035quater

condarecipe/larray/meta.yaml

@@ -28,6 +28,11 @@ requirements:
 test:
   requires:
     - pytest
+    - pytables
+    - matplotlib-base
+    - openpyxl
+    - xlsxwriter
+    - pydantic >=2
 
   imports:
     - larray

larray/core/array.py

@@ -7330,7 +7330,7 @@ def plot(self) -> PlotObject:
 
         Line plot with grid and a title, saved in a file
 
-        >>> arr.plot(grid=True, title='line plot', filepath='my_file.png')
+        >>> arr.plot(grid=True, title='line plot', filepath='my_file.png')       # doctest: +SKIP
 
         2 bar plots (one for each gender) sharing the same y axis, which makes sub plots
         easier to compare. By default sub plots are independant of each other and the axes
@@ -7352,7 +7352,7 @@ def plot(self) -> PlotObject:
 
         Create a figure containing 2 x 2 graphs
 
-        >>> import matplotlib.pyplot as plt
+        >>> import matplotlib.pyplot as plt                                      # doctest: +SKIP
         >>> # see matplotlib.pyplot.subplots documentation for more details
         >>> fig, ax = plt.subplots(2, 2, figsize=(10, 8), tight_layout=True)     # doctest: +SKIP
         >>> # line plot with 2 curves (Males and Females) in the top left corner (0, 0)

larray/tests/common.py

@@ -8,6 +8,11 @@
 import numpy as np
 from numpy.lib import NumpyVersion
 import pandas as pd
+
+try:
+    import matplotlib
+except ImportError:
+    matplotlib = None
 try:
     import xlwings as xw
 except ImportError:
@@ -141,11 +146,26 @@ def meta():
                     score=9.70, date=pd.Timestamp(dt.datetime(1970, 3, 21)))
 
 
-needs_pytables = pytest.mark.skipif(tables is None, reason="pytables is required for this test")
-needs_xlwings = pytest.mark.skipif(SKIP_EXCEL_TESTS or xw is None, reason="xlwings is required for this test")
-needs_openpyxl = pytest.mark.skipif(SKIP_EXCEL_TESTS or openpyxl is None, reason="openpyxl is required for this test")
-needs_xlsxwriter = pytest.mark.skipif(SKIP_EXCEL_TESTS or xlsxwriter is None,
-                                      reason="xlsxwriter is required for this test")
+needs_matplotlib = (
+    pytest.mark.skipif(matplotlib is None,
+                       reason="matplotlib is required for this test")
+)
+needs_pytables = (
+    pytest.mark.skipif(tables is None,
+                       reason="pytables is required for this test")
+)
+needs_xlwings = (
+    pytest.mark.skipif(SKIP_EXCEL_TESTS or xw is None,
+                       reason="xlwings is required for this test")
+)
+needs_openpyxl = (
+    pytest.mark.skipif(SKIP_EXCEL_TESTS or openpyxl is None,
+                       reason="openpyxl is required for this test")
+)
+needs_xlsxwriter = (
+    pytest.mark.skipif(SKIP_EXCEL_TESTS or xlsxwriter is None,
+                       reason="xlsxwriter is required for this test")
+)
 
 
 @contextmanager

larray/tests/test_array.py

@@ -1,24 +1,28 @@
 import os
 import sys
+from io import StringIO
 
 import pytest
 import numpy as np
 import pandas as pd
-import matplotlib.figure
-
-from io import StringIO
 
-from larray.tests.common import (meta, inputpath,
-                                 assert_larray_equal, assert_larray_nan_equal, assert_larray_equiv,
-                                 assert_nparray_equal, assert_nparray_nan_equal,
-                                 needs_xlwings, needs_pytables, needs_xlsxwriter, needs_openpyxl, NUMPY2,
-                                 must_warn, must_raise)
-from larray import (Array, LArray, Axis, AxisCollection, LGroup, IGroup, Metadata,
-                    zeros, zeros_like, ndtest, empty, ones, full, eye, diag, stack, sequence,
-                    asarray, union, clip, exp, where, X, mean, inf, nan, isnan, round,
-                    read_hdf, read_csv, read_eurostat, read_excel, open_excel,
-                    from_lists, from_string, from_frame, from_series,
-                    zip_array_values, zip_array_items, nan_to_num)
+from larray.tests.common import (
+    meta, inputpath,
+    assert_larray_equal, assert_larray_nan_equal, assert_larray_equiv,
+    assert_nparray_equal, assert_nparray_nan_equal,
+    needs_xlwings, needs_pytables, needs_xlsxwriter, needs_openpyxl,
+    needs_matplotlib,
+    NUMPY2,
+    must_warn, must_raise
+)
+from larray import (
+    Array, LArray, Axis, AxisCollection, LGroup, IGroup, Metadata,
+    zeros, zeros_like, ndtest, empty, ones, full, eye, diag, stack, sequence,
+    asarray, union, clip, exp, where, X, mean, inf, nan, isnan, round,
+    read_hdf, read_csv, read_eurostat, read_excel, open_excel,
+    from_lists, from_string, from_frame, from_series,
+    zip_array_values, zip_array_items, nan_to_num
+)
 from larray.core.axis import (
     _to_ticks, _to_key, _retarget_warn_msg, _group_as_aggregated_label_msg
 )
@@ -5568,7 +5572,9 @@ def test_broadcast_with():
     assert_larray_equiv(b, a2)
 
 
+@needs_matplotlib
 def test_plot():
+    import matplotlib.figure
     import matplotlib.pyplot as plt
 
     fig, ax = plt.subplots()  # doctest: +SKIP

larray/util/plot.py

@@ -1,37 +1,40 @@
 import numpy as np
-from matplotlib.ticker import MaxNLocator
 
+try:
+    from matplotlib.ticker import MaxNLocator
 
-class MaxNMultipleWithOffsetLocator(MaxNLocator):
-    def __init__(self, nbins=None, offset=0.5, **kwargs):
-        super().__init__(nbins, **kwargs)
-        self.offset = offset
+    class MaxNMultipleWithOffsetLocator(MaxNLocator):
+        def __init__(self, nbins=None, offset=0.5, **kwargs):
+            super().__init__(nbins, **kwargs)
+            self.offset = offset
 
-    def tick_values(self, vmin, vmax):
-        # matplotlib calls them vmin and vmax but they are actually the limits and vmin can be > vmax
-        invert = vmin > vmax
-        if invert:
-            vmin, vmax = vmax, vmin
+        def tick_values(self, vmin, vmax):
+            # matplotlib calls them vmin and vmax but they are actually the limits and vmin can be > vmax
+            invert = vmin > vmax
+            if invert:
+                vmin, vmax = vmax, vmin
 
-        max_desired_ticks = self._nbins
-        # not + 1 because we place ticks in the middle
-        num_ticks = vmax - vmin
-        desired_numticks = min(num_ticks, max_desired_ticks)
-        if desired_numticks < num_ticks:
-            step = np.ceil(num_ticks / desired_numticks)
-        else:
-            step = 1
-        vmin = int(vmin)
-        vmax = int(vmax)
-        # when we have an offset, we do not add 1 to vmax because we place ticks in the middle
-        # (by adding the offset), and would result in the last "tick" being outside the limits
-        stop = vmax + 1 if self.offset == 0 else vmax
-        new_ticks = np.arange(vmin, stop, step)
-        if invert:
-            new_ticks = new_ticks[::-1]
-        return new_ticks + self.offset
+            max_desired_ticks = self._nbins
+            # not + 1 because we place ticks in the middle
+            num_ticks = vmax - vmin
+            desired_numticks = min(num_ticks, max_desired_ticks)
+            if desired_numticks < num_ticks:
+                step = np.ceil(num_ticks / desired_numticks)
+            else:
+                step = 1
+            vmin = int(vmin)
+            vmax = int(vmax)
+            # when we have an offset, we do not add 1 to vmax because we place ticks in the middle
+            # (by adding the offset), and would result in the last "tick" being outside the limits
+            stop = vmax + 1 if self.offset == 0 else vmax
+            new_ticks = np.arange(vmin, stop, step)
+            if invert:
+                new_ticks = new_ticks[::-1]
+            return new_ticks + self.offset
 
-    def __call__(self):
-        """Return the locations of the ticks."""
-        vmin, vmax = self.axis.get_view_interval()
-        return self.tick_values(vmin, vmax)
+        def __call__(self):
+            """Return the locations of the ticks."""
+            vmin, vmax = self.axis.get_view_interval()
+            return self.tick_values(vmin, vmax)
+except ImportError:
+    pass