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Use mapclassify instead of PySAL due to change of PySAL structure. (#872)

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Martin Fleischmann authored and Joris Van den Bossche committed 2018-12-08 22:36:45 +01:00
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commit f4fa69eae0
13 files changed
+56 -46
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ci/travis/27-dev.yaml
+1 -1
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@@ -19,7 +19,6 @@ dependencies:
- rtree
- matplotlib
- descartes
- pysal
#- geopy
- SQLalchemy
- psycopg2
@@ -28,3 +27,4 @@ dependencies:
- git+https://github.com/pydata/pandas.git
- codecov
- geopy
- mapclassify==1.0.1
ci/travis/27-latest-conda-forge.yaml
+1 -1
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@@ -18,7 +18,7 @@ dependencies:
- rtree
- matplotlib
- descartes
- pysal
- mapclassify==1.0.1
#- geopy
- SQLalchemy
- psycopg2
ci/travis/27-latest-defaults.yaml
+1 -1
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@@ -18,7 +18,6 @@ dependencies:
- rtree
- matplotlib
- descartes
- pysal
#- geopy
- SQLalchemy
- psycopg2
@@ -26,3 +25,4 @@ dependencies:
- pip:
- codecov
- geopy
- mapclassify==1.0.1
ci/travis/27-pd020.yaml
+1 -1
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@@ -20,8 +20,8 @@ dependencies:
- rtree
- matplotlib==2.0.2
- descartes
- pysal
- geopy
- SQLalchemy
- psycopg2
- libspatialite
- mapclassify==1.0.1
ci/travis/35-minimal.yaml
+1 -1
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@@ -18,7 +18,7 @@ dependencies:
- rtree
- matplotlib==1.5.3
- descartes
- pysal
- mapclassify
- geopy
- SQLalchemy
- psycopg2
ci/travis/36-pd020.yaml
+1 -1
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@@ -17,7 +17,7 @@ dependencies:
- rtree
- matplotlib==1.5.3
- descartes
- pysal
- mapclassify
- geopy
- SQLalchemy
- psycopg2
ci/travis/36-pd022.yaml
+1 -1
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@@ -17,7 +17,6 @@ dependencies:
- rtree
- matplotlib==2.0.2
- descartes
- pysal
#- geopy
- SQLalchemy
- psycopg2
@@ -25,3 +24,4 @@ dependencies:
- pip:
- codecov
- geopy
- mapclassify
ci/travis/37-dev.yaml
+1 -1
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@@ -18,7 +18,6 @@ dependencies:
- rtree
- matplotlib
- descartes
- pysal
#- geopy
- SQLalchemy
- psycopg2
@@ -28,3 +27,4 @@ dependencies:
- git+https://github.com/pydata/pandas.git
- codecov
- geopy
- mapclassify
ci/travis/37-latest-conda-forge.yaml
+1 -1
View File
@@ -17,7 +17,7 @@ dependencies:
- rtree
- matplotlib
- descartes
- pysal
- mapclassify
- geopy
- SQLalchemy
- psycopg2
ci/travis/37-latest-defaults.yaml
+1 -1
View File
@@ -17,7 +17,6 @@ dependencies:
- rtree
- matplotlib
- descartes
- pysal
#- geopy
- SQLalchemy
- psycopg2
@@ -25,3 +24,4 @@ dependencies:
- pip:
- codecov
- geopy
- mapclassify
geopandas/plotting.py
+35 -23
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@@ -26,7 +26,7 @@ def _flatten_multi_geoms(geoms, colors=None):
colors = [None] * len(geoms)
components, component_colors = [], []
if not geoms.geom_type.str.startswith('Multi').any():
return geoms, colors
@@ -349,10 +349,10 @@ def plot_dataframe(df, column=None, cmap=None, color=None, ax=None,
legend : bool (default False)
Plot a legend. Ignored if no `column` is given, or if `color` is given.
scheme : str (default None)
Name of a choropleth classification scheme (requires PySAL).
A pysal.esda.mapclassify.Map_Classifier object will be used
under the hood. Supported schemes: 'Equal_interval', 'Quantiles',
'Fisher_Jenks'
Name of a choropleth classification scheme (requires mapclassify).
A mapclassify.Map_Classifier object will be used
under the hood. Supported schemes: 'Quantiles',
'Equal_Interval', 'Fisher_Jenks', 'Fisher_Jenks_Sampled'
k : int (default 5)
Number of classes (ignored if scheme is None)
vmin : None or float (default None)
@@ -445,7 +445,7 @@ def plot_dataframe(df, column=None, cmap=None, color=None, ax=None,
values = np.array([valuemap[k] for k in values])
if scheme is not None:
binning = __pysal_choro(values, scheme, k=k)
binning = _mapclassify_choro(values, scheme, k=k)
# set categorical to True for creating the legend
categorical = True
binedges = [values.min()] + binning.bins.tolist()
@@ -513,17 +513,18 @@ def plot_dataframe(df, column=None, cmap=None, color=None, ax=None,
return ax
def __pysal_choro(values, scheme, k=5):
def _mapclassify_choro(values, scheme, k=5):
"""
Wrapper for choropleth schemes from PySAL for use with plot_dataframe
Wrapper for choropleth schemes from mapclassify for use with plot_dataframe
Parameters
----------
values
Series to be plotted
scheme : str
One of pysal.esda.mapclassify classification schemes
Options are 'Equal_interval', 'Quantiles', 'Fisher_Jenks'
One of mapclassify classification schemes
Options are 'Quantiles', 'Equal_Interval', 'Fisher_Jenks',
'Fisher_Jenks_Sampled'
k : int
number of classes (2 <= k <=9)
@@ -535,17 +536,28 @@ def __pysal_choro(values, scheme, k=5):
"""
try:
from pysal.esda.mapclassify import (
Quantiles, Equal_Interval, Fisher_Jenks)
schemes = {}
schemes['equal_interval'] = Equal_Interval
schemes['quantiles'] = Quantiles
schemes['fisher_jenks'] = Fisher_Jenks
scheme = scheme.lower()
if scheme not in schemes:
raise ValueError("Invalid scheme. Scheme must be in the"
" set: %r" % schemes.keys())
binning = schemes[scheme](values, k)
return binning
from mapclassify import (
Quantiles, Equal_Interval, Fisher_Jenks,
Fisher_Jenks_Sampled)
except ImportError:
raise ImportError("PySAL is required to use the 'scheme' keyword")
try:
from mapclassify.api import (
Quantiles, Equal_Interval, Fisher_Jenks,
Fisher_Jenks_Sampled)
except ImportError:
raise ImportError(
"The 'mapclassify' package is required to use the 'scheme' "
"keyword")
schemes = {}
schemes['equal_interval'] = Equal_Interval
schemes['quantiles'] = Quantiles
schemes['fisher_jenks'] = Fisher_Jenks
schemes['fisher_jenks_sampled'] = Fisher_Jenks_Sampled
scheme = scheme.lower()
if scheme not in schemes:
raise ValueError("Invalid scheme. Scheme must be in the"
" set: %r" % schemes.keys())
binning = schemes[scheme](values, k)
return binning
geopandas/tests/test_plotting.py
+10 -12
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@@ -12,6 +12,7 @@ from shapely.affinity import rotate
from shapely.geometry import MultiPolygon, Polygon, LineString, Point, MultiPoint
from geopandas import GeoSeries, GeoDataFrame, read_file
from geopandas.datasets import get_path
import pytest
@@ -386,39 +387,36 @@ class TestNonuniformGeometryPlotting:
assert ax.collections[2].get_sizes() == [10]
class TestPySALPlotting:
class TestMapclassifyPlotting:
@classmethod
def setup_class(cls):
try:
import pysal as ps
except ImportError:
raise pytest.skip("PySAL is not installed")
pth = ps.examples.get_path("columbus.shp")
pytest.importorskip('mapclassify')
pth = get_path('naturalearth_lowres')
cls.df = read_file(pth)
cls.df['NEGATIVES'] = np.linspace(-10, 10, len(cls.df.index))
def test_legend(self):
with warnings.catch_warnings(record=True) as _: # don't print warning
# warning coming from pysal / scipy.stats
ax = self.df.plot(column='CRIME', scheme='QUANTILES', k=3,
# warning coming from scipy.stats
ax = self.df.plot(column='pop_est', scheme='QUANTILES', k=3,
cmap='OrRd', legend=True)
labels = [t.get_text() for t in ax.get_legend().get_texts()]
expected = [u'0.18 - 26.07', u'26.07 - 41.97', u'41.97 - 68.89']
expected = [u'-99.00 - 4579438.67', u'4579438.67 - 16639804.33',
u'16639804.33 - 1338612970.00']
assert labels == expected
def test_negative_legend(self):
ax = self.df.plot(column='NEGATIVES', scheme='FISHER_JENKS', k=3,
cmap='OrRd', legend=True)
labels = [t.get_text() for t in ax.get_legend().get_texts()]
expected = [u'-10.00 - -3.33', u'-3.33 - 3.33', u'3.33 - 10.00']
expected = [u'-10.00 - -3.41', u'-3.41 - 3.30', u'3.30 - 10.00']
assert labels == expected
def test_invalid_scheme(self):
with pytest.raises(ValueError):
scheme = 'invalid_scheme_*#&)(*#'
self.df.plot(column='CRIME', scheme=scheme, k=3,
self.df.plot(column='gdp_md_est', scheme=scheme, k=3,
cmap='OrRd', legend=True)
requirements.test.txt
+1 -1
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@@ -8,4 +8,4 @@ pytest>=3.1.0
pytest-cov
codecov
rtree>=0.8
pysal
mapclassify