def extract(self, rois=None, signal_channel=0, label=None,
remove_overlap=True, n_processes=None, demix_channel=None,
save_summary=True):
"""Extracts imaging data from the current dataset using the
supplied ROIs file.
Parameters
----------
rois : sima.ROI.ROIList, optional
ROIList of rois to extract
signal_channel : string or int, optional
Channel containing the signal to be extracted, either an integer
index or a name in self.channel_names
label : string or None, optional
Text label to describe this extraction, if None defaults to a
timestamp.
remove_overlap : bool, optional
If True, remove any pixels that overlap between masks.
n_processes : int, optional
Number of processes to farm out the extraction across. Should be
at least 1 and at most one less then the number of CPUs in the
computer. If None, uses half the CPUs.
demix_channel : string or int, optional
Channel to demix from the signal channel, either an integer index
or a name in self.channel_names If None, do not demix signals.
save_summary : bool, optional
If True, additionally save a summary of the extracted ROIs.
Return
------
dict of arrays
Keys: raw, demixed_raw, mean_frame, overlap, signal_channel, rois,
timestamp
See also
--------
sima.ROI.ROIList
"""
signal_channel = self._resolve_channel(signal_channel)
demix_channel = self._resolve_channel(demix_channel)
if rois is None:
rois = self.ROIs[most_recent_key(self.ROIs)]
if rois is None or not len(rois):
raise Exception('Cannot extract dataset with no ROIs.')
if self.savedir:
return save_extracted_signals(
self, rois, self.savedir, label, signal_channel=signal_channel,
remove_overlap=remove_overlap, n_processes=n_processes,
demix_channel=demix_channel, save_summary=save_summary
)
else:
return extract_rois(self, rois, signal_channel, remove_overlap,
n_processes, demix_channel)
def extract(self, rois=None, signal_channel=0, label=None,
remove_overlap=True, n_processes=1, demix_channel=None,
save_summary=True):
"""Extracts imaging data from the current dataset using the
supplied ROIs file.
Parameters
----------
rois : sima.ROI.ROIList, optional
ROIList of rois to extract
signal_channel : string or int, optional
Channel containing the signal to be extracted, either an integer
index or a name in self.channel_names
label : string or None, optional
Text label to describe this extraction, if None defaults to a
timestamp.
remove_overlap : bool, optional
If True, remove any pixels that overlap between masks.
n_processes : int, optional
Number of processes to farm out the extraction across. Should be
at least 1 and at most one less then the number of CPUs in the
computer. Defaults to 1.
demix_channel : string or int, optional
Channel to demix from the signal channel, either an integer index
or a name in self.channel_names If None, do not demix signals.
save_summary : bool, optional
If True, additionally save a summary of the extracted ROIs.
Return
------
dict of arrays
Keys: raw, demixed_raw, mean_frame, overlap, signal_channel, rois,
timestamp
See also
--------
sima.ROI.ROIList
"""
signal_channel = self._resolve_channel(signal_channel)
demix_channel = self._resolve_channel(demix_channel)
if rois is None:
rois = self.ROIs[most_recent_key(self.ROIs)]
if rois is None or not len(rois):
raise Exception('Cannot extract dataset with no ROIs.')
if self.savedir:
return save_extracted_signals(
self, rois, self.savedir, label, signal_channel=signal_channel,
remove_overlap=remove_overlap, n_processes=n_processes,
demix_channel=demix_channel, save_summary=save_summary
)
else:
return extract_rois(self, rois, signal_channel, remove_overlap,
n_processes, demix_channel)
def extract(self, rois=None, signal_channel=0, label=None,
remove_overlap=True, n_processes=1, demix_channel=None,
save_summary=True):
"""Extracts imaging data from the current dataset using the
supplied ROIs file.
Parameters
----------
rois : sima.ROI.ROIList, optional
ROIList of rois to extract
signal_channel : string or int, optional
Channel containing the signal to be extracted, either an integer
index or a name in self.channel_names.
label : string or None, optional
Text label to describe this extraction, if None defaults to a
timestamp.
remove_overlap : bool, optional
If True, remove any pixels that overlap between masks.
n_processes : int, optional
Number of processes to farm out the extraction across. Should be
at least 1 and at most one less then the number of CPUs in the
computer. Defaults to 1.
demix_channel : string or int, optional
Channel to demix from the signal channel, either an integer index
or a name in self.channel_names If None, do not demix signals.
save_summary : bool, optional
If True, additionally save a summary of the extracted ROIs.
Return
------
signals: dict
The extracted signals along with parameters and values calculated
during extraction.
Contains the following keys:
raw, demixed_raw : list of arrays
The raw/demixed extracted signal. List of length
num_sequences, each element is an array of shape
(num_ROIs, num_frames).
mean_frame : array
Time-averaged mean frame of entire dataset.
overlap : tuple of arrays
Tuple of (rows, cols) such that zip(*overlap) returns
row, col pairs of pixel coordinates that are in more than
one mask. Note: coordinates are for the **flattened**
image, so 'rows' is always 0s.
signal_channel : int
The index of the channel that was extracted.
rois : list of dict
All the ROIs used for the extraction with the order matched
to the order of the rows in 'raw'.
See sima.ROI.todict for details of dictionary format.
timestamp : string
Date and time of extraction in '%Y-%m-%d-%Hh%Mm%Ss' format
See also
--------
sima.ROI.ROI
sima.ROI.ROIList
"""
signal_channel = self._resolve_channel(signal_channel)
demix_channel = self._resolve_channel(demix_channel)
if rois is None:
rois = self.ROIs[most_recent_key(self.ROIs)]
if rois is None or not len(rois):
raise Exception('Cannot extract dataset with no ROIs.')
if self.savedir:
return save_extracted_signals(
self, rois, self.savedir, label, signal_channel=signal_channel,
remove_overlap=remove_overlap, n_processes=n_processes,
demix_channel=demix_channel, save_summary=save_summary
)
else:
return extract_rois(self, rois, signal_channel, remove_overlap,
n_processes, demix_channel)