MAINT: prefix developer-only functions with _
@@ -22,14 +22,14 @@ import numpy as np
class HCIPostProcAlgo(BaseEstimator):
""" Base HCI post-processing algorithm class.
"""
- def print_parameters(self):
+ def _print_parameters(self):
""" Printing out the parameters of the algorithm.
"""
dicpar = self.get_params()
for key in dicpar.keys():
print("{}: {}".format(key, dicpar[key]))
- def store_args(self, kwargs, *skip):
+ def _store_args(self, kwargs, *skip):
# TODO: this could be integrated with sklearn's BaseEstimator methods
for k in kwargs:
if k == "self" or k in skip:
@@ -161,9 +161,9 @@ class HCIMedianSub(HCIPostProcAlgo):
if not isinstance(dataset, (HCIDataset, type(None))):
raise ValueError('`dataset` must be a HCIDataset object or None')
- self.store_args(locals())
+ self._store_args(locals())
if verbose:
- self.print_parameters()
+ self._print_parameters()
def run(self, dataset=None, nproc=1, verbose=True):
""" Running the HCI median subtraction algorithm for model PSF
@@ -290,9 +290,9 @@ class HCIPca(HCIPostProcAlgo):
if not isinstance(dataset, (HCIDataset, type(None))):
raise ValueError('`dataset` must be a HCIDataset object or None')
- self.store_args(locals())
+ self._store_args(locals())
if verbose:
- self.print_parameters()
+ self._print_parameters()
def run(self, dataset=None, nproc=1, verbose=True, debug=False):
""" Running the HCI PCA algorithm for model PSF subtraction.
