Docs and input type fixes

Author: chpolste

src/earthkit/meteo/stats/array/distributions.py

@@ -27,23 +27,24 @@ def fit(cls, sample, axis):
 
     @abc.abstractmethod
     def cdf(self, x):
-        """Evaluate the continuous distribution function."""
+        """Evaluate the cumulative distribution function (CDF)."""
 
     @abc.abstractmethod
     def ppf(self, x):
-        """Evaluate the inverse CDF (percent point function)."""
+        """Evaluate the percent point function (PPF; inverse CDF)."""
 
 
 # Temporary drop-in replacement for scipy.stats.lmoment from scipy v0.15
 def _lmoment(sample, order=(1, 2), axis=0):
-    """Compute first 2 L-moments of dataset along first axis."""
+    """Compute first 2 L-moments of a dataset along the first axis."""
     if len(order) != 2 or order[0] != 1 or order[1] != 2:
         raise NotImplementedError
     if axis != 0:
         raise NotImplementedError
 
     nmoments = 3
 
+    sample = np.asarray(sample)
     # At least four values needed to make a sample L-moments estimation
     nvalues, *rest_shape = sample.shape
     if nvalues < 4:
@@ -137,7 +138,7 @@ def ndim(self):
         return self.mu.ndim
 
     def cdf(self, x):
-        """Evaluate the cumulative distribution function.
+        """Evaluate the cumulative distribution function (CDF).
 
         Parameters
         ----------
@@ -154,7 +155,7 @@ def cdf(self, x):
         return 1.0 - np.exp(-np.exp((self.mu - x) / self.sigma))
 
     def ppf(self, p):
-        """Evaluate the inverse cumulative distribution function.
+        """Evaluate the percent point function (PPF; inverse CDF).
 
         Parameters
         ----------

src/earthkit/meteo/stats/array/extreme_values.py

@@ -13,7 +13,7 @@
 class MaximumStatistics:
     """Recurrence statistics for a sample of maximum values.
 
-    All statistics are computed based on a fitted continuous probability
+    All statistics are computed from a fitted continuous probability
     distribution. Results will only be meaningful if this fitted distribution
     is representative of the sample statistics.
 
@@ -31,7 +31,7 @@ class MaximumStatistics:
         Temporal frequency of the input data. Used to scale return periods.
         Defaults to 1, i.e., no scaling applied. Note: when supplying a numpy
         timedelta64, the unit carries over to return periods.
-    dist:
+    dist: ContinuousDistribution
         Continuous probability distribution fitted to the input data.
     """
 
@@ -51,7 +51,7 @@ def freq(self):
         return self._freq
 
     def probability_of_threshold(self, threshold):
-        """Probability of exceeding the threshold.
+        """Probability of threshold exceedance.
 
         Parameters
         ----------
@@ -67,7 +67,7 @@ def probability_of_threshold(self, threshold):
         return self.dist.cdf(threshold)
 
     def return_period_of_threshold(self, threshold):
-        """Return period of exceeding the threshold.
+        """Return period of threshold exceedance.
 
         Parameters
         ----------