2 tick minimum also for logscale (#372)

* add test for minimum of 2 ticks for logscale

* bump version to 2.8.2

* create `_set_logticks` method that ensures at least 2 ticks per log axis, unfortunately appears to have to be called after every call to `plot_2d`

* try to fix `test_BarPlot` which actually should be unrelated to recent changes but for some reason acts up

* try alternative fix for `test_BarPlot` making use of `iloc`

* Revert "try alternative fix for `test_BarPlot` making use of `iloc`"

This reverts commit 50afec0.

* Revert "try to fix `test_BarPlot` which actually should be unrelated to recent changes but for some reason acts up"

This reverts commit eba68c8.

* remove comparison of bar yticks with barh xticks, since this test is not robust across different figure sizes, where often the yaxis is shorter than the xaxis, which caused failures in some CI settings

* remove `rcParams` modification from `test_logscale_ticks`, as this messes with other tests, make the test work with default settings instead

* Revert "remove comparison of bar yticks with barh xticks, since this test is not robust across different figure sizes, where often the yaxis is shorter than the xaxis, which caused failures in some CI settings"

This reverts commit 3bcc92d.

README.rst

@@ -2,7 +2,7 @@
 anesthetic: nested sampling post-processing
 ===========================================
 :Authors: Will Handley and Lukas Hergt
-:Version: 2.8.3
+:Version: 2.8.4
 :Homepage: https://github.com/handley-lab/anesthetic
 :Documentation: http://anesthetic.readthedocs.io/
 

anesthetic/_version.py

@@ -1 +1 @@
-__version__ = '2.8.3'
+__version__ = '2.8.4'

anesthetic/plot.py

@@ -18,7 +18,7 @@
 from matplotlib.axes import Axes
 import matplotlib.cbook as cbook
 import matplotlib.lines as mlines
-from matplotlib.ticker import MaxNLocator, AutoMinorLocator
+from matplotlib.ticker import MaxNLocator, AutoMinorLocator, LogLocator
 from matplotlib.colors import LinearSegmentedColormap
 from matplotlib.transforms import Affine2D
 from anesthetic.utils import nest_level
@@ -388,6 +388,15 @@ def _set_scale(self):
                     if y in self._logy:
                         ax.set_yscale('log')
 
+    def _set_logticks(self):
+        for y, rows in self.iterrows():
+            for x, ax in rows.items():
+                if ax is not None:
+                    if x in self._logx:
+                        ax.xaxis.set_major_locator(LogLocator(numticks=3))
+                    if y in self._logy:
+                        ax.yaxis.set_major_locator(LogLocator(numticks=3))
+
     @staticmethod
     def _set_labels(axes, labels, **kwargs):
         all_params = list(axes.columns) + list(axes.index)

anesthetic/samples.py

@@ -355,6 +355,8 @@ def plot_2d(self, axes=None, *args, **kwargs):
                         else:
                             ax.plot([], [])
 
+        axes._set_logticks()
+
         return axes
 
     plot_2d_default_kinds = {

tests/test_samples.py

@@ -514,6 +514,25 @@ def test_plot_logscale_2d(kind):
                     assert ax.twin.get_yscale() == 'linear'
 
 
+def test_logscale_ticks():
+    np.random.seed(42)
+    ndim = 5
+    data = np.exp(10 * np.random.randn(200, ndim))
+    params = [f'a{i}' for i in range(ndim)]
+    fig, axes = make_2d_axes(params, logx=params, logy=params, upper=False)
+    samples = Samples(data, columns=params)
+    samples.plot_2d(axes)
+    for _, col in axes.iterrows():
+        for _, ax in col.items():
+            if ax is not None:
+                xlims = ax.get_xlim()
+                xticks = ax.get_xticks()
+                assert np.sum((xticks > xlims[0]) & (xticks < xlims[1])) > 1
+                ylims = ax.get_ylim()
+                yticks = ax.get_yticks()
+                assert np.sum((yticks > ylims[0]) & (yticks < ylims[1])) > 1
+
+
 @pytest.mark.parametrize('k', ['hist_1d', 'hist'])
 @pytest.mark.parametrize('b', ['scott', 10, np.logspace(-3, 0, 20)])
 @pytest.mark.parametrize('r', [None, (1e-5, 1)])