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[MNT] - Update peak extraction array & describe index column #197

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Merged
merged 3 commits into from
Feb 25, 2021
Merged

[MNT] - Update peak extraction array & describe index column #197

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608fe71
update array mechanics
TomDonoghue Feb 25, 2021
e1c815e
update docstrings for get_params
TomDonoghue Feb 25, 2021
47188e9
update docstrings for get_params
TomDonoghue Feb 25, 2021
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4 changes: 1 addition & 3 deletions fooof/objs/fit.py
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Original file line number Diff line number Diff line change
Expand Up @@ -586,9 +586,7 @@ def get_params(self, name, col=None):

Notes
-----
For further description of the data you can extract, check the FOOOFResults documentation.

If there is no data on periodic features, this method will return NaN.
If there are no fit peak (no peak parameters), this method will return NaN.
"""

if not self.has_model:
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16 changes: 7 additions & 9 deletions fooof/objs/group.py
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Expand Up @@ -354,7 +354,8 @@ def get_params(self, name, col=None):

Notes
-----
For further description of the data you can extract, check the FOOOFResults documentation.
When extracting peak information ('peak_params' or 'gaussian_params'), an additional column
is appended to the returned array, indicating the index of the model that the peak came from.
"""

if not self.has_model:
Expand All @@ -375,21 +376,18 @@ def get_params(self, name, col=None):
# As a special case, peak_params are pulled out in a way that appends
# an extra column, indicating which FOOOF run each peak comes from
if name in ('peak_params', 'gaussian_params'):
out = np.array([np.insert(getattr(data, name), 3, index, axis=1)
for index, data in enumerate(self.group_results)])

# Collect peak data, appending the index of the model it comes from
out = np.vstack([np.insert(getattr(data, name), 3, index, axis=1)
for index, data in enumerate(self.group_results)])

# This updates index to grab selected column, and the last column
# This last column is the 'index' column (FOOOF object source)
if col is not None:
col = [col, -1]
else:
out = np.array([getattr(data, name) for data in self.group_results])

# Some data can end up as a list of separate arrays
# If so, concatenate it all into one 2d array
if isinstance(out[0], np.ndarray):
out = np.concatenate([arr.reshape(1, len(arr)) \
if arr.ndim == 1 else arr for arr in out], 0)

# Select out a specific column, if requested
if col is not None:
out = out[:, col]
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