diff options
Diffstat (limited to 'numpy/ma/morestats.py')
-rw-r--r-- | numpy/ma/morestats.py | 16 |
1 files changed, 8 insertions, 8 deletions
diff --git a/numpy/ma/morestats.py b/numpy/ma/morestats.py index 9816608b7..7dbc844b0 100644 --- a/numpy/ma/morestats.py +++ b/numpy/ma/morestats.py @@ -59,7 +59,7 @@ Returns Notes ----- The function is restricted to 2D arrays. - + """ def _hd_1D(data,prob,var): "Computes the HD quantiles for a 1D array. Returns nan for invalid data." @@ -114,7 +114,7 @@ Parameters Axis along which to compute the quantiles. If None, use a flattened array. var : boolean Whether to return the variance of the estimate. - + """ result = hdquantiles(data,[0.5], axis=axis, var=var) return result.squeeze() @@ -137,7 +137,7 @@ Parameters Notes ----- The function is restricted to 2D arrays. - + """ def _hdsd_1D(data,prob): "Computes the std error for 1D arrays." @@ -192,7 +192,7 @@ Parameters Confidence level of the intervals. axis : int Axis along which to cut. If None, uses a flattened version of the input. - + """ data = masked_array(data, copy=False) trimmed = trim_both(data, proportiontocut=proportiontocut, axis=axis) @@ -215,7 +215,7 @@ Parameters Sequence of quantiles to compute. axis : int Axis along which to compute the quantiles. If None, use a flattened array. - + """ def _mjci_1D(data, p): data = data.compressed() @@ -345,7 +345,7 @@ def rank_data(data, axis=None, use_missing=False): along the given axis. If some values are tied, their rank is averaged. - If some values are masked, their rank is set to 0 if use_missing is False, + If some values are masked, their rank is set to 0 if use_missing is False, or set to the average rank of the unmasked values if use_missing is True. Parameters @@ -353,8 +353,8 @@ def rank_data(data, axis=None, use_missing=False): data : sequence Input data. The data is transformed to a masked array axis : integer - Axis along which to perform the ranking. - If None, the array is first flattened. An exception is raised if + Axis along which to perform the ranking. + If None, the array is first flattened. An exception is raised if the axis is specified for arrays with a dimension larger than 2 use_missing : boolean Whether the masked values have a rank of 0 (False) or equal to the |