improve f_zero slope error, increase trials for fi_curve_model
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a.ott
parent
2f0c19ea5a
commit
0dfff5768c
@ -321,7 +321,7 @@ class FICurveCellData(FICurve):
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class FICurveModel(FICurve):
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def __init__(self, model, stimulus_values, eod_frequency, trials=1):
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def __init__(self, model, stimulus_values, eod_frequency, trials=5):
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self.eod_frequency = eod_frequency
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self.model = model
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self.trials = trials
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35
Fitter.py
35
Fitter.py
@ -175,7 +175,9 @@ class Fitter:
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self.f_inf_slope = 0
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self.f_zero_values = []
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self.f_zero_slopes = []
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# self.f_zero_slopes = []
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self.f_zero_slope_at_straight = 0
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self.f_zero_straight_contrast = 0
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self.f_zero_fit = []
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self.tau_a = 0
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@ -200,7 +202,9 @@ class Fitter:
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self.f_zero_values = fi_curve.f_zero_frequencies
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self.f_zero_fit = fi_curve.f_zero_fit
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self.f_zero_slopes = [fi_curve.get_f_zero_fit_slope_at_stimulus_value(c) for c in self.fi_contrasts]
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# self.f_zero_slopes = [fi_curve.get_f_zero_fit_slope_at_stimulus_value(c) for c in self.fi_contrasts]
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self.f_zero_slope_at_straight = fi_curve.get_f_zero_fit_slope_at_straight()
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self.f_zero_straight_contrast = self.f_zero_fit[3]
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# around 1/3 of the value at straight
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# self.f_zero_slope = fi_curve.get_fi_curve_slope_at(fi_curve.get_f_zero_and_f_inf_intersection())
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@ -385,15 +389,13 @@ class Fitter:
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serial_correlation = model_baseline.get_serial_correlation(self.sc_max_lag)
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coefficient_of_variation = model_baseline.get_coefficient_of_variation()
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# f_infinities, f_infinities_slope = self.base_model.calculate_fi_markers(self.fi_contrasts, self.eod_freq)
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fi_curve_model = get_fi_curve_class(self.base_model, self.fi_contrasts, self.eod_freq)
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f_zeros = fi_curve_model.get_f_zero_frequencies()
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f_infinities = fi_curve_model.get_f_inf_frequencies()
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f_infinities_slope = fi_curve_model.get_f_inf_slope()
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f_zero_slopes = [fi_curve_model.get_f_zero_fit_slope_at_stimulus_value(x) for x in self.fi_contrasts]
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# f_zero_slopes = [fi_curve_model.get_f_zero_fit_slope_at_stimulus_value(x) for x in self.fi_contrasts]
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f_zero_slope_at_straight = fi_curve_model.get_f_zero_fit_slope_at_stimulus_value(self.f_zero_straight_contrast)
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# print("fi-curve features calculated!")
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# calculate errors with reference values
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error_bf = abs((baseline_freq - self.baseline_freq) / self.baseline_freq)
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error_vs = abs((vector_strength - self.vector_strength) / self.vector_strength)
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@ -404,14 +406,16 @@ class Fitter:
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error_sc = abs((serial_correlation[i] - self.serial_correlation[i]) / self.serial_correlation[i])
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error_sc = error_sc / self.sc_max_lag
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error_f_inf_slope = abs((f_infinities_slope - self.f_inf_slope) / self.f_inf_slope)
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error_f_inf_slope = abs((f_infinities_slope - self.f_inf_slope) / (self.f_inf_slope/20))
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error_f_inf = calculate_list_error(f_infinities, self.f_inf_values)
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error_f_zero_slopes = calculate_list_error(f_zero_slopes, self.f_zero_slopes)
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# error_f_zero_slopes = calculate_list_error(f_zero_slopes, self.f_zero_slopes)
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error_f_zero_slope_at_straight = abs(self.f_zero_slope_at_straight - f_zero_slope_at_straight) \
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/ (self.f_zero_slope_at_straight / 20)
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error_f_zero = calculate_list_error(f_zeros, self.f_zero_values)
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error_list = [error_bf, error_vs, error_sc, error_cv,
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error_f_inf, error_f_inf_slope, error_f_zero, error_f_zero_slopes]
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error_f_inf, error_f_inf_slope, error_f_zero, error_f_zero_slope_at_straight]
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if error_weights is not None and len(error_weights) == len(error_list):
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for i in range(len(error_weights)):
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@ -437,8 +441,8 @@ class Fitter:
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self.f_inf_slope, f_infinities_slope, error_f_inf_slope),
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"f-infinity values:\nexpected:", np.around(self.f_inf_values), "\ncurrent: ", np.around(f_infinities),
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"\nerror: {:.3f}\n".format(error_f_inf),
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"f-zero slopes:\nexpected:", np.around(self.f_zero_slopes), "\ncurrent: ", np.around(f_zero_slopes),
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"\nerror: {:.3f}".format(error_f_zero_slopes),
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"f-zero slope - expected: {:.0f}, current: {:.0f}, error: {:.3f}\n".format(
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self.f_zero_slope_at_straight, f_zero_slope_at_straight, error_f_zero_slope_at_straight),
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"f-zero values:\nexpected:", np.around(self.f_zero_values), "\ncurrent: ", np.around(f_zeros),
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"\nerror: {:.3f}".format(error_f_zero))
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return error_list
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@ -447,16 +451,17 @@ class Fitter:
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def calculate_list_error(fit, reference):
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error = 0
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for i in range(len(reference)):
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# TODO ??? add a constant to f_inf to allow for small differences in small values
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# example: 1 vs 3 would result in way smaller error.
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constant = 10
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error += abs((fit[i] - reference[i])+constant) / (abs(reference[i]) + constant)
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error += abs_freq_error(fit[i] - reference[i])
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norm_error = error / len(reference)
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return norm_error
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def abs_freq_error(diff, factor=10):
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return abs(diff) / factor
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def create_init_simples(x0, search_scale=3.):
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dim = len(x0)
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simplex = [[x0[0]/search_scale], [x0[0]*search_scale]]
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