clean warnings

getdist/chains.py

@@ -8,7 +8,7 @@
 import logging
 from copy import deepcopy
 from collections import namedtuple
-from typing import Sequence, Any, Optional
+from typing import Sequence, Any, Optional, Union
 
 # whether to write to terminal chain names and burn in details when loaded from file
 print_load_details = True
@@ -747,7 +747,7 @@ def mean_diff(self, paramVec, where=None):
         else:
             return paramVec[where] - self.mean(paramVec, where)
 
-    def mean_diffs(self, pars=None, where=None) -> Sequence:
+    def mean_diffs(self, pars: Union[None, int, Sequence] = None, where=None) -> Sequence:
         """
         Calculates a list of parameter vectors giving distances from parameter means
 
@@ -762,7 +762,6 @@ def mean_diffs(self, pars=None, where=None) -> Sequence:
             means = self.getMeans()
             return [self.samples[:, i] - means[i] for i in range(pars)]
         else:
-            # noinspection PyTypeChecker
             return [self.mean_diff(i, where) for i in pars]
 
     def twoTailLimits(self, paramVec, confidence):

getdist/cobaya_interface.py

@@ -6,7 +6,7 @@
 from numbers import Number
 import numpy as np
 import os
-from collections import Mapping
+from typing import Mapping
 
 # Conventions
 _label = "label"
@@ -152,6 +152,7 @@ def get_info_params(info):
     return info_params_full
 
 
+# noinspection PyUnboundLocalVariable
 def get_range(param_info):
     # Sampled
     if is_sampled_param(param_info):

getdist/mcsamples.py

@@ -5,7 +5,7 @@
 import pickle
 import math
 import time
-from collections import Mapping
+from typing import Mapping
 
 import numpy as np
 from scipy.stats import norm

getdist/paramnames.py

@@ -20,10 +20,9 @@ def makeList(roots):
 def escapeLatex(text):
     if text:
         import matplotlib
-    if text and matplotlib.rcParams['text.usetex']:
-        return text.replace('_', '{\\textunderscore}')
-    else:
-        return text
+        if matplotlib.rcParams['text.usetex']:
+            return text.replace('_', '{\\textunderscore}')
+    return text
 
 
 def mergeRenames(*dicts, **kwargs):

getdist/plots.py

@@ -1,6 +1,6 @@
 import os
 import copy
-from collections import Mapping
+from typing import Mapping
 import matplotlib
 import sys
 import warnings
@@ -30,6 +30,7 @@
 from getdist.matplotlib_ext import BoundedMaxNLocator, SciFuncFormatter
 from getdist._base import _BaseObject
 from types import MappingProxyType
+from typing import Sequence, Union
 
 """Plotting scripts for GetDist outputs"""
 
@@ -1375,7 +1376,7 @@ def _get_list(tag):
 
     def _make_contour_args(self, nroots, **kwargs):
         contour_args = self._make_line_args(nroots, **kwargs)
-        filled = kwargs.get('filled')
+        filled: Union[None, bool, Sequence] = kwargs.get('filled')
         if filled and not isinstance(filled, bool):
             for cont, fill in zip(contour_args, filled):
                 cont['filled'] = fill
@@ -1725,7 +1726,7 @@ def make_figure(self, nplot=1, nx=None, ny=None, xstretch=1.0, ystretch=1.0, sha
         self.subplots[:, :] = None
         return self.plot_col, self.plot_row
 
-    def get_param_array(self, root, params=None, renames=None):
+    def get_param_array(self, root, params: Union[None, str, Sequence] = None, renames: Mapping = None):
         """
         Gets an array of :class:`~.paramnames.ParamInfo` for named params
         in the given `root`.
@@ -2749,6 +2750,7 @@ def add_3d_scatter(self, root, params, color_bar=True, alpha=1, extra_thin=1, sc
         else:
             pts = self.sample_analyser.load_single_samples(root)
             weights = 1
+            mcsamples = None
         names = self.param_names_for_root(root)
         fixed_color = kwargs.get('fixed_color')  # if actually just a plain scatter plot
         samples = []
@@ -2757,7 +2759,7 @@ def add_3d_scatter(self, root, params, color_bar=True, alpha=1, extra_thin=1, sc
                 samples.append(param.getDerived(self._make_param_object(names, pts)))
             else:
                 samples.append(pts[:, names.numberOfName(param.name)])
-        if alpha_samples:
+        if mcsamples:
             # use most samples, but alpha with weight
             from matplotlib.cm import ScalarMappable
             from matplotlib.colors import Normalize, to_rgb

getdist/tests/test_distributions.py

@@ -249,6 +249,7 @@ def compare_method_nsims(g, probs, sizes=(1000, 10000), **kwargs):
 
 def compare_method(probs, nx=2, fname='', **kwargs):
     ny = (len(probs) - 1) // nx + 1
+    # noinspection PyTypeChecker
     fig, axs = plt.subplots(ny, nx, sharex=True, sharey=True, squeeze=False, figsize=(nx * 3, ny * 3))
     for i, prob in enumerate(probs):
         ax = axs.reshape(-1)[i]