From d80af4d65095925e0bb3bac861fdcebcbe540578 Mon Sep 17 00:00:00 2001
From: Martin Fleischmann <martin@martinfleischmann.net>
Date: Tue, 23 Apr 2024 23:08:42 +0200
Subject: [PATCH 01/11] ENH: describe as a replacement of AverageCharacter

---
 momepy/functional/_distribution.py | 84 +++++++++++++++++++++++++++++-
 momepy/utils.py                    |  6 +--
 2 files changed, 84 insertions(+), 6 deletions(-)

diff --git a/momepy/functional/_distribution.py b/momepy/functional/_distribution.py
index e6ded9d0..25dbbc35 100644
--- a/momepy/functional/_distribution.py
+++ b/momepy/functional/_distribution.py
@@ -3,9 +3,12 @@
 import shapely
 from geopandas import GeoDataFrame, GeoSeries
 from libpysal.graph import Graph
+from numpy.typing import NDArray
 from packaging.version import Version
-from pandas import Series
-from scipy import sparse
+from pandas import DataFrame, Series
+from scipy import sparse, stats
+
+from ..utils import limit_range
 
 __all__ = [
     "orientation",
@@ -16,6 +19,7 @@
     "building_adjacency",
     "neighbors",
     "street_alignment",
+    "describe",
 ]
 
 GPD_GE_013 = Version(gpd.__version__) >= Version("0.13.0")
@@ -339,3 +343,79 @@ def street_alignment(
     Series
     """
     return (building_orientation - street_orientation.loc[street_index].values).abs()
+
+
+def describe(
+    values: NDArray[np.float_] | Series,
+    graph: Graph,
+    q: tuple[float, float] | None = None,
+    include_mode: bool = False,
+) -> DataFrame:
+    """Describe the distribution of values within a set neighbourhood.
+
+    Given the graph, computes the descriptive statisitcs of values within the
+    neighbourhood of each node. Optionally, the values can be limited to a certain
+    quantile range before computing the statistics.
+
+    Notes
+    -----
+    The index of ``values`` must match the index along which the ``graph`` is
+    built.
+
+    Parameters
+    ----------
+    values : NDArray[np.float_] | Series
+        array of values
+    graph : libpysal.graph.Graph
+        Graph representing spatial relationships between elements.
+    q : tuple[float, float] | None, optional
+        tuple of percentages for the percentiles to compute. Values must be between 0
+        and 100 inclusive. When set, values below and above the percentiles will be
+        discarded before computation of the average. The percentiles are computed for
+        each neighborhood. By default None
+    include_mode : False
+        Compute mode along with other statistics. Default is False. Mode is
+        computationally expensive and not useful for continous variables.
+
+    Returns
+    -------
+    DataFrame
+        A DataFrame with descriptive statistics
+    """
+
+    def _describe(values, q, include_mode=False):
+        """Helper function to calculate average."""
+        values = limit_range(values, q)
+
+        results = [
+            np.mean(values),
+            np.median(values),
+            np.std(values),
+            np.min(values),
+            np.max(values),
+            np.sum(values),
+        ]
+        if include_mode:
+            results.append(stats.mode(values, keepdims=False)[0])
+        return results
+
+    if not isinstance(values, Series):
+        values = Series(values)
+
+    grouper = values.take(graph._adjacency.index.codes[1]).groupby(
+        graph._adjacency.index.codes[0]
+    )
+
+    if q is None:
+        stat_ = grouper.agg(["mean", "median", "std", "min", "max", "sum"])
+        if include_mode:
+            stat_["mode"] = grouper.agg(lambda x: stats.mode(x, keepdims=False)[0])
+    else:
+        agg = graph.apply(values, _describe, q=q, include_mode=include_mode)
+        stat_ = DataFrame(zip(*agg, strict=True)).T
+        cols = ["mean", "median", "std", "min", "max", "sum"]
+        if include_mode:
+            cols.append("mode")
+        stat_.columns = cols
+
+    return stat_
diff --git a/momepy/utils.py b/momepy/utils.py
index 89d8e3c6..f7134b4b 100644
--- a/momepy/utils.py
+++ b/momepy/utils.py
@@ -479,11 +479,9 @@ def limit_range(vals, rng):
             method = {"interpolation": "nearest"}
         rng = sorted(rng)
         if nan_tracker.any():
-            lower = np.nanpercentile(vals, rng[0], **method)
-            higher = np.nanpercentile(vals, rng[1], **method)
+            lower, higher = np.nanpercentile(vals, rng, **method)
         else:
-            lower = np.percentile(vals, rng[0], **method)
-            higher = np.percentile(vals, rng[1], **method)
+            lower, higher = np.percentile(vals, rng, **method)
         vals = vals[(lower <= vals) & (vals <= higher)]
 
     return vals

From 595a5c4794d3e017b2cbc2f3796ce7b32071128c Mon Sep 17 00:00:00 2001
From: Martin Fleischmann <martin@martinfleischmann.net>
Date: Tue, 23 Apr 2024 23:26:07 +0200
Subject: [PATCH 02/11] perf + fixup

---
 momepy/functional/_distribution.py | 4 ++--
 momepy/utils.py                    | 1 -
 2 files changed, 2 insertions(+), 3 deletions(-)

diff --git a/momepy/functional/_distribution.py b/momepy/functional/_distribution.py
index 25dbbc35..4783045d 100644
--- a/momepy/functional/_distribution.py
+++ b/momepy/functional/_distribution.py
@@ -385,7 +385,7 @@ def describe(
 
     def _describe(values, q, include_mode=False):
         """Helper function to calculate average."""
-        values = limit_range(values, q)
+        values = limit_range(values.values, q)
 
         results = [
             np.mean(values),
@@ -411,7 +411,7 @@ def _describe(values, q, include_mode=False):
         if include_mode:
             stat_["mode"] = grouper.agg(lambda x: stats.mode(x, keepdims=False)[0])
     else:
-        agg = graph.apply(values, _describe, q=q, include_mode=include_mode)
+        agg = grouper.apply(_describe, q=q, include_mode=include_mode)
         stat_ = DataFrame(zip(*agg, strict=True)).T
         cols = ["mean", "median", "std", "min", "max", "sum"]
         if include_mode:
diff --git a/momepy/utils.py b/momepy/utils.py
index f7134b4b..bb437718 100644
--- a/momepy/utils.py
+++ b/momepy/utils.py
@@ -469,7 +469,6 @@ def limit_range(vals, rng):
         The limited array.
     """
 
-    vals = np.asarray(vals)
     nan_tracker = np.isnan(vals)
 
     if (len(vals) > 2) and (not nan_tracker.all()):

From 24abb99bc24f90faafbcaf19bc14ae1fff171357 Mon Sep 17 00:00:00 2001
From: Martin Fleischmann <martin@martinfleischmann.net>
Date: Tue, 23 Apr 2024 23:30:29 +0200
Subject: [PATCH 03/11] limit_range array input

---
 momepy/dimension.py        | 2 +-
 momepy/diversity.py        | 2 +-
 momepy/tests/test_utils.py | 6 +++---
 3 files changed, 5 insertions(+), 5 deletions(-)

diff --git a/momepy/dimension.py b/momepy/dimension.py
index eac95128..61956fbc 100644
--- a/momepy/dimension.py
+++ b/momepy/dimension.py
@@ -438,7 +438,7 @@ def __init__(
                 values_list = data.loc[neighbours]
 
                 if rng:
-                    values_list = limit_range(values_list, rng=rng)
+                    values_list = limit_range(values_list.values, rng=rng)
                 if "mean" in mode:
                     means.append(np.mean(values_list))
                 if "median" in mode:
diff --git a/momepy/diversity.py b/momepy/diversity.py
index a53725b9..f8399c6e 100644
--- a/momepy/diversity.py
+++ b/momepy/diversity.py
@@ -209,7 +209,7 @@ def __init__(self, gdf, values, spatial_weights, unique_id, rng=None, verbose=Tr
                 values_list = data.loc[neighbours]
 
                 if rng:
-                    values_list = limit_range(values_list, rng=rng)
+                    values_list = limit_range(values_list.values, rng=rng)
                 results_list.append(Theil(values_list).T)
             else:
                 results_list.append(np.nan)
diff --git a/momepy/tests/test_utils.py b/momepy/tests/test_utils.py
index dd289e4b..701d2dc5 100644
--- a/momepy/tests/test_utils.py
+++ b/momepy/tests/test_utils.py
@@ -196,9 +196,9 @@ def test_nx_to_gdf_osmnx(self):
         assert len(lines) == 16
 
     def test_limit_range(self):
-        assert list(mm.limit_range(range(10), rng=(25, 75))) == [2, 3, 4, 5, 6, 7]
-        assert list(mm.limit_range(range(10), rng=(10, 90))) == [1, 2, 3, 4, 5, 6, 7, 8]
-        assert list(mm.limit_range([0, 1], rng=(25, 75))) == [0, 1]
+        assert list(mm.limit_range(np.arange(10), rng=(25, 75))) == [2, 3, 4, 5, 6, 7]
+        assert list(mm.limit_range(np.arange(10), rng=(10, 90))) == [1, 2, 3, 4, 5, 6, 7, 8]
+        assert list(mm.limit_range(np.array([0, 1]), rng=(25, 75))) == [0, 1]
         assert list(
             mm.limit_range(np.array([0, 1, 2, 3, 4, np.nan]), rng=(25, 75))
         ) == [1, 2, 3]

From 24bded69ce10386fcdf9c631762405686dc0ecd8 Mon Sep 17 00:00:00 2001
From: Martin Fleischmann <martin@martinfleischmann.net>
Date: Wed, 24 Apr 2024 09:14:52 +0200
Subject: [PATCH 04/11] Apply suggestions from code review

Co-authored-by: James Gaboardi <jgaboardi@gmail.com>
---
 momepy/functional/_distribution.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/momepy/functional/_distribution.py b/momepy/functional/_distribution.py
index 4783045d..b71b8249 100644
--- a/momepy/functional/_distribution.py
+++ b/momepy/functional/_distribution.py
@@ -365,14 +365,14 @@ def describe(
     Parameters
     ----------
     values : NDArray[np.float_] | Series
-        array of values
+        An array of values.
     graph : libpysal.graph.Graph
         Graph representing spatial relationships between elements.
     q : tuple[float, float] | None, optional
-        tuple of percentages for the percentiles to compute. Values must be between 0
+        Tuple of percentages for the percentiles to compute. Values must be between 0
         and 100 inclusive. When set, values below and above the percentiles will be
         discarded before computation of the average. The percentiles are computed for
-        each neighborhood. By default None
+        each neighborhood. By default None.
     include_mode : False
         Compute mode along with other statistics. Default is False. Mode is
         computationally expensive and not useful for continous variables.
@@ -380,7 +380,7 @@ def describe(
     Returns
     -------
     DataFrame
-        A DataFrame with descriptive statistics
+        A DataFrame with descriptive statistics.
     """
 
     def _describe(values, q, include_mode=False):

From 90005ba477ef6aa866f4b38f44dce082d8a4fa9a Mon Sep 17 00:00:00 2001
From: Martin Fleischmann <martin@martinfleischmann.net>
Date: Wed, 24 Apr 2024 09:31:57 +0200
Subject: [PATCH 05/11] rename to y

---
 momepy/functional/_distribution.py | 12 ++++++------
 1 file changed, 6 insertions(+), 6 deletions(-)

diff --git a/momepy/functional/_distribution.py b/momepy/functional/_distribution.py
index b71b8249..9be1a1c5 100644
--- a/momepy/functional/_distribution.py
+++ b/momepy/functional/_distribution.py
@@ -346,7 +346,7 @@ def street_alignment(
 
 
 def describe(
-    values: NDArray[np.float_] | Series,
+    y: NDArray[np.float_] | Series,
     graph: Graph,
     q: tuple[float, float] | None = None,
     include_mode: bool = False,
@@ -364,8 +364,8 @@ def describe(
 
     Parameters
     ----------
-    values : NDArray[np.float_] | Series
-        An array of values.
+    y : NDArray[np.float_] | Series
+        An 1D array of numeric values to be described.
     graph : libpysal.graph.Graph
         Graph representing spatial relationships between elements.
     q : tuple[float, float] | None, optional
@@ -399,10 +399,10 @@ def _describe(values, q, include_mode=False):
             results.append(stats.mode(values, keepdims=False)[0])
         return results
 
-    if not isinstance(values, Series):
-        values = Series(values)
+    if not isinstance(y, Series):
+        y = Series(y)
 
-    grouper = values.take(graph._adjacency.index.codes[1]).groupby(
+    grouper = y.take(graph._adjacency.index.codes[1]).groupby(
         graph._adjacency.index.codes[0]
     )
 

From 88082f885c119a160604eb3daa9a7303fb8ab8ab Mon Sep 17 00:00:00 2001
From: Martin Fleischmann <martin@martinfleischmann.net>
Date: Wed, 24 Apr 2024 09:33:43 +0200
Subject: [PATCH 06/11] move to diversity

---
 momepy/__init__.py                 |  1 +
 momepy/functional/_distribution.py | 84 +----------------------------
 momepy/functional/_diversity.py    | 85 ++++++++++++++++++++++++++++++
 3 files changed, 88 insertions(+), 82 deletions(-)
 create mode 100644 momepy/functional/_diversity.py

diff --git a/momepy/__init__.py b/momepy/__init__.py
index e18a4bd2..8ad653a4 100644
--- a/momepy/__init__.py
+++ b/momepy/__init__.py
@@ -9,6 +9,7 @@
 from .elements import *
 from .functional._dimension import *
 from .functional._distribution import *
+from .functional._diversity import *
 from .functional._elements import *
 from .functional._shape import *
 from .graph import *
diff --git a/momepy/functional/_distribution.py b/momepy/functional/_distribution.py
index 9be1a1c5..e6ded9d0 100644
--- a/momepy/functional/_distribution.py
+++ b/momepy/functional/_distribution.py
@@ -3,12 +3,9 @@
 import shapely
 from geopandas import GeoDataFrame, GeoSeries
 from libpysal.graph import Graph
-from numpy.typing import NDArray
 from packaging.version import Version
-from pandas import DataFrame, Series
-from scipy import sparse, stats
-
-from ..utils import limit_range
+from pandas import Series
+from scipy import sparse
 
 __all__ = [
     "orientation",
@@ -19,7 +16,6 @@
     "building_adjacency",
     "neighbors",
     "street_alignment",
-    "describe",
 ]
 
 GPD_GE_013 = Version(gpd.__version__) >= Version("0.13.0")
@@ -343,79 +339,3 @@ def street_alignment(
     Series
     """
     return (building_orientation - street_orientation.loc[street_index].values).abs()
-
-
-def describe(
-    y: NDArray[np.float_] | Series,
-    graph: Graph,
-    q: tuple[float, float] | None = None,
-    include_mode: bool = False,
-) -> DataFrame:
-    """Describe the distribution of values within a set neighbourhood.
-
-    Given the graph, computes the descriptive statisitcs of values within the
-    neighbourhood of each node. Optionally, the values can be limited to a certain
-    quantile range before computing the statistics.
-
-    Notes
-    -----
-    The index of ``values`` must match the index along which the ``graph`` is
-    built.
-
-    Parameters
-    ----------
-    y : NDArray[np.float_] | Series
-        An 1D array of numeric values to be described.
-    graph : libpysal.graph.Graph
-        Graph representing spatial relationships between elements.
-    q : tuple[float, float] | None, optional
-        Tuple of percentages for the percentiles to compute. Values must be between 0
-        and 100 inclusive. When set, values below and above the percentiles will be
-        discarded before computation of the average. The percentiles are computed for
-        each neighborhood. By default None.
-    include_mode : False
-        Compute mode along with other statistics. Default is False. Mode is
-        computationally expensive and not useful for continous variables.
-
-    Returns
-    -------
-    DataFrame
-        A DataFrame with descriptive statistics.
-    """
-
-    def _describe(values, q, include_mode=False):
-        """Helper function to calculate average."""
-        values = limit_range(values.values, q)
-
-        results = [
-            np.mean(values),
-            np.median(values),
-            np.std(values),
-            np.min(values),
-            np.max(values),
-            np.sum(values),
-        ]
-        if include_mode:
-            results.append(stats.mode(values, keepdims=False)[0])
-        return results
-
-    if not isinstance(y, Series):
-        y = Series(y)
-
-    grouper = y.take(graph._adjacency.index.codes[1]).groupby(
-        graph._adjacency.index.codes[0]
-    )
-
-    if q is None:
-        stat_ = grouper.agg(["mean", "median", "std", "min", "max", "sum"])
-        if include_mode:
-            stat_["mode"] = grouper.agg(lambda x: stats.mode(x, keepdims=False)[0])
-    else:
-        agg = grouper.apply(_describe, q=q, include_mode=include_mode)
-        stat_ = DataFrame(zip(*agg, strict=True)).T
-        cols = ["mean", "median", "std", "min", "max", "sum"]
-        if include_mode:
-            cols.append("mode")
-        stat_.columns = cols
-
-    return stat_
diff --git a/momepy/functional/_diversity.py b/momepy/functional/_diversity.py
new file mode 100644
index 00000000..93836e74
--- /dev/null
+++ b/momepy/functional/_diversity.py
@@ -0,0 +1,85 @@
+import numpy as np
+from libpysal.graph import Graph
+from numpy.typing import NDArray
+from pandas import DataFrame, Series
+from scipy import stats
+
+from ..utils import limit_range
+
+__all__ = ["describe"]
+
+
+def describe(
+    y: NDArray[np.float_] | Series,
+    graph: Graph,
+    q: tuple[float, float] | None = None,
+    include_mode: bool = False,
+) -> DataFrame:
+    """Describe the distribution of values within a set neighbourhood.
+
+    Given the graph, computes the descriptive statisitcs of values within the
+    neighbourhood of each node. Optionally, the values can be limited to a certain
+    quantile range before computing the statistics.
+
+    Notes
+    -----
+    The index of ``values`` must match the index along which the ``graph`` is
+    built.
+
+    Parameters
+    ----------
+    y : NDArray[np.float_] | Series
+        An 1D array of numeric values to be described.
+    graph : libpysal.graph.Graph
+        Graph representing spatial relationships between elements.
+    q : tuple[float, float] | None, optional
+        Tuple of percentages for the percentiles to compute. Values must be between 0
+        and 100 inclusive. When set, values below and above the percentiles will be
+        discarded before computation of the average. The percentiles are computed for
+        each neighborhood. By default None.
+    include_mode : False
+        Compute mode along with other statistics. Default is False. Mode is
+        computationally expensive and not useful for continous variables.
+
+    Returns
+    -------
+    DataFrame
+        A DataFrame with descriptive statistics.
+    """
+
+    def _describe(values, q, include_mode=False):
+        """Helper function to calculate average."""
+        values = limit_range(values.values, q)
+
+        results = [
+            np.mean(values),
+            np.median(values),
+            np.std(values),
+            np.min(values),
+            np.max(values),
+            np.sum(values),
+        ]
+        if include_mode:
+            results.append(stats.mode(values, keepdims=False)[0])
+        return results
+
+    if not isinstance(y, Series):
+        y = Series(y)
+
+    grouper = y.take(graph._adjacency.index.codes[1]).groupby(
+        graph._adjacency.index.codes[0]
+    )
+
+    if q is None:
+        stat_ = grouper.agg(["mean", "median", "std", "min", "max", "sum"])
+        if include_mode:
+            stat_["mode"] = grouper.agg(lambda x: stats.mode(x, keepdims=False)[0])
+    else:
+        agg = grouper.apply(_describe, q=q, include_mode=include_mode)
+        stat_ = DataFrame(zip(*agg, strict=True)).T
+        cols = ["mean", "median", "std", "min", "max", "sum"]
+        if include_mode:
+            cols.append("mode")
+        stat_.columns = cols
+
+    return stat_

From 8db53b51f34fd947b805ffc467b3ec71576dd570 Mon Sep 17 00:00:00 2001
From: Martin Fleischmann <martin@martinfleischmann.net>
Date: Wed, 24 Apr 2024 09:35:59 +0200
Subject: [PATCH 07/11] move assert_result to its own file

---
 momepy/functional/tests/_testing.py          | 11 +++++++++++
 momepy/functional/tests/test_distribution.py |  2 +-
 momepy/functional/tests/test_shape.py        | 12 +++---------
 3 files changed, 15 insertions(+), 10 deletions(-)
 create mode 100644 momepy/functional/tests/_testing.py

diff --git a/momepy/functional/tests/_testing.py b/momepy/functional/tests/_testing.py
new file mode 100644
index 00000000..d8a7b62f
--- /dev/null
+++ b/momepy/functional/tests/_testing.py
@@ -0,0 +1,11 @@
+import pandas as pd
+import pytest
+from pandas.testing import assert_index_equal
+
+
+def assert_result(result, expected, geometry, **kwargs):
+    """Check the expected values and types of the result."""
+    for key, value in expected.items():
+        assert getattr(result, key)() == pytest.approx(value)
+    assert isinstance(result, pd.Series)
+    assert_index_equal(result.index, geometry.index, **kwargs)
diff --git a/momepy/functional/tests/test_distribution.py b/momepy/functional/tests/test_distribution.py
index 04ba73e2..76993ec0 100644
--- a/momepy/functional/tests/test_distribution.py
+++ b/momepy/functional/tests/test_distribution.py
@@ -4,7 +4,7 @@
 
 import momepy as mm
 
-from .test_shape import assert_result
+from ._testing import assert_result
 
 
 class TestDistribution:
diff --git a/momepy/functional/tests/test_shape.py b/momepy/functional/tests/test_shape.py
index 78ca3003..b79d199a 100644
--- a/momepy/functional/tests/test_shape.py
+++ b/momepy/functional/tests/test_shape.py
@@ -3,19 +3,13 @@
 import pandas as pd
 import pytest
 from packaging.version import Version
-from pandas.testing import assert_frame_equal, assert_index_equal, assert_series_equal
+from pandas.testing import assert_frame_equal, assert_series_equal
 
 import momepy as mm
 
-GPD_013 = Version(gpd.__version__) >= Version("0.13")
-
+from ._testing import assert_result
 
-def assert_result(result, expected, geometry, **kwargs):
-    """Check the expected values and types of the result."""
-    for key, value in expected.items():
-        assert getattr(result, key)() == pytest.approx(value)
-    assert isinstance(result, pd.Series)
-    assert_index_equal(result.index, geometry.index, **kwargs)
+GPD_013 = Version(gpd.__version__) >= Version("0.13")
 
 
 class TestShape:

From 0ce3c3bb6977915674ee700a57961714937c8372 Mon Sep 17 00:00:00 2001
From: Martin Fleischmann <martin@martinfleischmann.net>
Date: Wed, 24 Apr 2024 09:57:17 +0200
Subject: [PATCH 08/11] add tests

---
 momepy/functional/tests/test_diversity.py | 111 ++++++++++++++++++++++
 1 file changed, 111 insertions(+)
 create mode 100644 momepy/functional/tests/test_diversity.py

diff --git a/momepy/functional/tests/test_diversity.py b/momepy/functional/tests/test_diversity.py
new file mode 100644
index 00000000..4bc63a5d
--- /dev/null
+++ b/momepy/functional/tests/test_diversity.py
@@ -0,0 +1,111 @@
+import geopandas as gpd
+from libpysal.graph import Graph
+from pandas.testing import assert_frame_equal
+
+import momepy as mm
+
+from ._testing import assert_result
+
+
+class TestDistribution:
+    def setup_method(self):
+        test_file_path = mm.datasets.get_path("bubenec")
+        self.df_buildings = gpd.read_file(test_file_path, layer="buildings")
+        self.graph = Graph.build_knn(self.df_buildings.centroid, k=3)
+
+    def test_describe(self):
+        area = self.df_buildings.area
+        r = mm.describe(area, self.graph)
+
+        expected_mean = {
+            "mean": 587.3761020554495,
+            "sum": 84582.15869598472,
+            "min": 50.44045729583316,
+            "max": 1187.2662413659234,
+        }
+        assert_result(r["mean"], expected_mean, self.df_buildings, exact=False)
+
+        expected_median = {
+            "mean": 577.4640489818667,
+            "sum": 83154.8230533888,
+            "min": 50.43336175017242,
+            "max": 1225.8094201694726,
+        }
+        assert_result(r["median"], expected_median, self.df_buildings, exact=False)
+
+        expected_std = {
+            "mean": 255.59307136480083,
+            "sum": 36805.40227653132,
+            "min": 0.05050450812944085,
+            "max": 1092.484902679786,
+        }
+        assert_result(r["std"], expected_std, self.df_buildings, exact=False)
+
+        expected_min = {
+            "mean": 349.53354434499295,
+            "sum": 50332.830385678986,
+            "min": 50.39387578315866,
+            "max": 761.0313042971973,
+        }
+        assert_result(r["min"], expected_min, self.df_buildings, exact=False)
+
+        expected_max = {
+            "mean": 835.1307128394886,
+            "sum": 120258.82264888636,
+            "min": 50.49413435416841,
+            "max": 2127.7522277389035,
+        }
+        assert_result(r["max"], expected_max, self.df_buildings, exact=False)
+
+        expected_sum = {
+            "mean": 1762.128306166348,
+            "sum": 253746.47608795413,
+            "min": 151.32137188749948,
+            "max": 3561.79872409777,
+        }
+        assert_result(r["sum"], expected_sum, self.df_buildings, exact=False)
+
+    def test_describe_quantile(self):
+        graph = Graph.build_knn(self.df_buildings.centroid, k=15)
+        area = self.df_buildings.area
+        r = mm.describe(area, graph, q=(25, 75))
+
+        expected_mean = {
+            "mean": 601.6960154385389,
+            "sum": 86644.2262231496,
+            "min": 250.25984637364323,
+            "max": 901.0028506943196,
+        }
+        assert_result(r["mean"], expected_mean, self.df_buildings, exact=False)
+
+    def test_describe_mode(self):
+        corners = mm.corners(self.df_buildings)
+        r = mm.describe(corners, self.graph, include_mode=True)
+
+        expected = {
+            "mean": 6.152777777777778,
+            "sum": 886,
+            "min": 4,
+            "max": 17,
+        }
+        assert_result(r["mode"], expected, self.df_buildings, exact=False)
+
+    def test_describe_quantile_mode(self):
+        graph = Graph.build_knn(self.df_buildings.centroid, k=15)
+        corners = mm.corners(self.df_buildings)
+        r = mm.describe(corners, graph, q=(25, 75), include_mode=True)
+
+        expected = {
+            "mean": 6.958333333333333,
+            "sum": 1002.0,
+            "min": 4.0,
+            "max": 12,
+        }
+        assert_result(r["mode"], expected, self.df_buildings, exact=False)
+
+    def test_describe_array(self):
+        area = self.df_buildings.area
+        r = mm.describe(area, self.graph)
+        r2 = mm.describe(area.values, self.graph)
+
+        assert_frame_equal(r, r2)

From 7c04fa0aa00ff9369348d6000ea630591a1ce8dd Mon Sep 17 00:00:00 2001
From: Martin Fleischmann <martin@martinfleischmann.net>
Date: Wed, 24 Apr 2024 10:02:17 +0200
Subject: [PATCH 09/11] skip mode tests on oldest

---
 momepy/functional/tests/test_diversity.py | 6 ++++++
 1 file changed, 6 insertions(+)

diff --git a/momepy/functional/tests/test_diversity.py b/momepy/functional/tests/test_diversity.py
index 4bc63a5d..4da03822 100644
--- a/momepy/functional/tests/test_diversity.py
+++ b/momepy/functional/tests/test_diversity.py
@@ -1,11 +1,15 @@
 import geopandas as gpd
+import pytest
 from libpysal.graph import Graph
+from packaging.version import Version
 from pandas.testing import assert_frame_equal
 
 import momepy as mm
 
 from ._testing import assert_result
 
+GPD_013 = Version(gpd.__version__) >= Version("0.13")
+
 
 class TestDistribution:
     def setup_method(self):
@@ -78,6 +82,7 @@ def test_describe_quantile(self):
         }
         assert_result(r["mean"], expected_mean, self.df_buildings, exact=False)
 
+    @pytest.mark.skipif(not GPD_013, reason="get_coordinates() not available")
     def test_describe_mode(self):
         corners = mm.corners(self.df_buildings)
         r = mm.describe(corners, self.graph, include_mode=True)
@@ -90,6 +95,7 @@ def test_describe_mode(self):
         }
         assert_result(r["mode"], expected, self.df_buildings, exact=False)
 
+    @pytest.mark.skipif(not GPD_013, reason="get_coordinates() not available")
     def test_describe_quantile_mode(self):
         graph = Graph.build_knn(self.df_buildings.centroid, k=15)
         corners = mm.corners(self.df_buildings)

From 46e6978e4e712d1730c9564cf34e1d0dc0e2ba77 Mon Sep 17 00:00:00 2001
From: Martin Fleischmann <martin@martinfleischmann.net>
Date: Wed, 24 Apr 2024 19:06:55 +0200
Subject: [PATCH 10/11] use agg

---
 momepy/functional/_diversity.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/momepy/functional/_diversity.py b/momepy/functional/_diversity.py
index 93836e74..deac7176 100644
--- a/momepy/functional/_diversity.py
+++ b/momepy/functional/_diversity.py
@@ -75,7 +75,7 @@ def _describe(values, q, include_mode=False):
         if include_mode:
             stat_["mode"] = grouper.agg(lambda x: stats.mode(x, keepdims=False)[0])
     else:
-        agg = grouper.apply(_describe, q=q, include_mode=include_mode)
+        agg = grouper.agg(_describe, q=q, include_mode=include_mode)
         stat_ = DataFrame(zip(*agg, strict=True)).T
         cols = ["mean", "median", "std", "min", "max", "sum"]
         if include_mode:

From fdf600d27e3fa15cbc70d1d131bdc317f04b86dd Mon Sep 17 00:00:00 2001
From: Martin Fleischmann <martin@martinfleischmann.net>
Date: Wed, 24 Apr 2024 19:07:04 +0200
Subject: [PATCH 11/11] conftest

---
 momepy/functional/tests/{_testing.py => conftest.py} | 0
 momepy/functional/tests/test_distribution.py         | 2 +-
 momepy/functional/tests/test_diversity.py            | 2 +-
 momepy/functional/tests/test_shape.py                | 2 +-
 4 files changed, 3 insertions(+), 3 deletions(-)
 rename momepy/functional/tests/{_testing.py => conftest.py} (100%)

diff --git a/momepy/functional/tests/_testing.py b/momepy/functional/tests/conftest.py
similarity index 100%
rename from momepy/functional/tests/_testing.py
rename to momepy/functional/tests/conftest.py
diff --git a/momepy/functional/tests/test_distribution.py b/momepy/functional/tests/test_distribution.py
index 76993ec0..162c8f46 100644
--- a/momepy/functional/tests/test_distribution.py
+++ b/momepy/functional/tests/test_distribution.py
@@ -4,7 +4,7 @@
 
 import momepy as mm
 
-from ._testing import assert_result
+from .conftest import assert_result
 
 
 class TestDistribution:
diff --git a/momepy/functional/tests/test_diversity.py b/momepy/functional/tests/test_diversity.py
index 4da03822..2fe06319 100644
--- a/momepy/functional/tests/test_diversity.py
+++ b/momepy/functional/tests/test_diversity.py
@@ -6,7 +6,7 @@
 
 import momepy as mm
 
-from ._testing import assert_result
+from .conftest import assert_result
 
 GPD_013 = Version(gpd.__version__) >= Version("0.13")
 
diff --git a/momepy/functional/tests/test_shape.py b/momepy/functional/tests/test_shape.py
index b79d199a..85d1d97b 100644
--- a/momepy/functional/tests/test_shape.py
+++ b/momepy/functional/tests/test_shape.py
@@ -7,7 +7,7 @@
 
 import momepy as mm
 
-from ._testing import assert_result
+from .conftest import assert_result
 
 GPD_013 = Version(gpd.__version__) >= Version("0.13")