def __init__(self,
gdf,
values,
spatial_weights,
unique_id,
rng=None,
verbose=True):
try:
from inequality.gini import Gini
except ImportError:
raise ImportError("The 'inequality' package is required.")
self.gdf = gdf
self.sw = spatial_weights
self.id = gdf[unique_id]
self.rng = rng
data = gdf.copy()
if values is not None:
if not isinstance(values, str):
data["mm_v"] = values
values = "mm_v"
self.values = data[values]
if self.values.min() < 0:
raise ValueError(
"Values contain negative numbers. Normalise data before"
"using momepy.Gini.")
data = data.set_index(unique_id)[values]
if rng:
from momepy import limit_range
results_list = []
for index in tqdm(data.index, total=data.shape[0],
disable=not verbose):
if index in spatial_weights.neighbors.keys():
neighbours = spatial_weights.neighbors[index].copy()
if neighbours:
neighbours.append(index)
values_list = data.loc[neighbours].values
if rng:
values_list = limit_range(values_list, rng=rng)
results_list.append(Gini(values_list).g)
else:
results_list.append(0)
else:
results_list.append(np.nan)
self.series = pd.Series(results_list, index=gdf.index)
def test_Gini(self):
g = Gini(self.y)
np.testing.assert_almost_equal(g.g, 0.35372371173452849)