DOC/TST: fixed from docstring styles/typos and moved therandom seed t…

…o the setup methods of the tests

statsmodels/graphics/gofplots.py

@@ -197,14 +197,12 @@ def ppplot(self, xlabel=None, ylabel=None, line=None, other=None,
 
         Parameters
         ----------
-        ax : Matplotlib AxesSubplot instance, optional
-            If given, this subplot is used to plot in instead of a new figure
-            being created.
         xlabel, ylabel : str or None, optional
             User-provided lables for the x-axis and y-axis. If None (default),
             other values are used depending on the status of the kwarg `other`.
         line : str {'45', 's', 'r', q'} or None, optional
             Options for the reference line to which the data is compared:
+
             - '45' - 45-degree line
             - 's' - standardized line, the expected order statistics are scaled
               by the standard deviation of the given sample and have the mean
@@ -220,6 +218,9 @@ def ppplot(self, xlabel=None, ylabel=None, line=None, other=None,
             instance. If an array-like object is provided, it will be turned
             into a `ProbPlot` instance using default parameters. If not provided
             (default), the theoretical quantiles are used.
+        ax : Matplotlib AxesSubplot instance, optional
+            If given, this subplot is used to plot in instead of a new figure
+            being created.
         **plotkwargs : additional matplotlib arguments to be passed to the
             `plot` command.
 
@@ -263,16 +264,13 @@ def ppplot(self, xlabel=None, ylabel=None, line=None, other=None,
         return fig
 
     def qqplot(self, xlabel=None, ylabel=None, line=None, other=None,
-                ax=None, **plotkwargs):
+               ax=None, **plotkwargs):
         """
         Q-Q plot of the quantiles of x versus the quantiles/ppf of a
         distribution or the quantiles of another `ProbPlot` instance.
 
         Parameters
         ----------
-        ax : Matplotlib AxesSubplot instance, optional
-            If given, this subplot is used to plot in instead of a new figure
-            being created.
         xlabel, ylabel : str or None, optional
             User-provided lables for the x-axis and y-axis. If None (default),
             other values are used depending on the status of the kwarg `other`.
@@ -293,6 +291,9 @@ def qqplot(self, xlabel=None, ylabel=None, line=None, other=None,
             instance. If an array-like object is provided, it will be turned
             into a `ProbPlot` instance using default parameters. If not provided
             (default), the theoretical quantiles are used.
+        ax : Matplotlib AxesSubplot instance, optional
+            If given, this subplot is used to plot in instead of a new figure
+            being created.
         **plotkwargs : additional matplotlib arguments to be passed to the
             `plot` command.
 
@@ -332,8 +333,8 @@ def qqplot(self, xlabel=None, ylabel=None, line=None, other=None,
 
         return fig
 
-    def probplot(self, ax=None, xlabel=None, ylabel=None, line=None,
-                 exceed=False, **plotkwargs):
+    def probplot(self, xlabel=None, ylabel=None, line=None,
+                 exceed=False, ax=None, **plotkwargs):
         """
         Probability plot of the unscaled quantiles of x versus the
         probabilities of a distibution (not to be confused with a P-P plot).
@@ -343,16 +344,12 @@ def probplot(self, ax=None, xlabel=None, ylabel=None, line=None,
 
         Parameters
         ----------
-        ax : Matplotlib AxesSubplot instance, optional
-            If given, this subplot is used to plot in instead of a new figure
-            being created.
-
         xlabel, ylabel : str or None, optional
             User-provided lables for the x-axis and y-axis. If None (default),
             other values are used depending on the status of the kwarg `other`.
-
         line : str {'45', 's', 'r', q'} or None, optional
             Options for the reference line to which the data is compared:
+
             - '45' - 45-degree line
             - 's' - standardized line, the expected order statistics are scaled
               by the standard deviation of the given sample and have the mean
@@ -362,15 +359,17 @@ def probplot(self, ax=None, xlabel=None, ylabel=None, line=None,
             - None - by default no reference line is added to the plot.
             - If True a reference line is drawn on the graph. The default is to
               fit a line via OLS regression.
+        exceed : boolean, optional
 
-        excced : boolean, optional
              - If False (default) the raw sample quantiles are plotted against
                the theoretical quantiles, show the probability that a sample
                will not exceed a given value
              - If True, the theoretical quantiles are flipped such that the
                figure displays the probability that a sample will exceed a
                given value.
-
+        ax : Matplotlib AxesSubplot instance, optional
+            If given, this subplot is used to plot in instead of a new figure
+            being created.
         **plotkwargs : additional matplotlib arguments to be passed to the
             `plot` command.
 

statsmodels/graphics/tests/test_gofplots.py

@@ -1,5 +1,4 @@
 import numpy as np
-np.random.seed(5)
 from numpy.testing import dec
 
 import statsmodels.api as sm
@@ -111,6 +110,7 @@ def test_probplot_pltkwargs(self):
 
 class TestProbPlotLongely(BaseProbplotMixin):
     def setup(self):
+        np.random.seed(5)
         self.data = sm.datasets.longley.load()
         self.data.exog = sm.add_constant(self.data.exog, prepend=False)
         self.mod_fit = sm.OLS(self.data.endog, self.data.exog).fit()
@@ -121,6 +121,7 @@ def setup(self):
 
 class TestProbPlotRandomNormalMinimal(BaseProbplotMixin):
     def setup(self):
+        np.random.seed(5)
         self.data = np.random.normal(loc=8.25, scale=3.25, size=37)
         self.prbplt = sm.ProbPlot(self.data)
         self.line = None
@@ -129,6 +130,7 @@ def setup(self):
 
 class TestProbPlotRandomNormalWithFit(BaseProbplotMixin):
     def setup(self):
+        np.random.seed(5)
         self.data = np.random.normal(loc=8.25, scale=3.25, size=37)
         self.prbplt = sm.ProbPlot(self.data, fit=True)
         self.line = 'q'
@@ -137,6 +139,7 @@ def setup(self):
 
 class TestProbPlotRandomNormalLocScale(BaseProbplotMixin):
     def setup(self):
+        np.random.seed(5)
         self.data = np.random.normal(loc=8.25, scale=3.25, size=37)
         self.prbplt = sm.ProbPlot(self.data, loc=8.25, scale=3.25)
         self.line = '45'