-
Notifications
You must be signed in to change notification settings - Fork 2
/
testPython.py
396 lines (392 loc) · 22.2 KB
/
testPython.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
# Use minisHeadles method of the minis object in order to execute 'minis'
# programatically using Python. Input and output variables of the method
# are described below. A usage example of how to set up the input variable
# is given at the end of the file.
#
# [status, output] = minisHeadless(input)
# minisHeadless function executes minis software in Matlab environment.
#
# Input: input - a structure with the following fields:
#
# 'task' - A task to carry out (character array). Available task
# options are:
# 'preprocess' - preprocess current-clamp recording data.
# 'detection' - carry out detection of spontaneous postsynaptic
# potentials/currents in the whole-cell patch-clamp recording
# data.
# 'detectionHeadless' - carry out detection of spontaneous
# postsynaptic potentials/currents in the whole-cell
# patch-clamp recording data but without displaying any
# graphical windows or saving any of the data. In this case
# detection results are stored in the 'output' (1) variable.
# This mode can be useful when embedding minis detection
# algorithm within custom-written code.
# 'detectCompare' - carry out detection of spontaneous
# postsynaptic potentials/currents in the whole-cell
# patch-clamp recording data stored in target and noise files
# and compare the two.
# 'errorBounds' - estimate error bounds for automated simulated
# spontaneous postsynaptic potential distribution fitting.
# 'autoDistributionFit' - carry out an automated simulated
# spontaneous postsynaptic potential distribution fitting.
# 'simulation' - carry out simulation of spontaneous
# postsynaptic potentials followed by detection and detection
# performance evaluation.
# 'simulationHeadless' - carry out simulation of spontaneous
# postsynaptic potentials followed by detection and detection
# performance evaluation without invoking a GUI and without
# saving ABFs with simulated traces. In this case the
# simulation traces and detection performance results are
# stored in the 'output' (2) variable.
#
# 'loadTargetFileInput' - A full path to a target file (character
# array). If you are using minis in a detectionHeadless mode, you
# can supply a series data vector instead. In this case
# 'loadTargetFileInput' should be a structure with the following
# fields:
# 'dt' - a sampling interval in milliseconds (scalar).
# 'lActualEpisodes' - a number of recordings sweeps (scalar).
# 'sweep' - membrane potential data row vector (mV). You can
# populate with zeros if running in a voltage clamp mode.
# 'current' - membrane current data row vector (nA). You can
# populate with zeros if running in a current clamp mode.
# 'loadNoiseFileInput' - A full path to a noise file (character
# array). If you are using minis in a simulationHeadless mode,
# you can supply a series data vector instead. In this case
# 'loadNoiseFileInput' should be a structure with the following
# fields:
# 'dt' - a sampling interval in milliseconds (scalar).
# 'lActualEpisodes' - a number of recordings sweeps (scalar).
# 'sweep' - membrane potential data row vector (mV).
# 'current' - membrane current data row vector (nA). You can
# also populate with zeros.
#
# 'maxTimeToPeak' - the beginning of the search window for finding
# the amplitude, and the rise time. It is measured in time to the
# peak, ms (character array);
# 'baselineDuration' - the default duration of the baseline of a
# detected event, ms (character array);
# 'peakIntegrationPeriod' - the duration of the
# refractory/integration period of a minis-like event, ms
# (character array);
# 'Amplobound' - the lower bound on amplitude of a minis-like
# event, mV (character array);
# 'Ampupbound' - the upper bound on amplitude of a minis-like
# event, mV (character array);
# 'smoothWindow' - the element-wise size of the normal smoothing
# window (character array);
# 'RTint' - a character array representing the rise time interval
# of choice: '10-90%' for a 10-90% rise time (default) and
# '20-80%' for a 20-80% rise time.
# 'downGoing' - a logical representing the direction of synaptic
# events (up- or down-going). If true, events are treated as
# down-going and the voltage or current trace is inverted prior
# to running detection.
# 'voltageClamp' - a logical indicating that voltage clamp data is
# being analysed. If true, detection is performed on the current
# channel instead of the voltage channel (default is current
# clamp).
#
# 'RTbinSize' - Rise time classification histogram bin size in ms.
# It can either be '0.25' or '0.5' (character array; default is
# 0.5).
#
# 'startPulseTarget' - Beginning of (the first) pulse in the target
# file (s; character array; optional).
# 'endPulseTarget' - End of (the first) pulse in the target file
# (s; character array; optional).
# 'startGlitchTarget' - End of a glitch period in the target file
# (s; character array; optional).
# 'endGlitchTarget' - End of a glitch period in the target file (s;
# character array; optional).
# 'startPulseNoise' - Beginning of (the first) pulse in the noise
# file (s; character array; optional).
# 'endPulseNoise' - End of (the first) pulse in the noise file (s;
# character array; optional).
# 'startGlitchNoise' - End of a glitch period in the noise file (s;
# character array; optional).
# 'endGlitchNoise' - End of a glitch period in the noise file (s;
# character array; optional).
# 'pulseDuration' - Brief (second) pulse duration (ms; character
# array). Default value is '0.5'.
#
# 'loSimAmp' - Simulated amplitude lower bound (mV; character
# array).
# 'L' - the starting size of the electronic length of the dendritic
# cylinder in simulations (unitless). It corresponds to the real
# dendritic cylinder length (measured in micrometers) divided by
# the dendritic length constant (l/delta). The default value is 0.6.
# 'tau_m' - Passive membrane time constant (ms), lower limit
# (character array).
# 'tau_PSPm' - Passive membrane time constant (ms), upper limit
# (character array).
#
# 'distType' - Simulated minis distribution type fitted to
# experimental data during optimisation (character array).
# Available types are 'Normal', 'Bimodal Normal',
# 'Trimodal Normal', 'Quadrimodal Normal', 'Log Normal',
# 'Bimodal Log Normal', 'Trimodal Log Normal', 'Gaussian',
# 'Bimodal Gaussian', 'Trimodal Gaussian',
# 'Quadrimodal Gaussian', 'Skew-normal', 'Bimodal Skew-normal',
# 'Trimodal Skew-normal'. 'Quadrimodal Normal' is the default
# option.
# 'distBaseline' - Fitted distribution baseline (character array).
# Options are either 'Zero' (default) or 'Subtracted'. This
# option allows the user to add to the simulated distribution all
# the positive events after subtracting the two-dimensional
# amplitude and rise time noise distribution from the target
# distribution (Subtracted option). The default is Zero which
# does not add anything.
# 'SDupbound' - Membrane potential standard deviation upper bound
# based on 15 ms size window average (mV; character array). This
# is optional and if set to be an empty character array, it is
# not used in optimisation (by default).
# 'SDlobound' - Membrane potential standard deviation lower bound
# based on 15 ms size window average (mV; character array). This
# is optional and if set to be an empty character array, it is
# not used in optimisation (by default).
# 'maxErr' - Maximum combined SAD (character array).
# 'maxAmpErr' - Maximum amplitude SAD (character array).
# 'maxRTErr' - Maximum rise time SAD (character array).
# 'maxAmpBottomErr' - Maximum amplitude top 50% SAD (character
# array).
# 'maxAmpMidErr' - Maximum amplitude top 10% SAD (character array).
# 'maxAmpTopErr' - Maximum amplitude top 2% SAD (character array).
# 'maxDev' - Maximum combined MAD (character array).
# 'maxDevAmp' - Maximum amplitude MAD (character array).
# 'maxDevRT' - Maximum rise time MAD (character array).
# 'maxAmpBottomDev' - Maximum amplitude top 50% MAD (character
# array).
# 'maxAmpMidDev' - Maximum amplitude top 10% MAD (character array).
# 'maxAmpTopDev' - Maximum amplitude top 2% MAD (character array).
#
# 'filtering' - a character array that can be either set to 'on' or
# 'off' (default). If set to 'on', the electrophysiological data
# is band-stop filtered to remove frequency components defined in
# 'filtfs'. This parameter is used only when running minis in a
# detectionHeadless or simulationHeadless modes.
# 'filtfs' - frequencies to be filtered out if 'filtering' is set
# to 'on' (optional). It is a cell with a character array inside
# the brackets. The default value is {'50, 150'}. This parameter
# is used only when running minis in a detectionHeadless or
# simulationHeadless modes.
#
# 'options' - A structure variable to store optimisation options.
# It contains the following fields:
# 'bounds' - a row matrix with the lower (top row) and upper
# (bottom row) bounds on the simulated distribution parameters
# used during automated simualted distribution fitting.
# 'nGenerations' - a number of genetic algorithm generations
# (scalar).
# 'parallelCores' - task parallelisation (number of cores;
# character array). When entering the number of parallel cores,
# instead of giving a number, the user can enter 'min' or 'max'
# which would give the minimum or maximum available cores on
# the cluster profile (computer), respectively.
# 'fullParallel' - a logical with true corresponding to the
# maximum available number of parallel cores and false
# (default) using the number of cores specified in the
# 'parallelCores' field.
# 'tauRange' - a logical with true corresponding having the
# passive membrane time constant as an extra parameter
# controlled by the optimisation procedure. Default is false.
# 'cluster' - true or false for evaluating on a remote parallel
# cluster (false by default).
# 'clusterProfile' - specify the parallel cluster profile name
# (character array). Default is 'local'.
# 'cliff' - a logical with true corresponding to using cliff
# constraint (refer to 'minis' documentation; false by default).
# 'figureDisplay' - a logical for displaying figures during the
# optimisation process (true by default).
# 'SDlobound' - a logical for using lower bound on membrane
# potential standard deviation as another controlled parameter
# during optimisation.
# 'SDupbound' - a logical for using upper bound on membrane
# potential standard deviation as another controlled parameter
# during optimisation.
# 'estimateTauLo' - a logical for estimating passive membrane
# time constant lower limit based on measured decays of
# detected minis-like events. This field is used only during
# autoDistributionFitHeadless task. If specified to be true,
# the supplied range of membrane time constants in the
# Simulation Paprameters panel is overridden and a new range is
# established if 'tauRange' was set to be true.
# 'estimateTauHi' - a logical for estimating passive membrane
# time constant upper limit based on measured decays of
# detected minis-like events. This field is used only during
# autoDistributionFitHeadless task. If specified to be true,
# the supplied range of membrane time constants in the
# Simulation Paprameters panel is overridden and a new range is
# established if 'tauRange' was set to be true.
# 'optimisationData' - a character array containing optimisation
# data file path obtained in error bound estimation. Supply
# only when running autoDistributionFitHeadless task. It is an
# empty character array by default.
# 'resumeOptimisation' - a character array containing unfinished
# optimisation data file path obtained during previous
# optimisation. Supply only when running
# autoDistributionFitHeadless task. It is an empty character
# array by default.
# Output: output (1) - a structure with the following fields (produced only
# during the detectionHeadless mode, otherwise empty):
# 'minisArray' - a matrix with rows corresponding to the
# detected minis-like events sorted according their temporal
# order and columns (from left to right) corresponding to the
# following characteristics of detected event:
# (1) - the peak value, mV or nA;
# (2) - the peak time, ms;
# (3) - the peak index;
# (4) - the amplitude, mV;
# (5) - the baseline value, mV;
# (6) - the start of a baseline, ms;
# (7) - the end of a baseline, ms;
# (8) - the element-wise start of a baseline, ms;
# (9) - the element-wise end of a baseline, ms;
# (10) - the element-wise 0-100% rise time (from the start of
# the baseline to the peak).
# (11) - the 0-100% rise time, ms.
# (12) - the 10-90% rise time, ms.
# (13) - the 10% rise time mark, ms.
# (14) - the 50% rise time mark, ms.
# (15) - the 90% rise time mark, ms.
# (16) - the index of the 10% rise time mark.
# (17) - the index of the 50% rise time mark.
# (18) - the index of the 90% rise time mark.
# (19) - membrane potential or current value at the 10% rise
# time mark, mV or nA.
# (20) - membrane potential or current value at the 50% rise
# time mark, mV or nA.
# (21) - membrane potential or current value at the 90% rise
# time mark, mV or nA.
# (22) - 1/e decay, ms.
# 'waveform' - a structure containing the fields:
# 'averageTrace' is an average recording trace in mV or nA.
# 'riseTimeArray' is a vector with rise times corresponding
# to counts stored in the 'riseTimeDist' vector.
# 'riseTimeDist' is a vector with a rise time distribution of
# large (top 10%) amplitude minis-like events that were
# used for obtaining the average waveform.
# 'parameters' is a structure variable containing estimated
# waveform parameters 'peak' (mV or nA), 'BL' (baseline, mV
# or nA), 'Amp' (amplitude, mV or nA), 'risetime' (ms),
# 'tau_m' (effective dendritic membrane time constant, ms).
# Additional fields like averageAmp and medianAmp are also
# added which correspond to the mean and median amplitude
# of the top 10% of the largest detected minis-like events.
# 'spectrum' - a matrix composed of four row vectors. The first
# vector contains amplitudes. The second one contains a
# power spectrum which should correspond to decibels (dB).
# The third vector contains phase information. The fourth
# vector contains frequencies.
# output (2) - a structure with the following fields (produced only
# during the simulationHeadless mode, otherwise empty):
# 'simData' - a row matrix with the top row being the noise +
# simulated membrane potential data after band-stop filtering
# and smoothing performed by the detection algorithms and the
# bottom row being the current data.
# 'simDataRaw' - a row matrix with the top row being the noise +
# simulated membrane potential data after band-stop filtering
# and the bottom row being the current data.
# 'detectionPerformance' - a structure variable with the
# following fields:
# 'sensitivity' - true positive (hit) rate.
# 'specificity' - specificity or 1 - false positive (false
# alarm) rate.
# 'FPR' - false positive rate.
# 'dPrime' - sensitivity index.
# 'performance' - a row matrix containing logical indices
# corresponding to
# row 1: simulated event positions (peaks);
# row 2: hits (detected positions) + misses;
# row 3: hits (detected positions) + false alarms;
# row 4: hits (detected positions);
# row 5: misses;
# row 6: false alarms;
# row 7: correct rejections.
# 'falseI' - locations (indices) of prominent noise events.
# 'falseT' - times of prominent noise events
# 'detectionParameters' - a structure variable containing part
# of input parameters controling the detection task.
# 'simulationParameters' - a structure variable containing part
# of input parameters controling simulation of sEPSPs.
# 'optimisationParameters' - a structure variable containing
# part of input parameters controling the automated
# distribution fitting task.
# 'classificationParameters' - a structure variable containing
# part of input parameters controling distribution binning.
# 'filtfs' - band-stop filtering stop frequencies.
# 'simulatedEventInfo' - a matrix with rows corresponding to
# simulated events and columns corresponding to (1) minis
# count, (2) amplitude, (3) rise time, (4) electrotonic charge
# input site distance from the measuring site, (5) electrotonic
# length of the dendritic cylinder, (6) onset index, (7) onset
# time, (8) peak index, (9) peak time.
import pyabf
import struct
import minisPy as minis
import matlab
# Setup minis input structure variable
inputDict = {
'task': 'detectionHeadless', # 'preprocess', 'detection', 'detectionHeadless', 'detectCompare', 'errorBounds', 'autoDistributionFit', 'simulation', 'simulationHeadless'
'loadTargetFileInput': 'C:/Users/44079/Phd/previous/Guy_Major/Data/p103a_copy/data/optimisation/target/p103a_0084_088.abf',
'loadNoiseFileInput': 'C:/Users/44079/Phd/previous/Guy_Major/Data/p103a_copy/data/optimisation/noise/p103a_0100-0104.abf',
'tau_PSPm': '...',
'tau_m': '13.5288',
'L': '0.6',
'loSimAmp': '0.01',
'maxAmpBottomErr': '726.387',
'maxAmpBottomDev': '136.34',
'maxAmpTopErr': '120.003',
'maxAmpMidErr': '247.006',
'maxAmpMidDev': '36.3331',
'maxAmpTopDev': '19.9999',
'SDupbound': '...',
'maxErr': '2260.41',
'SDlobound': '...',
'maxRTErr': '939.702',
'maxAmpErr': '1001.71',
'maxDevAmp': '201.701',
'maxDevRT': '333.014',
'maxDev': '196.339',
'distBaseline': 'Subtracted', # 'Zero' or 'Subtracted'
'distType': 'Normal', # 'Normal', 'Bimodal Normal', 'Trimodal Normal', 'Quadrimodal Normal', 'Log Normal', 'Bimodal Log Normal', 'Trimodal Log Normal', 'Gaussian', 'Bimodal Gaussian', 'Trimodal Gaussian', 'Quadrimodal Gaussian', 'Skew-normal', 'Bimodal Skew-normal', 'Trimodal Skew-normal'
'voltageClamp': False, # True or False
'downGoing': False, # True or False
'pulseDuration': '0.5',
'RTbinSize': '0.5', # '0.25' or '0.5'
'RTint': '10-90%', # '10-90%' or '20-80%'
'endGlitchNoise': '...',
'startGlitchNoise': '...',
'endPulseNoise': '1.1,2.2',
'startPulseNoise': '0.05,1.65',
'endGlitchTarget': '...',
'startGlitchTarget': '...',
'endPulseTarget': '1.1,2.2',
'startPulseTarget': '0.05,1.65',
'smoothWindow': '1.5',
'Ampupbound': '10',
'Amplobound': '0.1',
'peakIntegrationPeriod': '2.5',
'baselineDuration': '2',
'maxTimeToPeak': '10',
'filtering': 'on',
'filtfs': '50, 150'
}
optionsDict = {
'bounds': matlab.double([[0, 0, 0.05, 0.0001, 0.0003, 0, 0, 0, -1, 0, 0, -0.0001, 0, 0, -1, 0, 0, -0.0001, 0, 0, -1, 0, 0, -0.0001],
[0, 0, 0.05, 0.0001, 0.0003, 0, 0.0001, 0.0001, 1, 0.0010, 0.0010, 0.0001, 0.0001, 0.0001, 1.0000, 0.0010, 0.0010, 0.0001, 0.0001, 0.0001, 1, 0.0010, 0.0010, 0.0001]]),
'nGenerations': 200,
'parallelCores': 'max',
'fullParallel': True,
'tauRange': True,
'cluster': False,
'cliff': False,
'figureDisplay': True,
'clusterProfile': 'local',
'SDlobound': False,
'SDupbound': False
}
inputDict.update({'options': optionsDict})
# Run minis
minisObj = minis.initialize()
minisOutput = minisObj.minisHeadless(inputDict, nargout = 2)