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improve f_zero slope error, increase trials for fi_curve_model

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a.ott 2020-05-18 09:46:06 +02:00
parent 2f0c19ea5a
commit 0dfff5768c
2 changed files with 21 additions and 16 deletions
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2
FiCurve.py
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@ -321,7 +321,7 @@ class FICurveCellData(FICurve):
class FICurveModel(FICurve): class FICurveModel(FICurve):
def __init__(self, model, stimulus_values, eod_frequency, trials=1): def __init__(self, model, stimulus_values, eod_frequency, trials=5):
self.eod_frequency = eod_frequency self.eod_frequency = eod_frequency
self.model = model self.model = model
self.trials = trials self.trials = trials

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