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import geopandas as gpd
import numpy as np
import momepy as mm
class TimeDiversity:
def setup(self):
test_file_path = mm.datasets.get_path("bubenec")
self.df_buildings = gpd.read_file(test_file_path, layer="buildings")
self.df_streets = gpd.read_file(test_file_path, layer="streets")
self.df_tessellation = gpd.read_file(test_file_path, layer="tessellation")
self.df_buildings["height"] = np.linspace(10.0, 30.0, 144)
self.df_tessellation["area"] = mm.Area(self.df_tessellation).series
self.sw = mm.sw_high(k=3, gdf=self.df_tessellation, ids="uID")
self.df_tessellation["cat"] = list(range(8)) * 18
def time_Range(self):
mm.Range(self.df_tessellation, "area", self.sw, "uID", (25, 75))
def time_Theil(self):
mm.Theil(self.df_tessellation, "area", self.sw, "uID")
def time_Gini(self):
mm.Gini(self.df_tessellation, "area", self.sw, "uID")
def time_Unique(self):
mm.Unique(self.df_tessellation, "cat", self.sw, "uID")
class TimeDiversityBinning:
param_names = ["binning"]
params = [("HeadTailBreaks", "Quantiles", "EqualInterval")]
def setup(self, *args):
test_file_path = mm.datasets.get_path("bubenec")
self.df_buildings = gpd.read_file(test_file_path, layer="buildings")
self.df_streets = gpd.read_file(test_file_path, layer="streets")
self.df_tessellation = gpd.read_file(test_file_path, layer="tessellation")
self.df_buildings["height"] = np.linspace(10.0, 30.0, 144)
self.df_tessellation["area"] = mm.Area(self.df_tessellation).series
self.sw = mm.sw_high(k=3, gdf=self.df_tessellation, ids="uID")
def time_Simpson(self, binning):
mm.Simpson(self.df_tessellation, "area", self.sw, "uID", binning)
def time_Shannon(self, binning):
mm.Shannon(self.df_tessellation, "area", self.sw, "uID", binning)
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