def _unnormalize_df(self, df):
"""
Un-normalize DataFrame
Parameters
----------
df : pandas.DataFrame
DataFrame of features/label to un-normalize
Returns
-------
df : pandas.DataFrame
Native features/label df if norm params are not None
"""
means, stdevs = self.get_norm_params(df.columns)
if means is not None and stdevs is not None:
df = PreProcess.unnormalize(df.copy(), means, stdevs)
else:
msg = ("Normalization parameters are unavailable, df will not be "
"un-normalized!")
logger.warning(msg)
warn(msg)
return df
def _unnormalize_arr(self, arr, names):
"""
Un-normalize array using given names
Parameters
----------
arr : ndarray
Array of features/label to un-normalize
names : list
List of feature/label names
Returns
-------
arr : ndarray
Native features/label array if norm params are not None
"""
n_names = self._get_item_number(arr)
if len(names) != n_names:
msg = ("Number of item names ({}) does not match number of items "
"({})".format(len(names), arr.shape[1]))
logger.error(msg)
raise RuntimeError(msg)
means, stdevs = self.get_norm_params(names)
if means is not None and stdevs is not None:
arr = PreProcess.unnormalize(arr.copy(), means, stdevs)
else:
msg = ("Normalization parameters are unavailable, arr will not be "
"un-normalized!")
logger.warning(msg)
warn(msg)
return arr
def _unnormalize_dict(self, items):
"""
Un-normalize given dictionary of items (features | labels)
Parameters
----------
items : dict
mapping of names to vectors
Returns
-------
native_items : dict
mapping of names to native vectors
"""
native_items = {}
for key, value in items.items():
norm_params = self.normalization_parameters[key]
if norm_params is not None:
value = PreProcess.unnormalize(value, norm_params['mean'],
norm_params['stdev'])
else:
msg = ("Normalization Parameters unavailable, {} will not be "
"un-normalized!".format(key))
logger.warning(msg)
warn(msg)
native_items[key] = value
return native_items
def unnormalize_prediction(self, prediction):
"""
Unnormalize prediction if needed
Parameters
----------
prediction : ndarray
Model prediction
Returns
-------
prediction : ndarray
Native prediction
"""
means = self.label_means[0]
if means:
stdevs = self.label_stdevs[0]
prediction = PreProcess.unnormalize(prediction, means, stdevs)
return prediction
