Changes for pandas 2.1

.github/workflows/CI.yaml

@@ -40,7 +40,7 @@ jobs:
       - uses: actions/checkout@v2
       - uses: actions/setup-python@v2
         with:
-          python-version: '3.8'
+          python-version: '3.11'
       - name: Upgrade pip and install doc requirements
         run: |
           python -m pip install --upgrade pip
@@ -56,7 +56,7 @@ jobs:
     strategy:
       matrix:
         os: [ubuntu-latest]
-        python-version: ['3.8', '3.9', '3.10', '3.11']
+        python-version: ['3.9', '3.10', '3.11']
         extras: [true, false]
         include:
           - os: macos-latest
@@ -94,7 +94,7 @@ jobs:
     strategy:
       matrix:
         os: [ubuntu-latest]
-        python-version: ['3.8', '3.9', '3.10', '3.11']
+        python-version: ['3.9', '3.10', '3.11']
         include:
           - os: macos-latest
             python-version: '3.11'
@@ -126,10 +126,10 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v3
-      - name: Set up Python 3.8
+      - name: Set up Python 3.11
         uses: actions/setup-python@v4
         with:
-          python-version: 3.8
+          python-version: 3.11
       - name: Install pypa/build
         run: python -m pip install build --user
       - name: Build a binary wheel and a source tarball
@@ -146,10 +146,10 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v3
-      - name: Set up Python 3.8
+      - name: Set up Python 3.9
         uses: actions/setup-python@v4
         with:
-          python-version: 3.8
+          python-version: 3.9
 
       - name: Install dependencies
         run: |

.github/workflows/build.yaml

@@ -35,10 +35,10 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v3
-      - name: Set up Python 3.8
+      - name: Set up Python 3.11
         uses: actions/setup-python@v4
         with:
-          python-version: 3.8
+          python-version: 3.11
       - name: Install pypa/build
         run: python -m pip install build --user
       - name: Build a binary wheel and a source tarball
@@ -53,10 +53,10 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v3
-      - name: Set up Python 3.8
+      - name: Set up Python 3.11
         uses: actions/setup-python@v4
         with:
-          python-version: 3.8
+          python-version: 3.11
       - name: Install dependencies
         run: |
           python -m pip install --upgrade pip

README.rst

@@ -2,7 +2,7 @@
 anesthetic: nested sampling post-processing
 ===========================================
 :Authors: Will Handley and Lukas Hergt
-:Version: 2.3.1
+:Version: 2.4.0
 :Homepage: https://github.com/handley-lab/anesthetic
 :Documentation: http://anesthetic.readthedocs.io/
 

anesthetic/_version.py

@@ -1 +1 @@
-__version__ = '2.3.1'
+__version__ = '2.4.0'

anesthetic/labelled_pandas.py

@@ -117,7 +117,8 @@ def get_labels_map(self, axis=0, fill=True):
                 labels_map = index.to_frame().droplevel(labs)[labs]
                 if fill:
                     replacement = labels_map.loc[labels_map == ''].index
-                    labels_map.loc[labels_map == ''] = replacement
+                    labels_map.loc[labels_map == ''] = replacement.astype(
+                        labels_map.loc[labels_map != ''].dtype)
                 return labels_map
             else:
                 return index.to_series()

anesthetic/plotting/_core.py

@@ -15,7 +15,8 @@ def _process_docstring(doc):
         "                     with fastkde package (DataFrame only)\n"
         "    - 'scatter_2d' : 2d scatter plot (DataFrame only)\n"
         )
-    return doc[:i] + e + doc[i:]
+    j = doc.find('    Examples')
+    return doc[:i] + e + doc[i:j]
 
 
 class PlotAccessor(_PlotAccessor):

anesthetic/weighted_pandas.py

@@ -207,7 +207,7 @@ def set_weights(self, weights, axis=0, inplace=False, level=None):
     def _rand(self, axis=0):
         """Random number for consistent compression."""
         seed = hash_pandas_object(self._get_axis(axis)).sum() % 2**32
-        with temporary_seed(seed):
+        with temporary_seed(int(seed)):
             return np.random.rand(self.shape[axis])
 
     def reset_index(self, level=None, drop=False, inplace=False,

docs/source/anesthetic.read.rst

@@ -40,6 +40,7 @@ anesthetic.read.hdf module
 .. automodule:: anesthetic.read.hdf
    :members:
    :undoc-members:
+   :show-inheritance:
 
 
 anesthetic.read.multinest module
@@ -51,6 +52,15 @@ anesthetic.read.multinest module
    :show-inheritance:
 
 
+anesthetic.read.nestedfit module
+--------------------------------
+
+.. automodule:: anesthetic.read.nestedfit
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
+
 anesthetic.read.polychord module
 --------------------------------
 
@@ -60,3 +70,12 @@ anesthetic.read.polychord module
    :show-inheritance:
 
 
+anesthetic.read.ultranest module
+--------------------------------
+
+.. automodule:: anesthetic.read.ultranest
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
+

docs/source/anesthetic.rst

@@ -108,5 +108,6 @@ anesthetic.weighted\_pandas module
 .. automodule:: anesthetic.weighted_pandas
    :members:
    :undoc-members:
+   :show-inheritance:
 
 

pyproject.toml

@@ -33,7 +33,7 @@ requires-python = ">=3.8"
 dependencies = [
     "scipy",
     "numpy",
-    "pandas~=2.0.0",
+    "pandas~=2.1.0",
     "matplotlib>=3.6.1",
 ]
 classifiers = [

tests/test_gui.py

@@ -1,13 +1,14 @@
+import matplotlib.pyplot as plt
 import anesthetic.examples._matplotlib_agg  # noqa: F401
 from anesthetic import read_chains
 import pytest
-import pandas._testing as tm
 from utils import skipif_no_h5py
 
 
 @pytest.fixture(autouse=True)
 def close_figures_on_teardown():
-    tm.close()
+    yield
+    plt.close("all")
 
 
 @pytest.mark.parametrize('root', ["./tests/example_data/pc",

tests/test_plot.py

@@ -9,7 +9,6 @@
                              scatter_plot_2d, quantile_plot_interval,
                              basic_cmap, AxesSeries, AxesDataFrame)
 from numpy.testing import assert_array_equal
-import pandas._testing as tm
 
 from matplotlib.axes import SubplotBase
 from matplotlib.contour import ContourSet
@@ -25,7 +24,8 @@
 
 @pytest.fixture(autouse=True)
 def close_figures_on_teardown():
-    tm.close()
+    yield
+    plt.close("all")
 
 
 def test_AxesObjects():

tests/test_reader.py

@@ -3,6 +3,7 @@
 import pytest
 import numpy as np
 from numpy.testing import assert_array_equal, assert_array_almost_equal
+import matplotlib.pyplot as plt
 from anesthetic.testing import assert_frame_equal
 from anesthetic import MCMCSamples, NestedSamples
 from anesthetic import read_chains
@@ -12,14 +13,14 @@
 from anesthetic.read.multinest import read_multinest
 from anesthetic.read.ultranest import read_ultranest
 from anesthetic.read.nestedfit import read_nestedfit
-import pandas._testing as tm
 from anesthetic.read.hdf import HDFStore, read_hdf
 from utils import pytables_mark_xfail, h5py_mark_xfail, getdist_mark_skip
 
 
 @pytest.fixture(autouse=True)
 def close_figures_on_teardown():
-    tm.close()
+    yield
+    plt.close("all")
 
 
 def test_read_getdist():

tests/test_samples.py

@@ -18,15 +18,15 @@
 from numpy.testing import (assert_array_equal, assert_array_almost_equal,
                            assert_array_less, assert_allclose)
 from pandas.testing import assert_frame_equal
-import pandas._testing as tm
 from matplotlib.colors import to_hex
 from scipy.stats import ks_2samp, kstest, norm
 from utils import skipif_no_fastkde, astropy_mark_xfail, fastkde_mark_skip
 
 
 @pytest.fixture(autouse=True)
 def close_figures_on_teardown():
-    tm.close()
+    yield
+    plt.close("all")
 
 
 def test_build_samples():
@@ -1517,47 +1517,47 @@ def test_groupby_stats():
         if 'chain' not in col:
             for chain in [1, 2]:
                 mask = mcmc.chain == chain
-                assert_allclose(mcmc.loc[mask, col].mean(),
+                assert_allclose(mcmc.loc[mask][col].mean(),
                                 chains[col].mean().loc[chain])
-                assert_allclose(mcmc.loc[mask, col].std(),
+                assert_allclose(mcmc.loc[mask][col].std(),
                                 chains[col].std().loc[chain])
-                assert_allclose(mcmc.loc[mask, col].median(),
+                assert_allclose(mcmc.loc[mask][col].median(),
                                 chains[col].median().loc[chain])
-                assert_allclose(mcmc.loc[mask, col].var(),
+                assert_allclose(mcmc.loc[mask][col].var(),
                                 chains[col].var().loc[chain])
-                assert_allclose(mcmc.loc[mask, col].kurt(),
+                assert_allclose(mcmc.loc[mask][col].kurt(),
                                 chains[col].kurt().loc[chain])
-                assert_allclose(mcmc.loc[mask, col].kurtosis(),
+                assert_allclose(mcmc.loc[mask][col].kurtosis(),
                                 chains[col].kurtosis().loc[chain])
-                assert_allclose(mcmc.loc[mask, col].skew(),
+                assert_allclose(mcmc.loc[mask][col].skew(),
                                 chains[col].skew().loc[chain])
-                assert_allclose(mcmc.loc[mask, col].sem(),
+                assert_allclose(mcmc.loc[mask][col].sem(),
                                 chains[col].sem().loc[chain])
-                assert_allclose(mcmc.loc[mask, col].cov(mcmc.loc[mask, col]),
-                                chains[col].cov(mcmc.loc[mask, col])
+                assert_allclose(mcmc.loc[mask][col].cov(mcmc.loc[mask][col]),
+                                chains[col].cov(mcmc.loc[mask][col])
                                 .loc[chain])
-                assert_allclose(mcmc.loc[mask, col].corr(mcmc.loc[mask, col]),
-                                chains[col].corr(mcmc.loc[mask, col])
+                assert_allclose(mcmc.loc[mask][col].corr(mcmc.loc[mask][col]),
+                                chains[col].corr(mcmc.loc[mask][col])
                                 .loc[chain])
                 q = np.random.rand()
-                assert_allclose(mcmc.loc[mask, col].quantile(q),
+                assert_allclose(mcmc.loc[mask][col].quantile(q),
                                 chains[col].quantile(q).loc[chain])
 
                 group = chains[col].get_group(chain)
-                assert_allclose(mcmc.loc[mask, col].mean(), group.mean())
-                assert_allclose(mcmc.loc[mask, col].std(), group.std())
-                assert_allclose(mcmc.loc[mask, col].median(), group.median())
-                assert_allclose(mcmc.loc[mask, col].var(), group.var())
-                assert_allclose(mcmc.loc[mask, col].kurt(), group.kurt())
-                assert_allclose(mcmc.loc[mask, col].kurtosis(),
+                assert_allclose(mcmc.loc[mask][col].mean(), group.mean())
+                assert_allclose(mcmc.loc[mask][col].std(), group.std())
+                assert_allclose(mcmc.loc[mask][col].median(), group.median())
+                assert_allclose(mcmc.loc[mask][col].var(), group.var())
+                assert_allclose(mcmc.loc[mask][col].kurt(), group.kurt())
+                assert_allclose(mcmc.loc[mask][col].kurtosis(),
                                 group.kurtosis())
-                assert_allclose(mcmc.loc[mask, col].skew(), group.skew())
-                assert_allclose(mcmc.loc[mask, col].sem(), group.sem())
+                assert_allclose(mcmc.loc[mask][col].skew(), group.skew())
+                assert_allclose(mcmc.loc[mask][col].sem(), group.sem())
 
-                assert_allclose(mcmc.loc[mask, col].cov(mcmc.loc[mask, col]),
-                                group.cov(mcmc.loc[mask, col]))
-                assert_allclose(mcmc.loc[mask, col].corr(mcmc.loc[mask, col]),
-                                group.corr(mcmc.loc[mask, col]))
+                assert_allclose(mcmc.loc[mask][col].cov(mcmc.loc[mask][col]),
+                                group.cov(mcmc.loc[mask][col]))
+                assert_allclose(mcmc.loc[mask][col].corr(mcmc.loc[mask][col]),
+                                group.corr(mcmc.loc[mask][col]))
 
     sample = chains.sample(5)
     assert len(sample) == 10

tests/test_scripts.py

@@ -1,12 +1,13 @@
+import matplotlib.pyplot as plt
 from anesthetic.scripts import gui
 from bin.utils import unit_incremented
 import pytest
-import pandas._testing as tm
 
 
 @pytest.fixture(autouse=True)
 def close_figures_on_teardown():
-    tm.close()
+    yield
+    plt.close("all")
 
 
 def test_gui():

tests/test_weighted_pandas.py

@@ -11,12 +11,12 @@
 from pandas.plotting._matplotlib.misc import (
     scatter_matrix as orig_scatter_matrix
 )
-import pandas._testing as tm
 
 
 @pytest.fixture(autouse=True)
 def close_figures_on_teardown():
-    tm.close()
+    yield
+    plt.close("all")
 
 
 @pytest.fixture