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A LineString with the same start and end point is not a Polygon but a LinearRing. You need to understand the difference. If you want a Polygon from the LinearRing # test if your output is a LinearRi …

=0: buff = geom1.Buffer(0.0001) linkline = geom2.Intersection(buff) linkpoint = linkline.GetPoint(0) # create a new ogr geometry with wkt here …

Sympy is inappropriate here (or very difficult to use). For geometrical calculations in 2D, the best solution is Shapely. But don't forget that GRASS GIS 6.4.x has the module grass.script (look at …

It is a part of a GeoJSON formated geometry and the ordering of x and y are important. …

it is not realy complicated, look at Memory provider in vector: : a point is created with QgsPoint(x,y) and QgsGeometry.fromPoint(QgsPoint(x,y)) a line is created with two points: QgsGeometry.fromPo …

I don't understand your question: line = LineString([(0, 0), (2, 2)]) # create a point which lies along the line point = line.interpolate(1) line.contains(point) True You want the two lines which li …

There are many geospatial Python modules that can convert GeoJSON to shapefiles (and the reverse): Fiona PySAL Pyshp 1.7 and up GDAL/OGR PyQGIS with the new API python-geojson see Python Geo_inte …

WKT is only a text markup language for representing vector geometry, therefore you cannot convert 3D WKT to 2D (= text to text), you need to change the geometry The problem with ogr is that it seems that … False point.GetGeometryType()==ogr.wkbPoint25D True 2) But, with the creation of a 2D point with Shapely from shapely.geometry import Point pt = Point(1198054.34, 648493.09) # conversion to an ogr geometry …

intersects gives the boolean value True, False, intersection gives the geometry If you use the dir function of Python dir(intersection) ['Error', '__class__', '__delattr__', '__dict__', '__doc__', ' …

nearest_geom = nearest_points(point, multipoint) d = queried_geom.distance(nearest_geom) df.loc[index, "nearest_geom"] = str(nearest_geom) df.loc[index, "dist"] = d print(df) id geometry … 2, algorithm='ball_tree').fit(coords) distances, indices = nbrs.kneighbors(coords) And after: df['ind1']= indices[:,0] df['ind2']= indices[:,1] df['dist']= distances[:,1] print(df) id geometry …

Shapely PyQGIS, and GeoDjango use the same API based on the GEOS library: With Shapely: with a list of points: from shapely.geometry import Point, LineString, mapping pt1 = Point(0,0) pt2 = Point …

QgsField("latStart", QVariant.String), QgsField("lonStart", QVariant.String), QgsField("latEnd", QVariant.String), QgsField("lonEnd", QVariant.String) ]) # create a feature feat = QgsFeature() # add the geometry …

In QGIS try using GDAL/OGR to read shapefiles and in GDAL: ESRI Shapefile MultiPatch files are read and each patch geometry is turned into a multi-polygon representation with one polygon per triangle … Control in Python with Fiona import fiona c = fiona.open(fiona.open("4_134.shp")) print len(c) #number of features 1 first = c.next() print first['geometry'] {'type': 'MultiPolygon', 'coordinates': [ …

Writing the shapefile import fiona from fiona.crs import from_epsg my_schema={'geometry': 'Point', 'properties': {'intLanes': 'str', 'y': 'str', 'incLanes': 'str', 'junction_shape': 'str', 'x': 'str', … 'type': 'str', 'id': 'str'}} wr_dict = {'geometry': {'type': 'Point', 'coordinates': (488901.97760411515, 5078198.250875515)}, 'properties': {'intLanes': ':A_0_0 :A_1_0', 'junction_shape': '30.62,42.35 …

( W.component_labels) [0 0 1 2 3 4 3] There are 2 groups with polygon intersections, 0,1 and 4,6 gdf['inter']= W.component_labels #labels of connected components: print(gdf) id geometry … "] = g.geometry[g.index[0]]- g.geometry[g.index[1]] gdf.loc[g.index[1],"geometry"]= g.geometry[g.index[1]]- g.geometry[g.index[0]] for name, group in groups: if len(group) > 1: # intersection …