str = 'dip', azimuth: str = 'azimuth') → Tuple[List[pyvista.core.pointset.PolyData], pyvista.core.pointset.PolyData, List[pandas.core.frame.DataFrame]]#

Plotting boreholes in 3D

Parameters

df_collar (pd.DataFrame) – DataFrame containing the extracted borehole data
df_survey (pd.DataFrame) – DataFrame containing the extracted borehole survey data
min_length (Union[float, int]) – Value defining the minimum depth of boreholes to be plotted, e.g. min_length=1000
color_dict (dict) – Dict containing the surface colors of the model
radius (Union[float, int]) – Values of the radius of the boreholes plotted with PyVista, e.g. radius=100, default is 10
collar_depth (str) – Name of the column that contains the depth values, e.g. collar_depth='depth', default is 'Depth'
survey_depth (str) – Name of the column that contains the depth values, e.g. survey_depth='depth', default is 'Depth'
index (str) – Name of the column that contains the index values, e.g. index='index', default is 'index'
dip (str) – Name of the column that contains the dip values, e.g. dip='dip', default is 'dip'
azimuth (str) – Name of the column that contains the azimuth values, e.g. azimuth='azimuth' default is 'azimuth'

Returns

tubes (List[pv.core.pointset.PolyData]) – List of PyVista tubes
labels (pv.core.pointset.PolyData) – PyVista PolyData with Borehole Labels
df_groups (List[pd.DataFrame]) – List containing DataFrames

New in version 1.0.x.

Example

gemgis.visualization.create_lines_3d_linestrings(gdf: geopandas.geodataframe.GeoDataFrame, dem: Union[rasterio.io.DatasetReader, numpy.ndarray], extent: List[Union[int, float]] = None) → geopandas.geodataframe.GeoDataFrame#

Creating lines with z-component (LineString Z)

Parameters

gdf (gpd.geodataframe.GeoDataFrame) – GeoDataFrame containing the LineStrings to be converted to linestrings with z-component
dem (Union[rasterio.io.DatasetReader, np.ndarray]) – Rasterio object or NumPy array containing the height values
extent (List[Union[int, float]]) – List containing the bounds of the raster, e.g. extent=[0, 972, 0, 1069]

Returns

gdf_3d – GeoDataFrame containing the LineStrings with Z component (LineString Z)

Return type

gpd.geodataframe.GeoDataFrame

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import geopandas as gpd
>>> import rasterio
>>> gdf = gpd.read_file(filename='file.shp')
>>> gdf
id      formation   geometry
0   None    Unterjura   LINESTRING (32522415.430 5777985.396, 32521520...
1   None    Unterjura   LINESTRING (32479802.616 5782183.163, 32480593...
2   None    Mitteljura  LINESTRING (32522376.263 5779907.729, 32520580...
3   None    Mitteljura  LINESTRING (32463272.196 5788327.350, 32464107...

>>> # Loading Digital Elevation Model
>>> dem = rasterio.open('raster.tif')

>>> # Create LineStrings with Z-component
>>> gdf_3d = gg.visualization.create_lines_3d_linestrings(gdf=gdf, dem=dem)
>>> gdf_3d
    id      formation   geometry
0   None    Unterjura   LINESTRING Z (32522415.430 5777985.396 213.000...
1   None    Unterjura   LINESTRING Z (32479802.616 5782183.163 84.000,...
2   None    Mitteljura  LINESTRING Z (32522376.263 5779907.729 116.000...
3   None    Mitteljura  LINESTRING Z (32463272.196 5788327.350 102.000...

See also

create_lines_3d_polydata: Creating lines with z-component for the plotting with PyVista
create_dem_3d: Creating a mesh from a Digital Elevation Model
create_points_3d: Creating a mesh from points

gemgis.visualization.create_lines_3d_polydata(gdf: geopandas.geodataframe.GeoDataFrame) → pyvista.core.pointset.PolyData#

Creating lines with z-component for the plotting with PyVista

Parameters: gdf (gpd.geodataframe.GeoDataFrame) – GeoDataFrame containing the contour information
Returns: poly – PyVista Polydata Set containing the lines and vertices
Return type: pyvista.core.pointset.PolyData

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import geopandas as gpd
>>> gdf = gpd.read_file(filename='file.shp')
>>> gdf
    id      Z   geometry
0   None    400 LINESTRING (0.741 475.441, 35.629 429.247, 77....
1   None    300 LINESTRING (645.965 0.525, 685.141 61.866, 724...
2   None    400 LINESTRING (490.292 0.525, 505.756 40.732, 519...
3   None    600 LINESTRING (911.433 1068.585, 908.856 1026.831...
4   None    700 LINESTRING (228.432 1068.585, 239.772 1017.037...

>>> # Create mesh from LineStrings
>>> polydata = gg.visualization.create_lines_3d_polydata(gdf=gdf)
>>> polydata
    PolyData    Information
N   Cells       7
N   Points      121
X   Bounds      7.409e-01, 9.717e+02
Y   Bounds      5.250e-01, 1.069e+03
Z   Bounds      3.000e+02, 7.000e+02
N   Arrays      0

See also

create_dem_3d: Creating a mesh from a Digital Elevation Model
create_points_3d: Creating a mesh from points

gemgis.visualization.create_lines_from_points(df: pandas.core.frame.DataFrame) → pyvista.core.pointset.PolyData#

Creating a line set from a Pandas DataFrame

Parameters: df (pd.DataFrame) – Pandas DataFrame containing the data for one borehole
Returns: poly – Creating borehole traces from points
Return type: pv.core.pointset.PolyData

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import pandas as pd
>>> df = pd.read_csv('file.csv')
>>> df
    Unnamed: 0  Index   Name                            X           Y           Z       Altitude    Depth   formation       geometry
0   2091        GD1017  ForschungsbohrungMünsterland1   32386176.36 5763283.15  27.00   107.00      5956.00 OberCampanium   POINT (32386176.36 5763283.15)
1   2092        GD1017  ForschungsbohrungMünsterland1   32386176.36 5763283.15  -193.00 107.00      5956.00 UnterCampanium  POINT (32386176.36 5763283.15)

>>> # Adding row to DataFrames
>>> grouped = df.groupby(['Index'])
>>> df_groups = [grouped.get_group(x) for x in grouped.groups]
>>> list_df = gg.visualization.add_row_to_boreholes(df_groups)
>>> list_df[0]
    Unnamed: 0  Index   Name                            X           Y           Z       Altitude    Depth   formation       geometry
0   NaN         GD1017  ForschungsbohrungMünsterland1   32386176.36 5763283.15  27.00   107.00      5956.00                 NaN
0   2091        GD1017  ForschungsbohrungMünsterland1   32386176.36 5763283.15  27.00   107.00      5956.00 OberCampanium   POINT (32386176.36 5763283.15)
1   2092        GD1017  ForschungsbohrungMünsterland1   32386176.36 5763283.15  -193.00 107.00      5956.00 UnterCampanium  POINT (32386176.36 5763283.15)

>>> # Creating Lines from points
>>> line = gg.visualization.create_lines_from_points(df=list_df[0])
>>> line
PolyData    Information
N Cells     39
N Points    20
X Bounds    3.239e+07, 3.239e+07
Y Bounds    5.763e+06, 5.763e+06
Z Bounds    -5.849e+03, 1.070e+02
N Arrays    0

See also

add_row_to_boreholes: Adding a row to each borehole for later processing
create_borehole_tube: Creating borehole tube
create_borehole_tubes: Creating tubes from lines
create_borehole_labels: Creating labels for boreholes
create_boreholes_3d: Creating PyVista objects for plotting

gemgis.visualization.create_mesh_from_cross_section(linestring: shapely.geometry.linestring.LineString, zmax: Union[float, int], zmin: Union[float, int]) → pyvista.core.pointset.PolyData#

Creating a PyVista Mesh from one cross section

Parameters

linestring (shapely.geometry.linestring.LineString) – LineString representing the trace of the cross section on a geological map, e.g. linestring = LineString([(0, 0), (10, 10), (20, 20)])
zmax (Union[float, int]) – Upper vertical extent of the cross section, e.g. zmax=1000
zmin (Union[float, int]) – Lower vertical extent of the cross section, e.g. zmin=0

Returns

surface – Mesh defining the cross section in space

Return type

pyvista.core.pointset.PolyData

New in version 1.0.x.

Example

>>> # Loading Libraries and creating LineString
>>> import gemgis as gg
>>> from shapely.geometry import LineString
>>> linestring = LineString([(0, 0), (10, 10), (20, 20)])
>>> linestring.wkt
'LINESTRING (0 0, 10 10, 20 20)'

>>> # Creating PolyData from LineStrings
>>> polydata = gg.visualization.create_mesh_from_cross_section(linestring=linestring, zmax=1000, zmin=0)
>>> polydata
Header
PolyData    Information
N Cells     4
N Points    6
X Bounds    0.000e+00, 2.000e+01
Y Bounds    0.000e+00, 2.000e+01
Z Bounds    0.000e+00, 1.000e+03
N Arrays    1
Data Arrays
Name                Field   Type    N Comp  Min         Max
Texture Coordinates Points  float64 2       0.000e+00   1.000e+00

See also

create_meshes_from_cross_sections: Creating meshes from cross sections

gemgis.visualization.create_meshes_from_cross_sections(gdf: geopandas.geodataframe.GeoDataFrame) → List[pyvista.core.pointset.PolyData]#

Creating PyVista Meshes from multiple cross section

Parameters: gdf (gpd.geodataframe.GeoDataFrame) – GeoDataFrame containing the traces of the profiles as LineStrings
Returns: meshes_list – List containing the meshes of all profiles
Return type: List[pyvista.core.pointset.PolyData]

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import geopandas as gpd
>>> gdf = gpd.read_file(filename='file.shp')
>>> gdf
    id      zmax    zmin    name        geometry
0   None    500     -6000   Muenster    LINESTRING (32386148.890 5763304.720, 32393549...
1   None    500     -2000   Rheine      LINESTRING (32402275.136 5761828.501, 32431165...

>>> # Creating list of PolyData datasets from GeoDataFrame
>>> meshes_list = gg.visualization.create_meshes_from_cross_sections(gdf=gdf)
>>> meshes_list
[PolyData (0x2526e543ee0)
N Cells:     20
N Points:    22
X Bounds:    3.239e+07, 3.242e+07
Y Bounds:    5.717e+06, 5.763e+06
Z Bounds:    -6.000e+03, 5.000e+02
N Arrays:    1,
PolyData (0x2526a4687c0)
N Cells:     2
N Points:    4
X Bounds:    3.240e+07, 3.243e+07
Y Bounds:    5.762e+06, 5.814e+06
Z Bounds:    -2.000e+03, 5.000e+02
N Arrays:    1]

See also

create_mesh_from_cross_section: Creating a mesh from a cross section

gemgis.visualization.create_meshes_hypocenters(gdf: geopandas.geodataframe.GeoDataFrame, magnitude: str = 'Magnitude', magnitude_factor: int = 200, year: str = 'Year') → pyvista.core.composite.MultiBlock#

Plotting earthquake hypocenters with PyVista

Parameters

gdf (gpd.geodataframe.GeoDataFrame) – GeoDataFrame containing the earthquake hypocenter data
magnitude (str) – Name for the column containing the magnitude value, e.g. magnitude='Magnitude', default is 'Magnitude'
magnitude_factor (int) – Scaling factor for the magnitude values defining the size of the spheres, e.g. magnitude_factor=200, default is 200
year (str) – Name for the column containing the year of each earthquake event, e.g. year='Year', default to 'Year'

Returns

spheres – PyVista MultiBlock object containing the hypocenters stored as spheres

Return type

pv.core.composite.MultiBlock

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import geopandas as gpd
>>> gdf = gpd.read_file(filename='file.shp')
>>> gdf
    Y           X           Z           RASTERVALU  Tiefe [km]  Magnitude   Epizentrum      Year    geometry
0   5645741.63  32322660.15 -8249.25    150.75      8.40        1.50        STETTERNICH     2002    POINT (32322660.151 5645741.630)
1   5645947.18  32323159.51 89.63       89.63       0.00        0.80        SOPHIENHOEHE    2014    POINT (32323159.505 5645947.183)

>>> # Creating Spheres for hypocenters
>>> spheres = gg.visualization.create_meshes_hypocenters(gdf=gdf)
>>> spheres
Information
MultiBlock  Values
N Blocks    497
X Bounds    32287780.000, 32328260.000
Y Bounds    5620074.000, 5648385.000
Z Bounds    -24317.020, 309.130
Blocks
Index   Name        Type
0       Block-00    PolyData
1       Block-01    PolyData
2       Block-02    PolyData

gemgis.visualization.create_points_3d(gdf: geopandas.geodataframe.GeoDataFrame) → pyvista.core.pointset.PolyData#

Plotting points in 3D with PyVista

Parameters: points (gpd.geodataframe.GeoDataFrame) – GeoDataFrame containing the points including X, Y, and Z columns
Returns: points_mesh – PyVista PolyData Pointset
Return type: pyvista.core.pointset.PolyData

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import geopandas as gpd
>>> gdf = gpd.read_file(filename='file.shp')
>>> gdf
    id      formation   geometry
0   None    Ton         POINT (19.150 293.313)
1   None    Ton         POINT (61.934 381.459)
2   None    Ton         POINT (109.358 480.946)
3   None    Ton         POINT (157.812 615.999)
4   None    Ton         POINT (191.318 719.094)

>>> # Creating PolyData from points
>>> polydata = gg.visualization.create_points_3d(gdf=gdf)
>>> polydata
    PolyData    Information
N Cells     41
N Points        41
X Bounds        8.841e+00, 9.661e+02
Y Bounds        1.650e+02, 1.045e+03
Z Bounds        2.769e+02, 7.220e+02
N Arrays        0

See also

create_lines_3d_polydata: Creating a mesh from lines
create_dem_3d: Creating a mesh from a Digital Elevation model

gemgis.visualization.create_polydata_from_dxf(gdf: geopandas.geodataframe.GeoDataFrame) → pyvista.core.pointset.PolyData#

Converting loaded DXF object to PyVista PolyData

Parameters: gdf (gpd.geodataframe.GeoDataFrame) – GeoDataFrame containing the faces/polygons of the loaded DXF object
Returns: polydata – PyVista PolyData containing the mesh values
Return type: pyvista.core.pointset.PolyData

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import geopandas as gpd
>>> gdf = gpd.read_file(filename='file.dxf')
>>> gdf
    geometry
0   POLYGON Z ((1.00869 0.92852 1.00000, 0.97744 0...
1   POLYGON Z ((1.00869 0.92852 1.00000, 1.01735 0...
2   POLYGON Z ((0.97744 0.92853 1.00000, 0.94619 0...
3   POLYGON Z ((0.97744 0.92853 1.00000, 0.98610 0...
4   POLYGON Z ((0.94619 0.92853 1.00000, 0.91494 0...

>>> # Creating PolyData from dxf file
>>> polydata = gg.visualization.create_polydata_from_dxf(gdf=gdf)
>>> polydata
PolyData    Information
N Cells     98304
N Points    393216
X Bounds    -1.576e+00, 2.530e+00
Y Bounds    -9.751e+00, 1.000e+00
Z Bounds    -9.167e-01, 1.000e+00
N Arrays        0

See also

create_polydata_from_msh: Creating PolyData dataset from Leapfrog mesh file
create_polydata_from_ts: Creating PolyData dataset from GoCAD Tsurface file
create_structured_grid_from_asc: Creating StructuredGrid vom ESRI ASC Grid
create_structured_grid_from_zmap: Creating StructuredGrid vom Petrel ZMAP Grid
create_delaunay_mesh_from_gdf: Create Mesh from GeoDataFrame containing contour lines

gemgis.visualization.create_polydata_from_msh(data: Dict[str, numpy.ndarray]) → pyvista.core.pointset.PolyData#

Converting loaded Leapfrog mesh to PyVista PolyData

Parameters: data (Dict[str, np.ndarray]) – Dict containing the data loaded from a Leapfrog mesh with read_msh() of the raster module
Returns: polydata – PyVista PolyData containing the mesh values
Return type: pyvista.core.pointset.PolyData

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> data = gg.raster.read_msh('mesh.msh')
>>> data
{'Tri': array([[    0,     1,     2],
[    0,     3,     1],
[    4,     3,     0],
...,
[53677, 53672, 53680],
[53679, 53677, 53680],
[53673, 53672, 53677]]),
'Location': array([[ 1.44625109e+06,  5.24854344e+06, -1.12743862e+02],
[ 1.44624766e+06,  5.24854640e+06, -1.15102216e+02],
[ 1.44624808e+06,  5.24854657e+06, -1.15080548e+02],
...,
[ 1.44831008e+06,  5.24896679e+06, -1.24755449e+02],
[ 1.44830385e+06,  5.24896985e+06, -1.33694397e+02],
[ 1.44829874e+06,  5.24897215e+06, -1.42506587e+02]])}

>>> # Creating PolyData from msh file
>>> polydata = gg.visualization.create_polydata_from_msh(data=data)
>>> polydata
PolyData    Information
N Cells     107358
N Points    53681
X Bounds    1.444e+06, 1.449e+06
Y Bounds    5.246e+06, 5.249e+06
Z Bounds    -2.464e+02, 7.396e+02
N Arrays    0

See also

create_polydata_from_ts: Creating PolyData dataset from GoCAD Tsurface file
create_polydata_from_dxf: Creating PolyData dataset from DXF object
create_structured_grid_from_asc: Creating StructuredGrid vom ESRI ASC Grid
create_structured_grid_from_zmap: Creating StructuredGrid vom Petrel ZMAP Grid
create_delaunay_mesh_from_gdf: Create Mesh from GeoDataFrame containing contour lines

gemgis.visualization.create_polydata_from_ts(data: Tuple[list, list], concat: bool = False) → pyvista.core.pointset.PolyData#

Converting loaded GoCAD mesh to PyVista PolyData

Parameters

data (Tuple[list, list]) – Tuple containing the data loaded from a GoCAD mesh with read_ts() of the raster module
concat (bool) – Boolean defining whether the DataFrames should be concatenated or not

Returns

polydata – PyVista PolyData containing the mesh values

Return type

pyvista.core.pointset.PolyData

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> vertices, faces = gg.raster.read_ts('mesh.ts')

>>> # Inspecting vertices
>>> vertices
    id  X           Y           Z
0   0   297077.41   5677487.26  -838.50
1   1   297437.54   5676992.09  -816.61

>>> # Inspecting
>>> faces
array([[    0,     1,     2],
[    3,     2,     4],
[    1,     5,     6],...,
[40335, 40338, 40336],
[40339, 40340, 40341],
[40341, 40342, 40339]])

>>> # Creating PolyData from ts file
>>> polydata = gg.visualization.create_polydata_from_ts((vertices, faces))
>>> polydata
PolyData    Information
N Cells     29273
N Points    40343
X Bounds    2.804e+05, 5.161e+05
Y Bounds    5.640e+06, 5.833e+06
Z Bounds    -8.067e+03, 1.457e+02
N Arrays    0

See also

create_polydata_from_msh: Creating PolyData dataset from Leapfrog mesh file
create_polydata_from_dxf: Creating PolyData dataset from DXF object
create_structured_grid_from_asc: Creating StructuredGrid vom ESRI ASC Grid
create_structured_grid_from_zmap: Creating StructuredGrid vom Petrel ZMAP Grid
create_delaunay_mesh_from_gdf: Create Mesh from GeoDataFrame containing contour lines

gemgis.visualization.create_structured_grid_from_asc(data: dict) → pyvista.core.pointset.StructuredGrid#

Converting loaded ASC object to PyVista StructuredGrid

Parameters: data (dict) – Dict containing the extracted ASC data using read_asc(…) of the raster module
Returns: grid – PyVista StructuredGrid created from ASC data
Return type: pv.core.pointset.StructuredGrid

New in version 1.0.x.

Example

>>> # Loading Libraries and data
>>> import gemgis as gg
>>> data = gg.raster.read_asc('raster.asc')

>>> # Creating StructuredGrid from data
>>> grid = gg.visualization.create_structured_grid_from_asc(data=data)
>>> grid
Header  Data Arrays
StructuredGrid  Information
N Cells         2880012
N Points        2883540
X Bounds        -4.225e+04, 2.788e+05
Y Bounds        3.060e+05, 8.668e+05
Z Bounds        -1.000e+05, 2.880e+02
Dimensions      2244, 1285, 1
N Arrays        1
Name        Field   Type    N Comp  Min         Max
Depth [m]   Points  float64 1       -1.132e+04  2.887e+02

See also

create_polydata_from_msh: Creating PolyData dataset from Leapfrog mesh file
create_polydata_from_ts: Creating PolyData dataset from GoCAD Tsurface file
create_polydata_from_dxf: Creating PolyData dataset from DXF object
create_structured_grid_from_zmap: Creating StructuredGrid vom Petrel ZMAP Grid
create_delaunay_mesh_from_gdf: Create Mesh from GeoDataFrame containing contour lines

gemgis.visualization.create_structured_grid_from_zmap(data: dict) → pyvista.core.pointset.StructuredGrid#

Converting loaded ZMAP object to PyVista StructuredGrid

Parameters: data (dict) – Dict containing the extracted ZAMP data using read_zmap(…) of the raster module
Returns: grid – PyVista StructuredGrid created from zmap data
Return type: pv.core.pointset.StructuredGrid

New in version 1.0.x.

Example

>>> # Loading Libraries and data
>>> import gemgis as gg
>>> data = gg.raster.read_zmap('raster.dat')

>>> # Creating StructuredGrid from data
>>> grid = gg.visualization.create_structured_grid_from_zmap(data=data)
>>> grid
Header  Data Arrays
StructuredGrid  Information
N Cells         2880012
N Points        2883540
X Bounds        -4.225e+04, 2.788e+05
Y Bounds        3.060e+05, 8.668e+05
Z Bounds        -1.000e+05, 2.880e+02
Dimensions      2244, 1285, 1
N Arrays        1
Name        Field   Type    N Comp  Min         Max
Depth [m]   Points  float64 1       -1.132e+04  2.887e+02

See also

create_polydata_from_msh: Creating PolyData dataset from Leapfrog mesh file
create_polydata_from_ts: Creating PolyData dataset from GoCAD Tsurface file
create_polydata_from_dxf: Creating PolyData dataset from DXF object
create_structured_grid_from_asc: Creating StructuredGrid vom ESRI ASC Grid
create_delaunay_mesh_from_gdf: Create Mesh from GeoDataFrame containing contour lines

gemgis.visualization.create_temperature_map(dem: rasterio.io.DatasetReader, mesh: pyvista.core.pointset.PolyData, name: str = 'Thickness [m]', apply_threshold: bool = True, tsurface: Union[float, int] = 10, gradient: Union[float, int] = 0.03) → pyvista.core.pointset.PolyData#

Creating a temperature map for a surface at depth taking the topography into account

Parameters

dem (rasterio.io.DatasetReader) – Digital Elevation Model of the area
mesh (pv.core.pointset.PolyData) – PolyData dataset for which the temperature at depth will be calculated
name (str) – Name of the array to be added to the mesh, e.g. name='Thickness [m]', default is 'Thickness [m]'
apply_threshold (bool) – Variable to apply a threshold to the mesh to remove vertices that were located above the topography. Options include: True or False, default set to True
tsurface (Union[float, int]) – Surface temperature in degrees Celsius, e.g. tsurface=10, default is 10 degrees C
gradient (Union[float, int]) – Geothermal gradient in degrees celsius per meter, e.g. gradient=0.03, default is 0.03 degrees C per m

Returns

mesh – PolyData dataset including a temperature data array

Return type

pv.core.pointset.PolyData

New in version 1.0.x.

Example

>>> # Loading Libraries and Files
>>> import gemgis as gg
>>> import rasterio
>>> import pyvista as pv
>>> dem = rasterio.open(fp='raster.tif')
>>> mesh = pv.read(filename='mesh1.vtk')
>>> mesh
PolyData    Information
N Cells     4174
N Points    2303
X Bounds    9.720e+00, 9.623e+02
Y Bounds    1.881e+02, 9.491e+02
Z Bounds    3.050e+02, 7.250e+02
N Arrays    0

>>> # Creating temperature map
>>> mesh = gg.visualization.create_temperature_map(dem=dem, mesh=mesh)
>>> mesh
Header
UnstructuredGrid    Information
N Cells     3946
N Points    2130
X Bounds    9.720e+00, 9.623e+02
Y Bounds    1.881e+02, 9.491e+02
Z Bounds    3.050e+02, 7.250e+02
N Arrays    2
Data Arrays
Name                Field   Type    N Comp  Min         Max
Thickness [m]       Points  float64 1       9.321e-02   2.020e+02
Temperature [°C]    Points  float64 1       1.000e+01   1.606e+01

See also

create_depth_map: Creating depth map from PolyData dataset
create_depth_maps_from_gempy: Creating depth maps from GemPy Model Surfaces
create_thickness_maps: Creating thickness map from PolyData datasets

gemgis.visualization.create_thickness_maps(top_surface: pyvista.core.pointset.PolyData, base_surface: pyvista.core.pointset.PolyData) → pyvista.core.pointset.PolyData#

Creating a thickness map using https://docs.pyvista.org/examples/01-filter/distance-between-surfaces.html#sphx-glr-examples-01-filter-distance-between-surfaces-py

Parameters

top_surface (pv.core.pointset.PolyData) – Mesh representing the top of the layer
base_surface (pv.core.pointset.PolyData) – Mesh representing the base of the layer

Returns

thickness – Mesh with scalars representing the thickness of the layer

Return type

pv.core.pointset.PolyData

New in version 1.0.x.

Example

>>> # Loading Libraries and creating thickness map
>>> import gemgis as gg
>>> dict_all = gg.visualization.create_depth_maps_from_gempy(geo_model=geo_model, surfaces=['Sand1', 'Ton'])
>>> thickness_map = gg.visualization.create_thickness_maps(top_surface=dict_all['Sand1'][0], base_surface=dict_all['Ton'][0])
>>> thickness_map
Header
PolyData    Information
N Cells     5111
N Points    2739
X Bounds    9.720e+00, 9.623e+02
Y Bounds    3.578e+02, 1.058e+03
Z Bounds    3.050e+02, 7.265e+02
N Arrays    3
Data Arrays
Name            Field   Type    N Comp  Min             Max
Data            Points  float64 1       3.050e+02   7.265e+02
Normals         Points  float32 3       -9.550e-01  6.656e-01
Thickness [m]   Points  float64 1       4.850e+01   8.761e+01

See also

create_depth_map: Creating depth map from PolyData dataset
create_depth_maps_from_gempy: Creating depth maps from GemPy Model Surfaces
create_temperature_map: Creating temperature map from PolyData datasets

gemgis.visualization.drape_array_over_dem(array: numpy.ndarray, dem: Union[rasterio.io.DatasetReader, numpy.ndarray], extent: List[Union[int, float]] = None, zmax: Union[float, int] = 10000, resize_array: bool = True)#

Creating grid and texture to drape array over a digital elevation model

Parameters

array (np.ndarray) – Array containing the map data such as a WMS Map
dem (Union[rasterio.io.DatasetReader, np.ndarray]) – Digital elevation model where the array data is being draped over
extent (List[Union[float, int]]) – List containing the bounds of the raster, e.g. extent=[0, 972, 0, 1069]
zmax (Union[float, int]) – Maximum z value to limit the elevation data, e.g. zmax=1000
resize_array (bool) – Whether to resize the array or the dem if the shape of the dem does not match the shape of the array Options include: True or False, default set to True

Returns

mesh (pyvista.core.pointset.PolyData) – Mesh containing the Digital elevation model data
texture (pyvista.core.objects.Texture) – PyVista Texture containing the map data

New in version 1.0.x.

Changed in version 1.1: Function now allows rasters with different sizes and resizes one of the rasters automatically

Changed in version 1.1.2: Edit zmax value and fixing a bug with the scikit-image resize function, see https://github.com/cgre-aachen/gemgis/issues/303

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> array
array([[[ 93,  93, 126],
[104, 104, 133],
[227, 227, 234],
...,
[152, 178, 204],
[160, 188, 201],
[206, 200, 181]],
[[247, 246, 248],
[241, 240, 246],
[243, 241, 241],
...,
[150, 177, 205],
[175, 187, 177],
[232, 228, 219]]], dtype=uint8)

>>> # Inspecting Digital Elevation Model values
>>> dem
array([[  0.  ,   0.  ,   0.  , ...,  40.1 ,  40.09,  44.58],
[  0.  ,   0.  ,   0.  , ...,  40.08,  40.07,  44.21],
[  0.  ,   0.  ,   0.  , ...,  40.14,  44.21,  43.98],
...,
[100.56, 102.14, 102.17, ...,   0.  ,   0.  ,   0.  ],
[ 99.44,  99.85,  99.77, ...,   0.  ,   0.  ,   0.  ],
[ 88.32,  91.76,  98.68, ...,   0.  ,   0.  ,   0.  ]],
dtype=float32)

>>> # Draping mesh over array
>>> mesh, texture = gg.visualization.drape_array_over_dem(array=array, dem=dem)
>>> mesh
Header
StructuredGrid  Information
N Cells         5595201
N Points        5600000
X Bounds        3.236e+07, 3.250e+07
Y Bounds        5.700e+06, 5.800e+06
Z Bounds        0.000e+00, 5.038e+02
Dimensions      2000, 2800, 1
N Arrays        1
Data Arrays
Name                Field   Type    N Comp  Min         Max
Texture Coordinates Points  float32 2       -7.077e-06  1.000e+00

>>> # Inspecting the texture
>>> texture
(Texture)00000151B91F3AC0

See also

read_raster: Reading Digital Elevation Model as xarray
convert_to_rgb: Converting bands to RGB values for plotting

gemgis.visualization.get_batlow_cmap() → matplotlib.colors.ListedColormap#

Returning the Batlow cmap from https://github.com/callumrollo/cmcrameri/blob/master/cmcrameri/cmaps/batlow.txt

Returns: cmap_batlow – Batlow color map
Return type: matplotlib.colors.ListedColormap

New in version 1.0.x.

gemgis.visualization.get_color_lot(geo_model, lith_c: pandas.core.frame.DataFrame = None, index='surface', is_faults: bool = True, is_basement: bool = False) → pandas.core.series.Series#

Method to get the right color list depending on the type of plot.: Borrowed from https://github.com/cgre-aachen/gempy/blob/6aed72a4dfa26830df142a0461294bd9d21a4fa4/gempy/plot/vista.py#L133-L167

Parameters

geo_model (gp.core.model.Project) – Previously calculated GemPy Model
lith_c (pd.DataFrame) – Pandas Series with index surface names and values hex strings with the colors
index (str) – Index provided as string, e.g. index='surface', default is 'surface'
is_faults (bool) – Return the colors of the faults. This should be true for surfaces and input data and false for scalar values. Options include True and False, default is True
is_basement (bool) – Return or not the basement. This should be true for the lith block and false for surfaces and input data. Options include True and False, default is False

New in version 1.0.x.

gemgis.visualization.get_mesh_geological_map(geo_model) → Tuple[pyvista.core.pointset.PolyData, matplotlib.colors.ListedColormap, bool]#

Getting the geological map of a GemPy Model draped over the topography as mesh. Borrowed from https://github.com/cgre-aachen/gempy/blob/6aed72a4dfa26830df142a0461294bd9d21a4fa4/gempy/plot/vista.py#L512-L604

Parameters

geo_model (gp.core.model.Project) – Previously calculated GemPy Model

Returns

polydata (pv.core.PolyData) – PyVista Mesh containing the geological map draped over the topography
cm (matplotlib.colors.ListedColormap) – Colormap for plotting
rgb (bool) – Boolean to use rgb=True when plotting

New in version 1.0.x.

gemgis.visualization.get_petrel_cmap() → matplotlib.colors.ListedColormap#

Returning the Petrel cmap

Returns: cmap_seismic – Seismic color map
Return type: matplotlib.colors.ListedColormap

New in version 1.0.x.

gemgis.visualization.get_points_along_spline(spline: pyvista.core.pointset.PolyData, dist: numpy.ndarray)#

Returning the closest point on the spline a given a length along a spline.

Parameters

spline (pv.core.pointset.PolyData) – Spline with the resampled vertices
dist (np.ndarray) – np.ndarray containing the measured depths (MD) of values along the well path

Returns

spline.points[idx_list] – PyVista Array containing the selected points

Return type

pv.core.pyvista_ndarray.pyvista_ndarray

New in version 1.0.x.

gemgis.visualization.get_seismic_cmap() → matplotlib.colors.ListedColormap#

Returning the seismic cmap from https://github.com/lperozzi/Seismic_colormaps/blob/master/colormaps.py

Returns: cmap_seismic – Seismic color map
Return type: matplotlib.colors.ListedColormap

New in version 1.0.x.

gemgis.visualization.group_borehole_dataframe(df: pandas.core.frame.DataFrame) → List[pandas.core.frame.DataFrame]#

Grouping Borehole DataFrame by Index

Parameters: df (pd.DataFrame) – Pandas DataFrame containing the borehole data
Returns: df_groups
Return type: List[pd.DataFrame]

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import pandas as pd
>>> df = pd.read_csv('file.csv')

>>> # Creating groups
>>> df_groups = gg.visualization.group_borehole_dataframe(df=df)

gemgis.visualization.plane_through_hypocenters(spheres: pyvista.core.composite.MultiBlock) → pyvista.core.pointset.PolyData#

Fitting a plane through the hypocenters of earthquakes using Eigenvector analysis

Parameters: spheres (pv.core.composite.MultiBlock) – PyVista MultiBlock object containing the hypocenters stored as spheres
Returns: plane – Plane fitting through the hypocenters using Eigenvector analysis
Return type: pv.core.pointset.PolyData

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import pyvista as pv
>>> spheres = pv.read(filename='spheres.vtk')

>>> # Fitting plane through spheres
>>> plane = gg.visualization.plane_through_hypocenters(spheres=spheres)
>>> plane
Header
PolyData    Information
N Cells     100
N Points    121
X Bounds    3.230e+07, 3.231e+07
Y Bounds    5.618e+06, 5.620e+06
Z Bounds    -1.113e+04, -8.471e+03
N Arrays    2
Data Arrays
Name                Field   Type    N Comp  Min         Max
Normals             Points  float32 3       0.000e+00   1.000e+00
TextureCoordinates  Points  float32 2       0.000e+00   1.000e+00

gemgis.visualization.plot_data(geo_data, show_basemap: bool = False, show_geolmap: bool = False, show_topo: bool = False, show_interfaces: bool = False, show_orientations: bool = False, show_customsections: bool = False, show_wms: bool = False, show_legend: bool = True, show_hillshades: bool = False, show_slope: bool = False, show_aspect: bool = False, show_contours: bool = False, add_to_extent: float = 0, hide_topo_left: bool = False, **kwargs)#

Plotting Input Data

Parameters

geo_data – GemPy Geo Data Class containing the raw data
show_basemap (bool) – Showing the basemap. Options include True and False, default is False
show_geolmap (bool) – Showing the geological map. Options include True and False, default is False
show_topo (bool) – Showing the topography/digital elevation model. Options include True and False, default is False
show_interfaces (bool) – Showing the interfaces. Options include True and False, default is False
show_orientations (bool) – Showing orientations. Options include True and False, default is False
show_customsections (bool) – Showing custom sections. Options include True and False, default is False
show_wms (bool) – Showing a WMS layer. Options include True and False, default is False
show_legend (bool) – Showing the legend of interfaces. Options include True and False, default is False
show_hillshades (bool) – Showing hillshades. Options include True and False, default is False
show_slope (bool) – Showing the slope of the DEM. Options include True and False, default is False
show_aspect (bool) – Showing the aspect of the DEM. Options include True and False, default is False
show_contours (bool) – Showing the contours of the DEM
add_to_extent (float) – Number of meters to add to the extent of the plot in each direction, e.g. add_to_extent=10, default is 0
hide_topo_left (bool) – If set to True, the topography will not be shown in the left plot. Options include True and False, default is False
cmap_basemap (str) – Cmap for basemap
cmap_geolmap (str) – Cmap for geological map
cmap_topo (str) – Cmap for topography
cmap_hillshades (str) – Cmap for hillshades
cmap_slope (str) – Cmap for slope
cmap_aspect (str) – Cmap for aspect
cmap_interfaces (str) – Cmap for interfaces
cmap_orientations (str) – Cmap for orientations
cmap_wms (str) – Cmap for WMS Service
cmap_contours (str) – Cmap for contour lines

New in version 1.0.x.

gemgis.visualization.plot_orientations(gdf: Union[geopandas.geodataframe.GeoDataFrame, pandas.core.frame.DataFrame], show_planes: bool = True, show_density_contours: bool = True, show_density_contourf: bool = False, formation: str = None, method: str = 'exponential_kamb', sigma: Union[float, int] = 1, cmap: str = 'Blues_r')#

Plotting orientation values of a GeoDataFrame with mplstereonet

Parameters

gdf (Union[gpd.geodataframe.GeoDataFrame, pd.DataFrame]) – (Geo-)DataFrame containing columns with orientations values
show_planes (bool) – Variable to show planes of orientation values. Options include: True or False, default set to True
show_density_contours (bool) – Variable to display density contours. Options include: True or False, default set to True
show_density_contourf (bool) – Variable to display density contourf. Options include: True or False, default set to False
formation (str) – Name of the formation for which the contourf plot is shown, e.g. formation='Layer1', default is None
method (str) – Method to estimate the orientation density distribution, method='exponential_kamb', default is 'exponential_kamb'
sigma (Union[float, int]) – Expected count in standard deviations, e.g. sigma=1, default is 1
cmap (str) – Name of the colormap for plotting the orientation densities, e.g. cmap='Blues_r', default is 'Blues_r'

New in version 1.0.x.

Example

>>> # Loading Libraries and File
>>> import gemgis as gg
>>> import geopandas as gpd
>>> gdf = gpd.read_file(filename='file.shp')
>>> gdf
    id      formation   dip     azimuth geometry
0   None    Sand        25.00   310     POINT (49.249 1033.893)
1   None    Sand        30.00   315     POINT (355.212 947.557)
2   None    Sand        15.00   330     POINT (720.248 880.912)
3   None    Clay        10.00   135     POINT (526.370 611.300)
4   None    Clay        25.00   140     POINT (497.591 876.368)
5   None    Clay        35.00   50      POINT (394.593 481.039)

>>> # Creating plot
>>> gg.visualization.plot_orientations(gdf=gdf, show_planes=True, show_density_contours=False, show_density_contourf=False)

gemgis.visualization.polyline_from_points(points: numpy.ndarray) → pyvista.core.pointset.PolyData#

Creating PyVista PolyLine from points

Parameters: points (np.ndarray) – Points defining the PolyLine
Returns: poly
Return type: pv.core.pointset.PolyData

New in version 1.0.x.

gemgis.visualization.read_raster(path=<class 'str'>, nodata_val: typing.Union[float, int] = None, name: str = 'Elevation [m]') → pyvista.core.pointset.PolyData#

Reading a raster and returning a mesh

Parameters

path (str) – Path to the raster, e.g. path='raster.tif'
nodata_val (Union[float, int]) – Nodata value of the raster, e.g. nodata_val=9999.0
name (str) – Name of the data array, e.g. name='Elevation [m], default is 'Elevation [m]'

Returns

mesh – PyVista mesh containing the raster values

Return type

pyvista.core.pointset.PolyData

New in version 1.0.x.

Changed in version 1.1.1: Set nodata value manually if no data value is provided and raster does not contain nodata values

Example

>>> # Loading Libraries and outputting mesh
>>> import gemgis as gg
>>> polydata = gg.visualization.read_raster(path='raster.tif', nodata_val=9999.0, name='Elevation [m]')
>>> polydata
Header
StructuredGrid  Information
N Cells         5595201
N Points        5600000
X Bounds        3.236e+07, 3.250e+07
Y Bounds        5.700e+06, 5.800e+06
Z Bounds        0.000e+00, 0.000e+00
Dimensions      2000, 2800, 1
N Arrays        1
Data Arrays
Name            Field   Type    N Comp  Min         Max
Elevation [m]   Points  float32 1       0.000e+00   5.038e+02

See also

convert_to_rgb: Converting bands to RGB values for plotting
drape_array_over_dem: Draping an array of the Digital Elevation Model

gemgis.visualization.resample_between_well_deviation_points(coordinates: numpy.ndarray) → numpy.ndarray#

Resampling between points that define the path of a well

Parameters: coordinates (np.ndarray) – Nx3 Numpy array containing the X, Y, and Z coordinates that define the path of a well
Returns: points_resampled – Resampled points along a well
Return type: np.ndarray

New in version 1.0.x.

gemgis.visualization.seismic_to_array(seismic_data, cdp_start: Optional[int] = None, cdp_end: Optional[int] = None, max_depth: Optional[Union[int, float]] = None) → numpy.ndarray#

Converting seismic data loaded with segysak to a NumPy array

Parameters

seismic_data (xarray.core.dataset.Dataset) – seismic data loaded with the segysak package
cdp_start (Union[int, type(None)]) – Value for the start CDP number, e.g. cdp_start=100, default is None
cdp_end (Union[int, type(None)]) – Value for the end CDP number, e.g. cdp_start=200, default is None
max_depth (Union[int, float, type(None)]) – Maximum depth of the seismic, e.g. max_depth=200, default is None

Returns

df_seismic_data_values_reshaped_selected – NumPy array containing the seismic data

Return type

np.ndarray

New in version 1.0.x.

gemgis.visualization.seismic_to_mesh(seismic_data, cdp_start: Optional[int] = None, cdp_end: Optional[int] = None, max_depth: Union[int, float] = None, sampling_rate: Optional[int] = None, shift: Union[int, float] = 0, source_crs: Union[str, pyproj.crs.crs.CRS] = None, target_crs: Union[str, pyproj.crs.crs.CRS] = None, cdp_coords=None) → pyvista.core.pointset.StructuredGrid#

Converting seismic data loaded with segysak to a PyVista Mesh

Parameters

seismic_data (xarray.core.dataset.Dataset) – seismic data loaded with the segysak package
cdp_start (Union[int, type(None)]) – Value for the start CDP number, e.g. cdp_start=100, default is None
cdp_end (Union[int, type(None)]) – Value for the end CDP number, e.g. cdp_start=200, default is None
max_depth (Union[int, float, type(None)]) – Maximum depth of the seismic, e.g. max_depth=200, default is None
sampling_rate (Union[int, type(None)]) – Sampling rate of the seismic, e.g. sampling_rate=2, default is None
shift (Union[int, float]) – Shift of the seismic, e.g. shift=100, default is 0
source_crs (Union[str, pyproj.crs.crs.CRS]) – Source CRS of the seismic, e.g. source_crs='EPSG:25832', default is None
target_crs (Union[str, pyproj.crs.crs.CRS]) – Target CRS of the seismic, e.g. target_crs='EPSG:3034', default is None
cdp_coords (Union[int, float, type(None)]) – CDP coordinates of the seismic if no CDP columns are present in the segysak object, default is None

Returns

grid – PyVista Structured grid containing the seismic data

Return type

pv.core.pointset.StructuredGrid

New in version 1.0.x.

gemgis.visualization.show_well_log_along_well(coordinates: numpy.ndarray, dist: numpy.ndarray, values: numpy.ndarray, radius_factor: Union[int, float] = 2) → pyvista.core.pointset.PolyData#

Function to return a tube representing well log values along a well path

Parameters

coordinates (np.ndarray) – Nx3 Numpy array containing the X, Y, and Z coordinates that define the path of a well
dist (np.ndarray) – np.ndarray containing the measured depths (MD) of values along the well path
values (np.ndarray) – np.ndarray containing the measured well log values along the well path
radius_factor (int, float) – Radius factor to adjust the diameter of the tube, e.g. radius_factor=2, default is 2

Returns

tube_along_spline – PyVista PolyData Pointset representing the the measured well log values along the well path

Return type

pyvista.core.pointset.PolyData

New in version 1.0.x.

gemgis.web module#

Contributors: Alexander Jüstel, Arthur Endlein Correia, Florian Wellmann, Marius Pischke

gemgis.web.create_request(wcs_url: str, version: str, identifier: str, form: str, extent: List[Union[int, float]], name: str = 'test.tif') → str#

Creating URL to request data from WCS Server

Parameters

wcs_url (str) – Url of the WCS server, e.g. url='https://www.wcs.nrw.de/geobasis/wcs_nw_dgm'
version (str) – Version number of the WCS as string, e.g. version='2.0.1'
identifier (str) – Name of the layer, e.g. identifier='nw_dgm'
form (str) – Format of the layer, e.g. form='image/tiff'
extent (List[Union[float,int]]) – Extent of the tile to be downloaded, size may be restricted by server, e.g. extent=[0, 972, 0, 1069]
name (str) – Name of file, e.g. name='tile1.tif', default is 'test.tif'

Returns

url – Url for the WCS request

Return type

str

New in version 1.0.x.

Example

>>> # Loading Libraries and WCS Service
>>> import gemgis as gg
>>> wcs = gg.web.load_wms(url='https://www.wcs.nrw.de/geobasis/wcs_nw_dgm')
>>> wcs
<owslib.coverage.wcs201.WebCoverageService_2_0_1 at 0x27fc64783d0>

>>> # Creating Request for WCS Service
>>> url = gg.web.create_request(url=wcs.url, version=wcs.version, identifier='nw_dgm', form='image/tiff', extent=[0, 1000, 0, 1000], name='test.tif'])

See also

load_wcs: Load WCS Service
load_as_file: Download WCS data file
load_as_files: Download WCS data files

gemgis.web.load_as_array(url: str, layer: str, style: str, crs: Union[str, dict], bbox: List[Union[int, float]], size: List[int], filetype: str, transparent: bool = True, save_image: bool = False, path: str = None, overwrite_file: bool = False, create_directory: bool = False) → numpy.ndarray#

Loading a portion of a WMS as array

Parameters

url (str) – Link of the WMS Service, e.g. url='https://ows.terrestris.de/osm/service?'
layer (str) – Name of layer to be requested, e.g. layer='OSM-WMS'
style (str) – Name of style of the layer, e.g. style='default'
crs (str) – String or dict containing the CRS, e.g. crs='EPSG:4647'
bbox (List[Union[float,int]]) – List of bounding box coordinates, e.g. bbox=[0, 972, 0, 1069]
size (List[int]) – List of x and y values defining the size of the image, e.g. size=[1000,1000]
filetype (str) – String of the image type to be downloaded, e.g. ‘filetype=’image/png’``
transparent (bool) – Variable if layer is transparent. Options include: True or False, default set to True
save_image (bool) – Variable to save image. Options include: True or False, default set to False
path (str) – Path and file name of the file to be saved, e.g. path=map.tif
overwrite_file (bool) – Variable to overwrite an already existing file. Options include: True or False, default set to False
create_directory (bool) – Variable to create a new directory of directory does not exist Options include: True or False, default set to False

Returns

wms_array – OWSlib map object loaded as np.ndarray

Return type

np.ndarray

New in version 1.0.x.

Example

>>> # Loading Libraries and WMS Service as array
>>> import gemgis as gg
>>> wms_map = gg.web.load_as_array(url='https://ows.terrestris.de/osm/service?', layer='OSM-WMS', style='default', crs='EPSG:4647', bbox=[32286000,32328000, 5620000,5648000], size=[4200, 2800], filetype='image/png')
>>> wms_map
array([[[0.8039216 , 0.7647059 , 0.65882355],
[0.85882354, 0.8784314 , 0.6627451 ],
[0.87058824, 0.91764706, 0.6666667 ],
...,
[0.78431374, 0.7647059 , 0.65882355],
[0.8862745 , 0.9019608 , 0.81960785],
[0.9529412 , 0.93333334, 0.9019608 ]]], dtype=float32)

See also

load_wms: Load WMS Service
load_as_map: Load Map from WMS Service

gemgis.web.load_as_file(url: str, path: str, overwrite_file: bool = False, create_directory: bool = False)#

Executing WCS request and downloading file into specified folder

Parameters

url (str) – Url for request
path (str) – Path where file is saved, e.g. path='tile.tif'
overwrite_file (bool) – Variable to overwrite an already existing file. Options include: True or False, default set to False
create_directory (bool) – Variable to create a new directory of directory does not exist Options include: True or False, default set to False

New in version 1.0.x.

Example

>>> # Loading Libraries and WCS Service
>>> import gemgis as gg
>>> wcs = gg.web.load_wms(url='https://www.wcs.nrw.de/geobasis/wcs_nw_dgm')
>>> wcs
<owslib.coverage.wcs201.WebCoverageService_2_0_1 at 0x27fc64783d0>

>>> # Creating Request for WCS Service
>>> url = gg.web.create_request(url=wcs.url, version=wcs.version, identifier='nw_dgm', form='image/tiff', extent=[0, 1000, 0, 1000], name='test.tif'])

>>> # Downloading file from WCS Service
>>> gg.web.load_as_file(url=url, path='tile.tif')

See also

load_wcs: Load WCS Service
create_request: Create request for WCS
load_as_files: Download WCS data files

gemgis.web.load_as_files(wcs_url: str, version: str, identifier: str, form: str, extent: List[Union[int, float]], size: int, path: str = '', create_directory: bool = False)#

Executing WCS requests and downloading files into specified folder

Parameters

wcs_url (str) – Url of the WCS server, e.g. url='https://www.wcs.nrw.de/geobasis/wcs_nw_dgm'
version (str) – Version number of the WCS as string, e.g. version='2.0.1'
identifier (str) – Name of the layer, e.g. identifier='nw_dgm'
form (str) – Format of the layer, e.g. form='image/tiff'
extent (List[Union[float,int]]) – Extent of the tile to be downloaded, size may be restricted by server, e.g. extent=[0, 972, 0, 1069]
size (int) – Size of the quadratic tile that is downloaded, e.g. size=2000
path (str) – Path where the file is going to be downloaded, e.g. name='tile1'
create_directory (bool) – Variable to create a new directory of directory does not exist Options include: True or False, default set to False

New in version 1.0.x.

Example

>>> # Loading Libraries and WCS Service
>>> import gemgis as gg
>>> wcs = gg.web.load_wms(url='https://www.wcs.nrw.de/geobasis/wcs_nw_dgm')
>>> wcs
<owslib.coverage.wcs201.WebCoverageService_2_0_1 at 0x27fc64783d0>

>>> # Downloading files from WCS Service
>>> gg.web.load_as_files(wcs_url=wcs.url, version=wcs.version, form='image/tiff', extent=[0, 10000, 0, 10000], size=2000, path='tile.tif')

See also

load_wcs: Load WCS Service
create_request: Create request for WCS
load_as_file: Download WCS data file

gemgis.web.load_as_gpd(url: str, typename: str = None, outputformat: str = None) → geopandas.geodataframe.GeoDataFrame#

Requesting data from a WFS Service

Parameters

url (str) – URL of the Web Feature Service, e.g. url="https://nibis.lbeg.de/net3/public/ogc.ashx?NodeId=476&Service=WFS&"
typename (str) – Name of the feature layer, e.g. typename='iwan:L383', default is None
outputformat (str) – Output format of the feature layer, e.g. outputformat='xml/gml2', default is None

Returns

feature – GeoDataFrame containing the feature data of the WFS Service

Return type

gpd.geodataframe.GeoDataFrame

New in version 1.0.x.

Example

>>> # Loading Libraries and WFS Service as GeoDataFrame
>>> import gemgis as gg
>>> wfs = gg.web.load_as_gpd(url="https://nibis.lbeg.de/net3/public/ogc.ashx?NodeId=476&Service=WFS&")
>>> wfs
    gml_id      OBJECTID    ID  SURVEYNAME      ARCHIV  MESSJAHR        OPERATOR                                        OP_NACHFOL                          MESSFIRMA                               MESSPUNKTE  UP_DATE                     geometry
0       1541    1541        112 Jemgum 2007     0127494 2007        GdF Produktion Exploration Deutschland GmbH Neptune Energy Deutschland GmbH Geophysik und Geotechnik Leipzig GmbH   1340        2020-01-20T00:00:00+01:00   MULTIPOLYGON (((32395246.839 5907777.660, 3239...

See also

load_wfs: Load WFS Service

gemgis.web.load_as_map(url: str, layer: str, style: str, crs: Union[str, dict], bbox: List[Union[int, float]], size: List[int], filetype: str, transparent: bool = True, save_image: bool = False, path: str = None, overwrite_file: bool = False, create_directory: bool = False)#

Loading a portion of a WMS as array

Parameters

url (str) – Link of the WMS Service, e.g. url='https://ows.terrestris.de/osm/service?'
layer (str) – Name of layer to be requested, e.g. layer='OSM-WMS'
style (str) – Name of style of the layer, e.g. style='default'
crs (str) – String or dict containing the CRS, e.g. crs='EPSG:4647'
bbox (List[Union[float,int]]) – List of bounding box coordinates, e.g. bbox=[0, 972, 0, 1069]
size (List[int]) – List of x and y values defining the size of the image, e.g. size=[1000,1000]
filetype (str) – String of the image type to be downloaded, e.g. filetype='image/png'
transparent (bool) – Variable if layer is transparent. Options include: True or False, default set to True
save_image (bool) – Variable to save image. Options include: True or False, default set to False
path (str) – Path and file name of the file to be saved, e.g. path=map.tif
overwrite_file (bool) – Variable to overwrite an already existing file. Options include: True or False, default set to False
create_directory (bool) – Variable to create a new directory of directory does not exist Options include: True or False, default set to False

Returns

wms_map – OWSlib map object

Return type

owslib.util.ResponseWrapper

New in version 1.0.x.

Example

>>> # Loading Libraries and WMS Service as Map
>>> import gemgis as gg
>>> wms_map = gg.web.load_as_map(url='https://ows.terrestris.de/osm/service?', layer='OSM-WMS', style='default', crs='EPSG:4647', bbox=[32286000,32328000, 5620000,5648000], size=[4200, 2800], filetype='image/png')
>>> wms_map
<owslib.util.ResponseWrapper at 0x261d348cc10>

See also

load_wms: Load WMS Service
load_as_array: Load Map as array from WMS Service

gemgis.web.load_wcs(url: str)#

Loading Web Coverage Service

Parameters: url (str) – Link of the Web Coverage Service, e.g. url='https://www.wcs.nrw.de/geobasis/wcs_nw_dgm'
Returns: wcs – OWSLib Web Coverage Object
Return type: owslib.coverage.wcs201.WebCoverageService_2_0_1

New in version 1.0.x.

Example

>>> # Loading Libraries and WCS Service
>>> import gemgis as gg
>>> wcs = gg.web.load_wms(url='https://www.wcs.nrw.de/geobasis/wcs_nw_dgm')
>>> wcs
<owslib.coverage.wcs201.WebCoverageService_2_0_1 at 0x27fc64783d0>

See also

create_request: Create request for WCS
load_as_file: Download WCS data file
load_as_files: Download WCS data files

gemgis.web.load_wfs(url: str)#

Loading a WFS Service by URL

Parameters: url (str) – Link of the WFS Service, e.g. url="https://nibis.lbeg.de/net3/public/ogc.ashx?NodeId=476&Service=WFS&"
Returns: wfs – OWSLib Feature object
Return type: owslib.feature.wfs100.WebFeatureService_1_0_0

New in version 1.0.x.

Example

>>> # Loading Libraries and WFS Service
>>> import gemgis as gg
>>> wfs = gg.web.load_wfs(url="https://nibis.lbeg.de/net3/public/ogc.ashx?NodeId=476&Service=WFS&")
>>> wfs
<owslib.feature.wfs100.WebFeatureService_1_0_0 at 0x19260e21340>

See also

load_as_gpd: Load information of a WFS Service as GeoDataFrame

gemgis.web.load_wms(url: str)#

Loading a WMS Service by URL

Parameters: url (str) – Link of the WMS Service, e.g. url='https://ows.terrestris.de/osm/service?'
Returns: wms – OWSLib WebMapService Object
Return type: owslib.map.wms111.WebMapService

New in version 1.0.x.

Example

>>> # Loading Libraries and WMS Service
>>> import gemgis as gg
>>> wms = gg.web.load_wms(url='https://ows.terrestris.de/osm/service?')
>>> wms
<owslib.map.wms111.WebMapService_1_1_1 at 0x1c434eb6370>

See also

load_as_map: Load Map from WMS Service
load_as_array: Load Map as array from WMS Service

Module contents#

Top-level package for GemGIS.

GemGIS - Spatial data processing for geomodeling

GemGIS API Reference

Contents

GemGIS API Reference#

gemgis.download_gemgis_data module#

gemgis.gemgis module#

gemgis.misc module#

gemgis.postprocessing module#

gemgis.raster module#

gemgis.utils module#

gemgis.vector module#

gemgis.visualization module#

gemgis.web module#

Module contents#