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@@ -0,0 +1,74 @@
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+
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+import numpy as np
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+
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+
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+
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+
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+# #expected signature is like this:
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+# def ctv_dummy(
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+# time_trace, sampling_period,
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+# first_frame, last_frame,
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+# stimulus_number, stim_on_times, stim_off_times,
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+# flags, p1):
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+# """
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+# dummy CTV to specify function call signature
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+# :param time_trace: iterable of numbers
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+# :param sampling_period: float, sampling period of <time_trace>, in ms
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+# :param first_frame: int, interpreted as a frame number, where frames are numbered 0, 1, 2...
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+# :param last_frame: int, interpreted as a frame number, where frames are numbered 0, 1, 2...
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+# :param stimulus_number: int, indicates the which stimulus to use, use 1 for first stimulus
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+# :param stim_on_times: list of floats, stimulus onset times, in ms
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+# :param stim_off_times: list of floats, stimulus offset times, in ms
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+# :param flags: FlagsManager object, is a mapping of flag names to flags values with additional functions
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+# :param p1: pandas.Series object, internal representation of data
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+# :rtype: list
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+# :return: one member, float
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+# """
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+# return [0]
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+
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+def ctvBente(time_trace, sampling_period,
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+ first_frame, last_frame,
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+ stimulus_number, stim_on_times, stim_off_times,
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+ flags, p1):
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+ """
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+ ana's method -222
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+ mean(13-16) - mean(6-9) 4 frames each
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+ <insert a brief description of the method here>
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+ :param time_trace: iterable of numbers
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+ :param first_frame: int, interpreted as a frame number, where frames are numbered 1, 2, 3...
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+ :param last_frame: int, interpreted as a frame number, where frames are numbered 1, 2, 3...
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+ :param sampling_period: float, sampling period of <time_trace>, in ms
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+ :param stim_on_times: list of floats, stimulus onset times, in ms
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+ :param stim_off_times: list of floats, stimulus offset times, in ms
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+ :param flags: FlagsManager object, is a mapping of flag names to flags values with additional functions
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+ :param p1: pandas.Series object, internal representation of data
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+ :return: float
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+ """
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+ # print('**************************** running ctvBente now: ')
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+ # print('len time trace is: ', str(len(time_trace)))
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+
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+
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+ output = np.mean(time_trace[30:40]) - np.mean(time_trace[10:20])
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+ return [output]
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+
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+
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+def myownctv22(time_trace, sampling_period,
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+ first_frame, last_frame,
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+ stimulus_number, stim_on_times, stim_off_times,
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+ flags, p1):
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+ """
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+ ana's method -222
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+ mean(13-16) - mean(6-9) 4 frames each
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+ <insert a brief description of the method here>
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+ :param time_trace: iterable of numbers
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+ :param first_frame: int, interpreted as a frame number, where frames are numbered 1, 2, 3...
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+ :param last_frame: int, interpreted as a frame number, where frames are numbered 1, 2, 3...
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+ :param sampling_period: float, sampling period of <time_trace>, in ms
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+ :param stim_on_times: list of floats, stimulus onset times, in ms
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+ :param stim_off_times: list of floats, stimulus offset times, in ms
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+ :param flags: FlagsManager object, is a mapping of flag names to flags values with additional functions
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+ :param p1: pandas.Series object, internal representation of data
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+ :return: float
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+ """
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+ output = np.mean(time_trace[30:40]) - np.mean(time_trace[5:95])
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+ return [output]
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