From e8d43895bf4b0fd70a97df4cbf49ed2bd41df10b Mon Sep 17 00:00:00 2001 From: Ross Markello Date: Tue, 12 Nov 2019 23:05:18 -0500 Subject: [PATCH 1/9] [REF] Use scipy.signal.find_peaks Instead of rolling our own -- this has a lot more functionality that can potentially be integrated into `peakfind_physio()` --- peakdet/editor.py | 5 +- peakdet/operations.py | 22 ++++--- peakdet/utils.py | 148 +----------------------------------------- 3 files changed, 17 insertions(+), 158 deletions(-) diff --git a/peakdet/editor.py b/peakdet/editor.py index 293c957..a97146e 100644 --- a/peakdet/editor.py +++ b/peakdet/editor.py @@ -124,7 +124,6 @@ def undo(self): ) self.deleted.difference_update(peaks['remove']) - self.data._metadata.troughs = utils.check_troughs(self.data, - self.data.peaks, - self.data.troughs) + self.data._metadata['troughs'] = utils.check_troughs(self.data, + self.data.peaks) self.plot_signals() diff --git a/peakdet/operations.py b/peakdet/operations.py index 0aa7ca6..d798db8 100644 --- a/peakdet/operations.py +++ b/peakdet/operations.py @@ -122,12 +122,16 @@ def peakfind_physio(data, *, thresh=0.2, dist=None): # first pass peak detection to get approximate distance between peaks cdist = data.fs // 4 if dist is None else dist - locs = utils.find_peaks(data, dist=cdist, thresh=thresh) - cdist = np.diff(locs).mean() // 2 + thresh = np.squeeze(np.diff(np.percentile(data, [5, 95]))) * thresh + locs, heights = signal.find_peaks(data[:], distance=cdist, height=thresh) + # second, more thorough peak detection - data._metadata.peaks = utils.find_peaks(data, dist=cdist, thresh=thresh) + cdist = np.diff(locs).mean() // 2 + heights = np.percentile(heights['peak_heights'], 1) + data._metadata['peaks'] = signal.find_peaks(data[:], distance=cdist, + height=heights)[0] # perform trough detection based on detected peaks - data._metadata.troughs = utils.check_troughs(data, data.peaks, []) + data._metadata['troughs'] = utils.check_troughs(data, data.peaks) return data @@ -148,9 +152,8 @@ def delete_peaks(data, remove): """ data = utils.check_physio(data, ensure_fs=False, copy=True) - data._metadata.peaks = np.setdiff1d(data._metadata.peaks, remove) - data._metadata.troughs = utils.check_troughs(data, data.peaks, - data.troughs) + data._metadata['peaks'] = np.setdiff1d(data._metadata['peaks'], remove) + data._metadata['troughs'] = utils.check_troughs(data, data.peaks) return data @@ -171,9 +174,8 @@ def reject_peaks(data, remove): """ data = utils.check_physio(data, ensure_fs=False, copy=True) - data._metadata.reject = np.append(data._metadata.reject, remove) - data._metadata.troughs = utils.check_troughs(data, data.peaks, - data.troughs) + data._metadata['reject'] = np.append(data._metadata['reject'], remove) + data._metadata['troughs'] = utils.check_troughs(data, data.peaks) return data diff --git a/peakdet/utils.py b/peakdet/utils.py index 6588468..7b0e0ef 100644 --- a/peakdet/utils.py +++ b/peakdet/utils.py @@ -185,140 +185,7 @@ def new_physio_like(ref_physio, data, *, fs=None, dtype=None, return out -def get_extrema(data, peaks=True, thresh=0.4): - """ - Find extrema in `data` by changes in sign of first derivative - - Parameters - ---------- - data : array_like or Physio_like - Input data on which to perform extrema detection - peaks : bool, optional - Whether to look for peaks instead of troughs. Default: True - thresh : float (0, 1), optional - Amplitude based threshold - - Returns - ------- - locs : np.ndarray - Indices of extrema from `data` - """ - - if thresh < 0 or thresh > 1: - raise ValueError('Provided threshold {} is not in range [0, 1]. ' - 'Please provide a valid threshold.' - .format(thresh)) - - if peaks: - uthresh = (thresh * np.diff(np.percentile(data, [5, 95]))) - Indx = np.argwhere(data > uthresh).squeeze() - else: - uthresh = (thresh * np.diff(np.percentile(data, [95, 5]))) - Indx = np.argwhere(data < uthresh).squeeze() - - trend = np.sign(np.diff(data)) - idx = np.argwhere(trend == 0).squeeze() - - for i in range(idx.size - 1, -1, -1): - gtz = trend[min(idx[i] + 1, trend.size - 1)] >= 0 - trend[idx[i]] = 1 if gtz else -1 - - idx = np.argwhere(np.diff(trend) == (-2 if peaks else 2)).squeeze() + 1 - - return np.intersect1d(Indx, idx) - - -def min_peak_dist(data, locs, peaks=True, dist=250): - """ - Ensures `locs` in `data` are separated by at least `dist` - - Parameters - ---------- - data : array_like or Physio_like - Input data for which `locs` were detected - locs : array_like - Extrema in `data`, typically from `get_extrema()` - peaks : bool, optional - Whether to look for peaks instead of troughs. Default: True - dist : int, optional - Minimum required distance (in datapoints) b/w `locs`. Default: 250 - - Returns - ------- - locs : np.ndarray - Extrema separated by at least `dist` - """ - - if not any(np.diff(sorted(locs)) <= dist): - return locs - - idx = data[locs].argsort() - if peaks: - idx = idx[::-1] - locs = locs[idx] - idelete = np.zeros_like(locs, dtype=bool) - - for i in range(locs.size): - if not idelete[i]: - dist_diff = np.logical_and(locs >= locs[i] - dist, - locs <= locs[i] + dist) - idelete = np.logical_or(idelete, dist_diff) - idelete[i] = 0 - - return np.sort(locs[~idelete]) - - -def find_peaks(data, thresh=0.4, dist=250): - """ - Finds peaks in `data` - - Parameters - ---------- - data : array_like or Physio_like - Input data on which to perform peak detection - thresh : float (0, 1), optional - Amplitude based threshold - dist : int - Minimum required distance (in datapoints) b/w peaks in `data` - - Returns - ------- - peaks : np.ndarray - Indices of peak locations in `data` - """ - - extrema = get_extrema(data, thresh=thresh) - peaks = min_peak_dist(data, extrema, dist=dist) - - return peaks.astype(int) - - -def find_troughs(data, thresh=0.4, dist=250): - """ - Finds troughs in `data` - - Parameters - ---------- - data : array_like or Physio_like - Input data on which to perform trough detection - thresh : float (0, 1), optional - Amplitude based threshold - dist : int - Minimum required distance (in datapoints) b/w troughs in `data` - - Returns - ------- - troughs : np.ndarray - Indices of trough locations in `data` - """ - - extrema = get_extrema(data, peaks=False, thresh=thresh) - troughs = min_peak_dist(data, extrema, peaks=False, dist=dist) - - return troughs.astype(int) - - -def check_troughs(data, peaks, troughs): +def check_troughs(data, peaks): """ Confirms that `troughs` exists between every set of `peaks` in `data` @@ -328,8 +195,6 @@ def check_troughs(data, peaks, troughs): Input data for which `troughs` and `peaks` were detected peaks : array-like Indices of suspected peak locations in `data` - troughs : array-like - Indices of suspected trough locations in `data` Returns ------- @@ -340,15 +205,8 @@ def check_troughs(data, peaks, troughs): all_troughs = np.zeros(peaks.size - 1, dtype=int) for f in range(peaks.size - 1): - curr = np.logical_and(troughs > peaks[f], - troughs < peaks[f + 1]) - if not np.any(curr): - dp = data[peaks[f]:peaks[f + 1]] - idx = peaks[f] + np.argwhere(dp == dp.min())[0] - else: - idx = troughs[curr] - if idx.size > 1: - idx = idx[0] + dp = data[peaks[f]:peaks[f + 1]] + idx = peaks[f] + np.argwhere(dp == dp.min())[0] all_troughs[f] = idx return all_troughs From b78007dcaa3af8d7e43e487be8087425b42806ad Mon Sep 17 00:00:00 2001 From: Ross Markello Date: Tue, 12 Nov 2019 23:05:59 -0500 Subject: [PATCH 2/9] [TEST] Updates test from e8d4389 --- peakdet/tests/test_operations.py | 4 +-- peakdet/tests/test_utils.py | 51 +------------------------------- 2 files changed, 3 insertions(+), 52 deletions(-) diff --git a/peakdet/tests/test_operations.py b/peakdet/tests/test_operations.py index 8060cd3..4257e53 100644 --- a/peakdet/tests/test_operations.py +++ b/peakdet/tests/test_operations.py @@ -67,14 +67,14 @@ def test_peakfind_physio(): def test_delete_peaks(): - to_delete = [192, 24685, 44169] + to_delete = [24685, 44169] peaks = operations.peakfind_physio(WITHFS) deleted = operations.delete_peaks(peaks, to_delete) assert len(deleted.peaks) == len(peaks.peaks) - len(to_delete) def test_reject_peaks(): - to_reject = [192, 24685, 44169] + to_reject = [24685, 44169] peaks = operations.peakfind_physio(WITHFS) rejected = operations.reject_peaks(peaks, to_reject) assert len(rejected.peaks) == len(peaks.peaks) - len(to_reject) diff --git a/peakdet/tests/test_utils.py b/peakdet/tests/test_utils.py index 1d859f5..ddb54e9 100644 --- a/peakdet/tests/test_utils.py +++ b/peakdet/tests/test_utils.py @@ -85,58 +85,9 @@ def test_new_physio_like(): assert v.size == 0 -def test_get_extrema(): - # check that peak detection works - assert_array_equal(utils.get_extrema(DATA), PEAKS) - # check that threshold modulates detection - assert_array_equal(utils.get_extrema(DATA, thresh=0.6), np.array([])) - # check that trough detection works, too - assert_array_equal(utils.get_extrema(DATA, False), TROUGHS) - # check threshold bounds - with pytest.raises(ValueError): - utils.get_extrema(DATA, thresh=-0.1) - with pytest.raises(ValueError): - utils.get_extrema(DATA, thresh=1.1) - - -def test_min_peak_dist(): - # test peaks w/ and w/o removal due to `dist` - assert_array_equal(utils.min_peak_dist(DATA, PEAKS, dist=10), - PEAKS) - assert_array_equal(utils.min_peak_dist(DATA, PEAKS, dist=20), - np.array([3, 28])) - # test troughs w/ and w/o removal due to `dist` - assert_array_equal(utils.min_peak_dist(DATA, TROUGHS, False, dist=10), - TROUGHS) - assert_array_equal(utils.min_peak_dist(DATA, TROUGHS, False, dist=20), - np.array([9, 34])) - - -def test_find_peaks(): - # check that `dist` parameter modulates detected peaks - assert_array_equal(utils.find_peaks(DATA, dist=10), PEAKS) - assert_array_equal(utils.find_peaks(DATA, dist=20), np.array([3, 28])) - # ensure returned array is of correct type - assert utils.find_peaks(DATA).dtype == np.int64 - - -def test_find_troughs(): - # check that `dist` parameter modulates detected troughs - assert_array_equal(utils.find_troughs(DATA, dist=10), TROUGHS) - assert_array_equal(utils.find_troughs(DATA, dist=20), np.array([9, 34])) - # ensure returned array is of correct type - assert utils.find_peaks(DATA).dtype == np.int64 - - def test_check_troughs(): true = np.array([9, 21]) - # check that func fills in when no troughs provided - assert_array_equal(utils.check_troughs(DATA, PEAKS, []), true) - # check that func disregard troughs outside of peak bounds - assert_array_equal(utils.check_troughs(DATA, PEAKS, TROUGHS), true) - # check that func removes when two points are "troughs" inside peaks - assert_array_equal(utils.check_troughs(DATA, PEAKS, np.array([9, 10, 21])), - true) + assert_array_equal(utils.check_troughs(DATA, PEAKS), true) def test_corr(): From 23a4b80674cf994c6ca2e69d9bc0c54115a9380a Mon Sep 17 00:00:00 2001 From: Ross Markello Date: Thu, 14 May 2020 15:48:12 -0400 Subject: [PATCH 3/9] [REF] Remove sklearn dependency --- docs/conf.py | 1 - peakdet/editor.py | 10 ++-- peakdet/info.py | 1 - peakdet/operations.py | 5 +- peakdet/physio.py | 17 +++--- peakdet/tests/test_editor.py | 20 +++++-- peakdet/tests/test_utils.py | 32 +--------- peakdet/utils.py | 110 +---------------------------------- requirements.txt | 1 - 9 files changed, 33 insertions(+), 164 deletions(-) diff --git a/docs/conf.py b/docs/conf.py index ea0f0d0..3242e78 100644 --- a/docs/conf.py +++ b/docs/conf.py @@ -101,7 +101,6 @@ 'matplotlib': ('https://matplotlib.org', None), 'numpy': ('https://docs.scipy.org/doc/numpy', None), 'scipy': ('https://docs.scipy.org/doc/scipy/reference', None), - 'sklearn': ('http://scikit-learn.org/stable', None), } doctest_global_setup = """ diff --git a/peakdet/editor.py b/peakdet/editor.py index a97146e..49358fa 100644 --- a/peakdet/editor.py +++ b/peakdet/editor.py @@ -112,14 +112,14 @@ def undo(self): func, peaks = self.data._history.pop() if func == 'reject_peaks': - self.data._metadata.reject = np.setdiff1d( - self.data._metadata.reject, peaks['remove'] + self.data._metadata['reject'] = np.setdiff1d( + self.data._metadata['reject'], peaks['remove'] ) self.rejected.difference_update(peaks['remove']) elif func == 'delete_peaks': - self.data._metadata.peaks = np.insert( - self.data._metadata.peaks, - np.searchsorted(self.data._metadata.peaks, peaks['remove']), + self.data._metadata['peaks'] = np.insert( + self.data._metadata['peaks'], + np.searchsorted(self.data._metadata['peaks'], peaks['remove']), peaks['remove'] ) self.deleted.difference_update(peaks['remove']) diff --git a/peakdet/info.py b/peakdet/info.py index b268158..0ee99f3 100644 --- a/peakdet/info.py +++ b/peakdet/info.py @@ -18,7 +18,6 @@ INSTALL_REQUIRES = [ 'matplotlib', 'numpy', - 'scikit-learn', 'scipy', ] diff --git a/peakdet/operations.py b/peakdet/operations.py index d798db8..8d0c013 100644 --- a/peakdet/operations.py +++ b/peakdet/operations.py @@ -7,6 +7,7 @@ import numpy as np from scipy import signal from scipy.interpolate import InterpolatedUnivariateSpline + from peakdet import editor, utils @@ -128,8 +129,8 @@ def peakfind_physio(data, *, thresh=0.2, dist=None): # second, more thorough peak detection cdist = np.diff(locs).mean() // 2 heights = np.percentile(heights['peak_heights'], 1) - data._metadata['peaks'] = signal.find_peaks(data[:], distance=cdist, - height=heights)[0] + locs, heights = signal.find_peaks(data[:], distance=cdist, height=heights) + data._metadata['peaks'] = locs # perform trough detection based on detected peaks data._metadata['troughs'] = utils.check_troughs(data, data.peaks) diff --git a/peakdet/physio.py b/peakdet/physio.py index 5bcddcb..a5e4cec 100644 --- a/peakdet/physio.py +++ b/peakdet/physio.py @@ -4,7 +4,6 @@ """ import numpy as np -from sklearn.utils import Bunch class Physio(): @@ -63,11 +62,11 @@ def __init__(self, data, fs=None, history=None, metadata=None): except TypeError: raise TypeError('Provided metadata must be dict-like' 'with integer array entries.') - self._metadata = Bunch(**metadata) + self._metadata = dict(**metadata) else: - self._metadata = Bunch(peaks=np.empty(0, dtype=int), - troughs=np.empty(0, dtype=int), - reject=np.empty(0, dtype=int)) + self._metadata = dict(peaks=np.empty(0, dtype=int), + troughs=np.empty(0, dtype=int), + reject=np.empty(0, dtype=int)) def __array__(self): return self.data @@ -110,10 +109,10 @@ def peaks(self): @property def troughs(self): """ Indices of detected troughs in `data` """ - return self._metadata.troughs + return self._metadata['troughs'] @property def _masked(self): - return np.ma.masked_array(self._metadata.peaks, - mask=np.isin(self._metadata.peaks, - self._metadata.reject)) + return np.ma.masked_array(self._metadata['peaks'], + mask=np.isin(self._metadata['peaks'], + self._metadata['reject'])) diff --git a/peakdet/tests/test_editor.py b/peakdet/tests/test_editor.py index 95d292c..d3dee6d 100644 --- a/peakdet/tests/test_editor.py +++ b/peakdet/tests/test_editor.py @@ -1,31 +1,41 @@ # -*- coding: utf-8 -*- +from collections import namedtuple + import pytest -from sklearn.utils import Bunch + from peakdet import editor from peakdet.tests.utils import get_peak_data -PEAKS = get_peak_data() + +wheel = namedtuple('wheel', ('step')) +key = namedtuple('key', ('key',)) def test_PhysioEditor(): edits = editor._PhysioEditor(get_peak_data()) + # test scroll functionality - edits.on_wheel(Bunch(step=10)) + edits.on_wheel(wheel(10)) + # test reject / delete functionality for m in range(2): edits.on_remove(0, 10, reject=True) edits.on_remove(10, 20, reject=False) + # undo delete + reject for m in range(2): edits.undo() + # test key undo (and undo when history doesn't exist) - edits.on_key(Bunch(key='ctrl+z')) + edits.on_key(key('ctrl+z')) + # redo so that there is history on quit edits.on_remove(0, 10, reject=True) edits.on_remove(10, 20, reject=False) + # quit editor and clean up edits - edits.on_key(Bunch(key='ctrl+q')) + edits.on_key(key('ctrl+z')) with pytest.raises(TypeError): editor._PhysioEditor([0, 1, 2]) diff --git a/peakdet/tests/test_utils.py b/peakdet/tests/test_utils.py index ddb54e9..fa15da7 100644 --- a/peakdet/tests/test_utils.py +++ b/peakdet/tests/test_utils.py @@ -66,7 +66,7 @@ def test_new_physio_like(): fname = testutils.get_test_data_path('ECG.csv') data = physio.Physio(np.loadtxt(fname), fs=1000.) data._history = [('does history', 'copy?')] - data._metadata.peaks = np.array([1, 2, 3]) + data._metadata['peaks'] = np.array([1, 2, 3]) # assert all copies happen by default new_data = utils.new_physio_like(data, data[:]) assert np.allclose(data, utils.new_physio_like(data, data[:])) @@ -88,33 +88,3 @@ def test_new_physio_like(): def test_check_troughs(): true = np.array([9, 21]) assert_array_equal(utils.check_troughs(DATA, PEAKS), true) - - -def test_corr(): - x = np.random.rand(10, 1) - # works both as 2D and 1D vectors (i.e., squeezeable) - assert np.allclose(utils.corr(x, x), 1) - assert np.allclose(utils.corr(x.squeeze(), x.squeeze()), 1) - # error raised when inputs aren't the same size - with pytest.raises(ValueError): - utils.corr(x, np.random.rand(9, 1)) - # error raised when one of the inputs is not squeezeable - with pytest.raises(ValueError): - utils.corr(x, np.random.rand(10, 2)) - # zscore only first - utils.corr(x, x, zscored=[False, True]) - # zscore only second - utils.corr(x, x, zscored=[True, False]) - # zscore both - utils.corr(x, x, zscored=[True, True]) - - -def test_gen_temp(): - peaks = testutils.get_peak_data() - utils.gen_temp(peaks.data, peaks.peaks) - - -def test_corr_template(): - peaks = testutils.get_peak_data() - temp = utils.gen_temp(peaks.data, peaks.peaks) - assert utils.corr_template(temp).size == temp.shape[-1] diff --git a/peakdet/utils.py b/peakdet/utils.py index 7b0e0ef..578b3f7 100644 --- a/peakdet/utils.py +++ b/peakdet/utils.py @@ -7,8 +7,6 @@ from functools import wraps import inspect import numpy as np -from scipy.stats import zscore -from sklearn.utils import Bunch from peakdet import physio @@ -177,7 +175,7 @@ def new_physio_like(ref_physio, data, *, fs=None, dtype=None, if dtype is None: dtype = ref_physio.data.dtype history = list(ref_physio.history) if copy_history else [] - metadata = Bunch(**ref_physio._metadata) if copy_metadata else None + metadata = dict(**ref_physio._metadata) if copy_metadata else None # make new class out = ref_physio.__class__(np.array(data, dtype=dtype), @@ -210,109 +208,3 @@ def check_troughs(data, peaks): all_troughs[f] = idx return all_troughs - - -def gen_temp(data, locs, factor=0.5): - """ - Generate waveform template array from `data` - - Waveforms are taken from around peak locations in `locs` - - Parameters - ---------- - data : array_like - locs : arrray_like - Indices of suspected peak locations - factor: float (0, 1), optional - - Returns - ------- - array : peak waveforms - """ - - avgrate = round(np.diff(locs).mean()) - THW = int(np.ceil(factor * (avgrate / 2))) - nsamptemp = (THW * 2) + 1 - npulse = locs.size - template = np.zeros([npulse - 2, nsamptemp]) - - for n in range(1, npulse - 1): - template[n - 1] = data[locs[n] - THW:locs[n] + THW + 1] - template[n - 1] = template[n - 1] - template[n - 1].mean() - template[n - 1] = template[n - 1] / max(abs(template[n - 1])) - - return template - - -def corr(x, y, zscored=[False, False]): - """ - Potentially faster correlation of `x` and `y` - - Will z-transform data before correlation. - - Parameters - ---------- - x : array, n x 1 - y : array, n x 1 - zscored : [bool, bool] - Whether x and y, respectively, have been z-transformed - - Returns - ------- - float : [0,1] correlation between `x` and `y` - """ - - x, y = np.asarray(x).squeeze(), np.asarray(y).squeeze() - - if x.ndim > 1 or y.ndim > 1: - raise ValueError('Input arrays must have only one dimension.') - if x.size != y.size: - raise ValueError('Input array dimensions must be same size.') - - # numpy corrcoef is faster if both variables need to be z-scored - if not np.any(zscored): - return np.corrcoef(x, y)[0, 1] - - if not zscored[0]: - x = zscore(x, ddof=1) - if not zscored[1]: - y = zscore(y, ddof=1) - - return np.dot(x.T, y) * (1. / (x.size - 1)) - - -def corr_template(temp, sim=0.95): - """ - Generates single waveform template from output of `gen_temp`. - - Correlates each row of `temp` to averaged template and selects rows with - correlation >=`sim` for use in final, averaged template. - - Parameters - ---------- - temp : array of waveforms - sim : float (0,1) - Cutoff for correlation of waveforms to average template - - Returns - ------- - array : template waveform - """ - - npulse = temp.shape[0] - - mean_temp = zscore(temp.mean(axis=0), ddof=1) - sim_to_temp = np.zeros((temp.shape[0], 1)) - - for n in range(temp.shape[0]): - sim_to_temp[n] = corr(temp[n], mean_temp, [False, True]) - - good_temp_ind = np.where(sim_to_temp > sim)[0] - if good_temp_ind.shape[0] >= np.ceil(npulse * 0.1): - clean_temp = temp[good_temp_ind] - else: - comp = 1 - np.ceil(npulse * 0.1) / npulse - new_temp_ind = np.where(sim_to_temp > comp)[0] - clean_temp = np.atleast_2d(temp[new_temp_ind]).T - - return clean_temp.mean(axis=0) diff --git a/requirements.txt b/requirements.txt index a3f358f..74fa65e 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,4 +1,3 @@ matplotlib numpy -scikit-learn scipy From 7290cde8b204f7f98cb3acdf976478ddadbfab65 Mon Sep 17 00:00:00 2001 From: Ross Markello Date: Thu, 14 May 2020 15:48:28 -0400 Subject: [PATCH 4/9] [REF] Fix allow_pickle issue in numpy.load This is a bandaid and `np.load` and `np.savez_compressed` should be removed from `peakdet.io` and replaced with something more sustainable (like saving the data as a JSON file or something). OR just removed altogether, if necessary. Pickling SHOULD NOT be allowed, but I just want to get tests passing so that I can transfer ownership of this thing to physiopy --- peakdet/io.py | 22 +++++++++++++--------- peakdet/tests/test_io.py | 12 ++++++++---- 2 files changed, 21 insertions(+), 13 deletions(-) diff --git a/peakdet/io.py b/peakdet/io.py index 0868ac7..b3f0fc5 100644 --- a/peakdet/io.py +++ b/peakdet/io.py @@ -12,7 +12,8 @@ EXPECTED = ['data', 'fs', 'history', 'metadata'] -def load_physio(data, *, fs=None, dtype=None, history=None): +def load_physio(data, *, fs=None, dtype=None, history=None, + allow_pickle=False): """ Returns `Physio` object with provided data @@ -26,6 +27,9 @@ def load_physio(data, *, fs=None, dtype=None, history=None): Data type to convert `data` to, if conversion needed. Default: None history : list of tuples, optional Functions that have been performed on `data`. Default: None + allow_pickle : bool, optional + Whether to allow loading if `data` contains pickled objects. Default: + False Returns ------- @@ -42,7 +46,7 @@ def load_physio(data, *, fs=None, dtype=None, history=None): # load it as a plain text file and instantiate a history if isinstance(data, str): try: - inp = dict(np.load(data)) + inp = dict(np.load(data, allow_pickle=allow_pickle)) for attr in EXPECTED: try: inp[attr] = inp[attr].dtype.type(inp[attr]) @@ -53,7 +57,7 @@ def load_physio(data, *, fs=None, dtype=None, history=None): # fix history, which needs to be list-of-tuple if inp['history'] is not None: inp['history'] = list(map(tuple, inp['history'])) - except IOError: + except (IOError, OSError, ValueError): inp = dict(data=np.loadtxt(data), history=[utils._get_call(exclude=[])]) phys = physio.Physio(**inp) @@ -86,33 +90,33 @@ def load_physio(data, *, fs=None, dtype=None, history=None): return phys -def save_physio(file, data): +def save_physio(fname, data): """ Saves `data` to `fname` Parameters ---------- - file : str + fname : str Path to output file; .phys will be appended if necessary data : Physio_like Data to be saved to file Returns ------- - file : str + fname : str Full filepath to saved output """ from peakdet.utils import check_physio data = check_physio(data) - file += '.phys' if not file.endswith('.phys') else '' - with open(file, 'wb') as dest: + fname += '.phys' if not fname.endswith('.phys') else '' + with open(fname, 'wb') as dest: hist = data.history if data.history != [] else None np.savez_compressed(dest, data=data.data, fs=data.fs, history=hist, metadata=data._metadata) - return file + return fname def load_history(file, verbose=False): diff --git a/peakdet/tests/test_io.py b/peakdet/tests/test_io.py index 8896229..db02ebd 100644 --- a/peakdet/tests/test_io.py +++ b/peakdet/tests/test_io.py @@ -10,19 +10,22 @@ def test_load_physio(): # try loading pickle file (from io.save_physio) - pckl = io.load_physio(get_test_data_path('ECG.phys')) + pckl = io.load_physio(get_test_data_path('ECG.phys'), allow_pickle=True) assert isinstance(pckl, physio.Physio) assert pckl.data.size == 44611 assert pckl.fs == 1000. with pytest.warns(UserWarning): - pckl = io.load_physio(get_test_data_path('ECG.phys'), fs=500.) + pckl = io.load_physio(get_test_data_path('ECG.phys'), fs=500., + allow_pickle=True) assert pckl.fs == 500. + # try loading CSV file csv = io.load_physio(get_test_data_path('ECG.csv')) assert isinstance(csv, physio.Physio) assert np.allclose(csv, pckl) assert np.isnan(csv.fs) assert csv.history[0][0] == 'load_physio' + # try loading array with pytest.warns(UserWarning): arr = io.load_physio(np.loadtxt(get_test_data_path('ECG.csv'))) @@ -30,6 +33,7 @@ def test_load_physio(): arr = io.load_physio(np.loadtxt(get_test_data_path('ECG.csv')), history=[('np.loadtxt', {'fname': 'ECG.csv'})]) assert isinstance(arr, physio.Physio) + # try loading physio object (and resetting dtype) out = io.load_physio(arr, dtype='float32') assert out.data.dtype == np.dtype('float32') @@ -40,10 +44,10 @@ def test_load_physio(): def test_save_physio(tmpdir): - pckl = io.load_physio(get_test_data_path('ECG.phys')) + pckl = io.load_physio(get_test_data_path('ECG.phys'), allow_pickle=True) out = io.save_physio(tmpdir.join('tmp').purebasename, pckl) assert os.path.exists(out) - assert isinstance(io.load_physio(out), physio.Physio) + assert isinstance(io.load_physio(out, allow_pickle=True), physio.Physio) def test_load_history(tmpdir): From 81087c819d9f654f66c38a7e6be192ef9bb8b78c Mon Sep 17 00:00:00 2001 From: Ross Markello Date: Tue, 12 Nov 2019 22:18:28 -0500 Subject: [PATCH 5/9] [REF] Allow specification of interpolation type Adds `kind` param to `peakdet.interpolate_physio()` --- peakdet/operations.py | 11 ++++++----- 1 file changed, 6 insertions(+), 5 deletions(-) diff --git a/peakdet/operations.py b/peakdet/operations.py index 8d0c013..2563947 100644 --- a/peakdet/operations.py +++ b/peakdet/operations.py @@ -5,9 +5,7 @@ import matplotlib.pyplot as plt import numpy as np -from scipy import signal -from scipy.interpolate import InterpolatedUnivariateSpline - +from scipy import interpolate, signal from peakdet import editor, utils @@ -64,7 +62,7 @@ def filter_physio(data, cutoffs, method, *, order=3): @utils.make_operation() -def interpolate_physio(data, target_fs): +def interpolate_physio(data, target_fs, *, kind='cubic'): """ Interpolates `data` to desired sampling rate `target_fs` @@ -74,6 +72,9 @@ def interpolate_physio(data, target_fs): Input physiological data to be interpolated target_fs : float Desired sampling rate for `data` + kind : str or int, optional + Type of interpolation to perform. Must be one of available kinds in + :func:`scipy.interpolate.interp1d`. Default: 'cubic' Returns ------- @@ -90,7 +91,7 @@ def interpolate_physio(data, target_fs): t_new = np.linspace(0, len(data) / data.fs, int(len(data) * factor)) # interpolate data and generate new Physio object - interp = InterpolatedUnivariateSpline(t_orig, data[:])(t_new) + interp = interpolate.interp1d(t_orig, data, kind=kind)(t_new) interp = utils.new_physio_like(data, interp, fs=target_fs) return interp From bc37eddf91d5a0d0acb4144de3202c50495170ab Mon Sep 17 00:00:00 2001 From: Ross Markello Date: Thu, 14 May 2020 16:46:48 -0400 Subject: [PATCH 6/9] [DOC] Update docs to fix doctests --- docs/user_guide/loading.rst | 2 +- docs/user_guide/metrics.rst | 3 ++- docs/user_guide/physio.rst | 4 ++-- docs/user_guide/saving.rst | 9 ++++++--- 4 files changed, 11 insertions(+), 7 deletions(-) diff --git a/docs/user_guide/loading.rst b/docs/user_guide/loading.rst index 2a2e8b8..705c4fc 100644 --- a/docs/user_guide/loading.rst +++ b/docs/user_guide/loading.rst @@ -33,7 +33,7 @@ This way, the loading of the data is retained in the object's history: .. doctest:: >>> ecg.history - [('load_physio', {'data': 'ECG.csv', 'dtype': None, 'fs': 1000.0, 'history': None})] + [('load_physio', {'allow_pickle': False, 'data': 'ECG.csv', 'dtype': None, 'fs': 1000.0, 'history': None})] There are also a number of functions for loading data from "standard" formats. For example, if your data were collected using the `rtpeaks >> from peakdet import HRV >>> metrics = HRV(data) >>> print(f'{metrics.rmssd:.2f} ms') - 27.75 ms + 26.61 ms The :py:class:`~.HRV` class contains many common heart rate variability metrics including the root mean square of successive differences, as shown above. It diff --git a/docs/user_guide/physio.rst b/docs/user_guide/physio.rst index b1d5c0a..e15af86 100644 --- a/docs/user_guide/physio.rst +++ b/docs/user_guide/physio.rst @@ -68,9 +68,9 @@ store the indices of the detected :py:attr:`~.Physio.peaks` and >>> phys = operations.peakfind_physio(phys) >>> phys.peaks - array([ 477, 2120, 3253, 4128]) + array([ 477, 2120, 3253]) >>> phys.troughs - array([1413, 2611, 3756]) + array([1413, 2611]) Next, we'll move on to how you can load your data into a :py:class:`~.Physio` object in a more reproducible manner. Feel free to refer to the :ref:`api_ref` diff --git a/docs/user_guide/saving.rst b/docs/user_guide/saving.rst index d2086e7..506513a 100644 --- a/docs/user_guide/saving.rst +++ b/docs/user_guide/saving.rst @@ -31,13 +31,16 @@ If later on you want to reload the processed data you can do so: .. doctest:: >>> from peakdet import load_physio - >>> data = load_physio('out.phys') + >>> data = load_physio('out.phys', allow_pickle=True) -.. note:: +.. warning:: :py:func:`peakdet.save_physio` uses :py:func:`numpy.savez` to save the data objects, meaning the generated files can actually be quite a bit larger - than the original data, themselves! + than the original data, themselves! Moreover, you NEED to pass the + ``allow_pickle=True`` parameter; this is turned off by default for safety + reasons, as you should never load pickle files not generated by a trusted + source. Saving history ^^^^^^^^^^^^^^ From d0b03ceb3bf2799648087002bd95d3cf0f8dd952 Mon Sep 17 00:00:00 2001 From: Ross Markello Date: Thu, 14 May 2020 16:46:59 -0400 Subject: [PATCH 7/9] [FLK] Fix linting errors --- peakdet/modalities.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/peakdet/modalities.py b/peakdet/modalities.py index ac71c20..828ef82 100644 --- a/peakdet/modalities.py +++ b/peakdet/modalities.py @@ -12,14 +12,14 @@ def iHR(self, step=1, start=0, end=None, TR=None): time = np.arange(start - mod, end + mod + 1, self.TR, dtype='int') HR = np.zeros(len(time) - step) - for l in range(step, time.size): - inds = np.logical_and(self.rrtime >= time[l - step], - self.rrtime < time[l]) + for tpoint in range(step, time.size): + inds = np.logical_and(self.rrtime >= time[tpoint - step], + self.rrtime < time[tpoint]) relevant = self.rrint[inds] if relevant.size == 0: continue - HR[l - step] = (60 / relevant).mean() + HR[tpoint - step] = (60 / relevant).mean() return HR From 59d806a02332d5288840c35144311fdaa8028cc9 Mon Sep 17 00:00:00 2001 From: Ross Markello Date: Thu, 14 May 2020 16:52:19 -0400 Subject: [PATCH 8/9] [FIX] No sklearn --- peakdet/tests/data/ECG.phys | Bin 117413 -> 117398 bytes 1 file changed, 0 insertions(+), 0 deletions(-) diff --git a/peakdet/tests/data/ECG.phys b/peakdet/tests/data/ECG.phys index 5ddd3b0ea7382bf8e312973b1a498902d67b9e0a..3a61be3db2d42c7051ea2e0972a5f48d7179871c 100644 GIT binary patch delta 810 zcmZ2Fm3`V&_6ag_A`B^sC5d`@1(l2p0t_>XSQ$W|;20yAZdBW<#@KUAMuZ`)7^bEJ zEW^Oy0i~z!I>s1Q|7h*&&BuTu52L^^U57n?h0D^4~}4pJ4@d zB>|iCly+$BFqq-x(7~-~eDX!eZIyB(!7kk$6EAJGk5KpBRq!@8X2*Ton&-FccI>VX zxnTY4LakJNb%ZGyohrvm z-M^NJ7iE2$wC+X1xx)C|;#aMXIu(yNMFZScHqNhg+;~A;WENNBBaSo~4asRirxoMB zD6ew5sjJWu#k(TnM39@o>jQHVMPpr;F$d({-uHK+apbkF4fT~qbxo~`I#PL_N`go8 z4Rs8UsI5y?bJgZs;}ux7e&d?`mm9vWsXyHKYRi8vv;W_e8KYC~xNOi(Xx|}vl0!~S zU#IQv$|U{JH`WCcwD}@SV9+}ZTRvUce_hTJas4sI~fz^FCd{S>2|G-_laE6|m3`?{_6agv3=AoWC5d`@1(l6fTdf#-j&U$Bq!oks(;ppU46FY-Z*TM?1_lNP zMg|6MAf1s}T#{c@2~x1s$JhIafr!tlcUga;{yXNsJQVanEpAVxK~5N#ldXs6`l^d-><8>_b5o>QzCOx@$ikEHx5v zXzrFUtzk6&!q>TGNoZ8nqO)a+8-kNs0(f^n)i~$YvedGDFTaGS!My`@jO>z!FYh-J z{biQsG1KM!BPKq{qzYztR+;pijHtt$&;LBLel-0?Xv5`SpBdF+SS(h5mJg`+W@Zrq zdK(xj42leEUmq~91_p#769WSeP$W0CBoP*TODFjH-!Twqo2$FwXuty93t~|m^0`70 zYme|Ms;KbU3T#~9G4&F2SI+SV4h3a7%P(Vz> z$G(Fpm3QB6ja*pqd)FCXw<$`tb2QFzt?bpBd9Wdi>-3g?tm-cP7ZNzNgU*>e+f-NP8d^ET-ZF&#^SrX}re4ju+WjsYOg`OhfBL_6V&nQP=O?vHn|XJlkC0Dw zTQ<-ACXO(kHJ5f|wz`QvZN2cIujabeef6&#W^MasC#}@i`9GI0Y{?JRbhf&lg7t^~ zax^LKGd;3B)01aQ#&7xQi%&8pm`*#!2u-{J-i%Bl%!rsnPsYH=1A_)ers)=^80DnV VqZXlncY5I|MtQbPCxH>q008txW9 Date: Thu, 14 May 2020 17:16:15 -0400 Subject: [PATCH 9/9] [REF] Relicense to Apache 2.0 --- LICENSE | 875 +++++++++++------------------------------------- README.rst | 31 +- peakdet/info.py | 4 +- 3 files changed, 209 insertions(+), 701 deletions(-) diff --git a/LICENSE b/LICENSE index b743e04..261eeb9 100644 --- a/LICENSE +++ b/LICENSE @@ -1,674 +1,201 @@ -GNU GENERAL PUBLIC LICENSE - Version 3, 29 June 2007 - -Copyright (C) 2007 Free Software Foundation, Inc. -Everyone is permitted to copy and distribute verbatim copies -of this license document, but changing it is not allowed. - - Preamble - -The GNU General Public License is a free, copyleft license for -software and other kinds of works. - -The licenses for most software and other practical works are designed -to take away your freedom to share and change the works. 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We also recommend that a + file or class name and description of purpose be included on the + same "printed page" as the copyright notice for easier + identification within third-party archives. + + Copyright [yyyy] [name of copyright owner] + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. diff --git a/README.rst b/README.rst index 4f05db7..716bbc9 100644 --- a/README.rst +++ b/README.rst @@ -11,8 +11,8 @@ photoplethysmography, or electrocardiogram (ECG/EKG) monitors. :target: https://codecov.io/gh/rmarkello/peakdet .. image:: https://readthedocs.org/projects/peakdet/badge/?version=latest :target: http://peakdet.readthedocs.io/en/latest -.. image:: https://img.shields.io/badge/License-GPL%20v3-blue.svg - :target: https://www.gnu.org/licenses/gpl-3.0 +.. image:: https://img.shields.io/badge/license-Apache%202-blue.svg + :target: http://www.apache.org/licenses/LICENSE-2.0 .. _overview: @@ -55,31 +55,12 @@ anything you might like to work on. Alternatively, if you've found a bug, are experiencing a problem, or have a question, create a new issue with some information about it! -.. _acknowledgments: - -Acknowledgments ---------------- - -While this package was initially created in 2016, some of the behind-the-scenes -functions in the project were adopted from the `PhysIO `_ MATLAB toolbox. As such, -if you use this code it would be good to (1) provide a link back to the -``peakdet`` repository with the version of the code used, and (2) cite `their -paper `_ -([1]_): - -.. [1] Kasper, L., Bollmann, S., Diaconescu, A. O., Hutton, C., Heinzle, J., - Iglesias, S., ... & Stephan, K. E. (2017). The PhysIO toolbox for modeling - physiological noise in fMRI data. Journal of Neuroscience Methods, 276, - 56-72. - .. _licensing: License Information ------------------- -This codebase is licensed under the GNU General Public License version 3. -The full license can be found in the `LICENSE `_ file in the ``peakdet`` distribution. - -All trademarks referenced herein are property of their respective holders. +This codebase is licensed under the Apache License, Version 2.0. The full +license can be found in the `LICENSE `_ file in the ``peakdet`` distribution. You may also +obtain a copy of the license at: http://www.apache.org/licenses/LICENSE-2.0. diff --git a/peakdet/info.py b/peakdet/info.py index 0ee99f3..d48af12 100644 --- a/peakdet/info.py +++ b/peakdet/info.py @@ -5,7 +5,7 @@ MAINTAINER = 'Ross Markello' EMAIL = 'rossmarkello@gmail.com' VERSION = __version__ -LICENSE = 'GPLv3' +LICENSE = 'Apache-2.0' DESCRIPTION = """\ A toolbox for reproducible physiological data analysis\ """ @@ -48,6 +48,6 @@ CLASSIFIERS = [ 'Development Status :: 3 - Alpha', 'Intended Audience :: Science/Research', - 'License :: OSI Approved :: GNU General Public License v3 (GPLv3)', + 'License :: OSI Approved :: Apache Software License', 'Programming Language :: Python :: 3.6', ]