Пример #1
0
                                2]  # get data for each bin only
            speedmean = np.nanmean(barray, axis=0)  # average speed in that bin
            stopsarraybeacon[bcount, tcount] = speedmean  # store speed
            bcount += 1
    return stopsarraybeacon


# ------------------------------------------------------------------------------ #

#GET AND STORE STOPS DATA

for dcount, day in enumerate(days):
    for mcount, mouse in enumerate(mice):
        try:
            saraharray = readhdfdata(
                filename, day, mouse,
                'raw_data')  # get raw datafile for mouse and day
        except KeyError:  # if data file doesnt exist...
            print('Error, no file')
            continue
        # make array of trial number per row of data in dataset
        trialarray = maketrialarray(
            saraharray)  # make array of trial number same size as saraharray
        saraharray[:,
                   9] = trialarray[:,
                                   0]  # replace trial number because of increment error (see README.py)

        trialarray = saraharray[:,
                                9]  # makes an array of trial number per row in saraharray
        trarray = np.arange(np.min(saraharray[:, 9]),
                            np.max(saraharray[:, 9] + 0.1), 1)
Пример #2
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    firststop_b = np.zeros((len(session_paths), 6, 2))
    firststop_b[:, :, :] = np.nan
    firststop_nb = np.zeros((len(session_paths), 6, 2))
    firststop_nb[:, :, :] = np.nan
    firststop_p = np.zeros((len(session_paths), 6, 2))
    firststop_p[:, :, :] = np.nan


# loop thorugh mice and days to get data
for session_path, session_paths in enumerate(mice):
    session_count = 0
    for dcount, day in enumerate(days):  #load mouse and day
        print('Processing...', day, mouse)
        #load HDF5 data set for that day and mouse
        try:
            saraharray = readhdfdata(filename, day, mouse, 'raw_data')
        except KeyError:
            print('Error, no file')
            continue
        dayb = day.encode('UTF-8')  #""""
        mouseb = mouse.encode(
            'UTF-8')  #required for importing string from marray in python3
        length = np.max(saraharray[:, 1])  # max track length
        trial = np.max(saraharray[:, 9])  # max number of trials
        dayss = array[
            dcount,
            mcount]  # array which has days to analyse (day with highest beaconed first stop on that track)
        trialarray = saraharray[:,
                                9]  # makes an array of trial number per row in saraharray
        trialno = np.max(
            saraharray[:, 9])  # total number of trials for that day and mouse