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[frontend] FileStimulus is working for relacsed and nixed files

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This commit is contained in:
Jan Grewe 2020-08-06 19:41:05 +02:00
parent 07b60c6622
commit 38b73303c0
3 changed files with 121 additions and 20 deletions
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93
fishbook/frontend/relacs_classes.py
View File

@ -1,5 +1,5 @@
from .frontend_classes import Dataset, RePro, Stimulus
from .util import BoltzmannFit, unzip_if_needed, gaussian_kernel, zero_crossings, spike_times_to_rate
from .util import BoltzmannFit, unzip_if_needed, gaussian_kernel, zero_crossings, spike_times_to_rate, StimSpikesFile
import numpy as np
import nixio as nix
from scipy.stats import circstd
@ -638,18 +638,23 @@ class FileStimulusData:
self.__repros = None
self.__cell = dataset.cells[0] # Beware: Assumption that there is only a single cell
self.__all_spikes = None
self.__stimspikes = None
self._get_data()
def _get_data(self):
if not self.__dataset:
return
print("Find FileStimulus repro runs in this dataset!")
self.__repros, _ = RePro.find("FileStimulus", cell_id=self.__cell.id)
if not self.__dataset.has_nix:
self.__stimspikes = StimSpikesFile(self.__dataset.data_source)
for r in self.__repros:
if self.__dataset.has_nix:
spikes, contrasts, stims, delays, durations = self.__read_spike_data_from_nix(r)
else:
spikes, contrasts, stims, delays, durations = self.__read_spike_data_from_directory(r) # TODO
if spikes is not None and len(spikes) > 1:
spikes, contrasts, stims, delays, durations = self.__read_spike_data_from_directory(r)
if spikes is not None and len(spikes) > 0:
self.__spike_data.extend(spikes)
self.__contrasts.extend(contrasts)
self.__stimuli.extend(stims)
@ -659,19 +664,35 @@ class FileStimulusData:
continue
def __find_contrast(self, repro_settings, stimulus_settings, has_nix=True):
def read_contrast(str, has_nix):
if has_nix:
return float(str.split("+")[0]) * 100
else:
return float(str[:-1])
contrast = 0.0
if "project" in repro_settings.keys():
repro_settings = repro_settings["project"]
elif "Project" in repro_settings.keys():
repro_settings = repro_settings["Project"]
for k in repro_settings.keys():
if k.lower() == "contrast":
contrast = float(repro_settings[k].split("+")[0]) * (100 if has_nix else 1)
if contrast < 0.00001:
contrast = read_contrast(repro_settings[k], has_nix)
# fall back to the stimulus settings only for those when the contrast is zero in repro settings, it was probably mutable in relacs
if contrast < 0.0000001:
if "project" in repro_settings.keys():
stimulus_settings = stimulus_settings["project"]
elif "Project" in stimulus_settings.keys():
stimulus_settings = stimulus_settings["Project"]
for k in stimulus_settings.keys():
if k.lower() == "contrast":
contrast = float(stimulus_settings[k].split("+")[0]) * (100 if has_nix else 1)
contrast = read_contrast(stimulus_settings[k], has_nix)
return contrast
def __do_read_spike_data_from_nix(self, mt: nix.pycore.MultiTag, stimulus: Stimulus, repro: RePro):
spikes = None
spikes = np.empty(0)
contrast = 0.0
r_settings = yaml.safe_load(repro.settings.replace("\t", ""))
@ -719,22 +740,38 @@ class FileStimulusData:
mt = b.multi_tags[s.multi_tag_id]
sp, c, stim, delay, duration = self.__do_read_spike_data_from_nix(mt, s, repro)
spikes.append(sp)
contrasts.append(c)
stim_files.append(stim)
delays.append(delay)
durations.append(duration)
if len(sp) > 0:
spikes.append(sp)
contrasts.append(c)
stim_files.append(stim)
delays.append(delay)
durations.append(duration)
f.close()
return spikes, contrasts, stim_files, delays, contrasts
def __read_spike_data_from_directory(self, repro: RePro):
print("not yet, my friend!")
stimuli, _ = Stimulus.find(cell_id=repro.cell_id, repro_id=repro.id)
spikes = []
contrasts = []
stim_files = []
delays = []
durations = []
r_settings = yaml.safe_load(repro.settings.replace("\t", ""))
r_settings = r_settings["project"] if "project" in r_settings.keys() else r_settings
for s in stimuli:
s_settings = yaml.safe_load(s.settings.replace("\t", ""))
s_settings = s_settings["project"] if "project" in s_settings.keys() else s_settings
contrast = self.__find_contrast(r_settings, s_settings, False)
duration = float(s_settings["duration"][:-2]) / 1000
sp = self.__stimspikes.get(s.run, s.index)
if not sp or len(sp) < 1:
continue
contrasts.append(contrast)
delays.append(float(r_settings["before"][:-2]) / 1000)
durations.append(duration)
stim_files.append(s_settings["file"])
spikes.append(sp)
return spikes, contrasts, stim_files, delays, durations
def read_stimulus(self, index=0):
@ -768,6 +805,14 @@ class FileStimulusData:
else:
raise IndexError("FileStimulusData: index %i out of bounds for contrasts data of size %i" % (index, self.size))
def trial_duration(self, index=-1):
if index == -1:
return self.__durations
elif index >=0 and index < self.size:
return self.__durations[index]
else:
raise IndexError("FileStimulusData: index %i out of bounds for contrasts data of size %i" % (index, self.size))
def time_axis(self, index=-1):
"""
Get the time axis of a single trial or a list of time-vectors for all trials.
@ -790,6 +835,18 @@ class FileStimulusData:
raise IndexError("FileStimulusData: index %i out of bounds for time_axes of size %i" % (index, self.size))
def rate(self, index=-1, kernel_width=0.005):
"""[summary]
Args:
index (int, optional): [description]. Defaults to -1.
kernel_width (float, optional): [description]. Defaults to 0.005.
Raises:
IndexError: [description]
Returns:
[type]: [description]
"""
if index == -1:
time_axes = []
rates = []
@ -808,11 +865,11 @@ class FileStimulusData:
else:
raise IndexError("FileStimulusData: index %i out of bounds for time_axes of size %i" % (index, self.size))
if __name__ == "__main__":
# dataset = Dataset(dataset_id='2011-06-14-ag')
dataset = Dataset(dataset_id="2018-09-13-ac-invivo-1")
# dataset = Dataset(dataset_id='2013-04-18-ac')
# dataset = Dataset(dataset_id="2018-09-13-ac-invivo-1")
dataset = Dataset(dataset_id='2013-04-18-ac-invivo-1')
fi_curve = FileStimulusData(dataset)
embed()

46
fishbook/frontend/util.py
View File

@ -1,5 +1,8 @@
import numpy as np
import os
import subprocess
from scipy.optimize import curve_fit
from IPython import embed
def spike_times_to_rate(spike_times, time_axis, kernel_width=0.005):
"""Convert spike times to a rate by means of kernel convolution. A Gaussian kernel of the desired width is used.
@ -121,7 +124,7 @@ class BoltzmannFit:
"""
The underlying Boltzmann function.
.. math::
f(x) = y_max / \exp{-slope*(x-inflection}
f(x) = y_max / exp{-slope*(x-inflection}
:param x: The x values.
:param y_max: The maximum value.
@ -181,3 +184,44 @@ class BoltzmannFit:
xvalues = self.__x_sorted
return self.boltzmann(xvalues, *self.__fit_params)
class StimSpikesFile:
def __init__(self, filename):
if "stimspikes-1.dat" not in filename:
filename += os.path.join(os.path.sep, "stimspikes1.dat")
if not os.path.exists(filename):
raise ValueError("StimSpikesFile: the given file %s does not exist!" % filename)
self._filename = filename
self._data_map = self.__parse_file(filename)
def __parse_file(self, filename):
with open(filename, 'r') as f:
lines = f.readlines()
index_map = {}
trial_data = []
index = 0
trial = 0
for l in lines:
l = l.strip()
if "index:" in l:
if len(trial_data) > 0:
index_map[(index, trial)] = trial_data
trial_data = []
index = int(l[1:].strip().split(":")[-1])
if "trial:" in l:
if len(trial_data) > 0:
index_map[(index, trial)] = trial_data
trial_data = []
trial = int(l[1:].strip().split(":")[-1])
if len(l) > 0 and "#" not in l:
trial_data.append(float(l)/1000)
return index_map
def get(self, run_index, trial_index):
if tuple([run_index, trial_index]) not in self._data_map.keys():
print("Data not found for run %i and trial %i:" % (run_index, trial_index))
return None
return self._data_map[(run_index, trial_index)]

2
setup.py
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@ -6,7 +6,7 @@ assert(sys.version_info >= (3, 0))
__version__ = 0.1
# exec(open('fishbook/version.py').read())
requires = ['datajoint', 'nixio', 'numpy', 'PyYAML', 'scipy', 'backports-datetime-fromisoformat']
requires = ['datajoint', 'nixio', 'numpy', 'PyYAML', 'scipy', 'tqdm', 'yaml', 'backports-datetime-fromisoformat']
print(find_packages(exclude=['contrib', 'doc', 'tests*']))
setup(name='fishbook',