def form_string_all_trials_perf(self, translated_trial_matrix):
"""Form a string with side perf and anova for all trials"""
side2perf_all = count_hits_by_type_from_trials_info(
translated_trial_matrix, split_key='rewside')
string_perf_by_side = self.form_string_perf_by_side(side2perf_all)
if len(translated_trial_matrix
) > self.cached_anova_len2 or self.cached_anova_text2 == '':
numericated_trial_matrix = TrialMatrix.numericate_trial_matrix(
translated_trial_matrix)
anova_stats = TrialMatrix.run_anova(numericated_trial_matrix)
self.cached_anova_text2 = anova_stats
self.cached_anova_len2 = len(translated_trial_matrix)
else:
anova_stats = self.cached_anova_text2
return 'All: ' + string_perf_by_side + '. Biases: ' + anova_stats
def form_string_all_trials_perf(self, translated_trial_matrix):
"""Form a string with side perf and anova for all trials"""
side2perf_all = count_hits_by_type_from_trials_info(
translated_trial_matrix,
split_key='rewside')
string_perf_by_side = self.form_string_perf_by_side(side2perf_all)
if len(translated_trial_matrix) > self.cached_anova_len2 or self.cached_anova_text2 == '':
numericated_trial_matrix = TrialMatrix.numericate_trial_matrix(
translated_trial_matrix)
anova_stats = TrialMatrix.run_anova(numericated_trial_matrix)
self.cached_anova_text2 = anova_stats
self.cached_anova_len2 = len(translated_trial_matrix)
else:
anova_stats = self.cached_anova_text2
return 'All: ' + string_perf_by_side + '. Biases: ' + anova_stats
def form_string_recent_trials_perf(self, translated_trial_matrix):
"""Form a string with side perf and anova for recent trials
cached in cached_anova_text3 and cached_anova_len3
"""
side2perf = count_hits_by_type_from_trials_info(
translated_trial_matrix.iloc[-60:], split_key='rewside')
string_perf_by_side = self.form_string_perf_by_side(side2perf)
if len(translated_trial_matrix) > self.cached_anova_len3 or self.cached_anova_text3 == '':
numericated_trial_matrix = TrialMatrix.numericate_trial_matrix(
translated_trial_matrix.iloc[-60:])
anova_stats = TrialMatrix.run_anova(numericated_trial_matrix)
self.cached_anova_text3 = anova_stats
self.cached_anova_len3 = len(translated_trial_matrix)
else:
anova_stats = self.cached_anova_text3
return 'Recent: ' + string_perf_by_side + '. Biases: ' + anova_stats
def form_string_recent_trials_perf(self, translated_trial_matrix):
"""Form a string with side perf and anova for recent trials
cached in cached_anova_text3 and cached_anova_len3
"""
side2perf = count_hits_by_type_from_trials_info(
translated_trial_matrix.iloc[-60:], split_key='rewside')
string_perf_by_side = self.form_string_perf_by_side(side2perf)
if len(translated_trial_matrix
) > self.cached_anova_len3 or self.cached_anova_text3 == '':
numericated_trial_matrix = TrialMatrix.numericate_trial_matrix(
translated_trial_matrix.iloc[-60:])
anova_stats = TrialMatrix.run_anova(numericated_trial_matrix)
self.cached_anova_text3 = anova_stats
self.cached_anova_len3 = len(translated_trial_matrix)
else:
anova_stats = self.cached_anova_text3
return 'Recent: ' + string_perf_by_side + '. Biases: ' + anova_stats
def form_string_unforced_trials_perf(self, translated_trial_matrix):
"""Exactly the same as form_string_all_trials_perf, except that:
We drop all trials where bad is True.
We use cached_anova_len1 and cached_anova_text1 instead of 2.
"""
side2perf = count_hits_by_type_from_trials_info(
translated_trial_matrix[~translated_trial_matrix.bad],
split_key='rewside')
string_perf_by_side = self.form_string_perf_by_side(side2perf)
if len(translated_trial_matrix) > self.cached_anova_len1 or self.cached_anova_text1 == '':
numericated_trial_matrix = TrialMatrix.numericate_trial_matrix(
translated_trial_matrix[~translated_trial_matrix.bad])
anova_stats = TrialMatrix.run_anova(numericated_trial_matrix)
self.cached_anova_text1 = anova_stats
self.cached_anova_len1 = len(translated_trial_matrix)
else:
anova_stats = self.cached_anova_text1
return 'UF: ' + string_perf_by_side + '. Biases: ' + anova_stats
def form_string_unforced_trials_perf(self, translated_trial_matrix):
"""Exactly the same as form_string_all_trials_perf, except that:
We drop all trials where bad is True.
We use cached_anova_len1 and cached_anova_text1 instead of 2.
"""
side2perf = count_hits_by_type_from_trials_info(
translated_trial_matrix[~translated_trial_matrix.bad],
split_key='rewside')
string_perf_by_side = self.form_string_perf_by_side(side2perf)
if len(translated_trial_matrix
) > self.cached_anova_len1 or self.cached_anova_text1 == '':
numericated_trial_matrix = TrialMatrix.numericate_trial_matrix(
translated_trial_matrix[~translated_trial_matrix.bad])
anova_stats = TrialMatrix.run_anova(numericated_trial_matrix)
self.cached_anova_text1 = anova_stats
self.cached_anova_len1 = len(translated_trial_matrix)
else:
anova_stats = self.cached_anova_text1
return 'UF: ' + string_perf_by_side + '. Biases: ' + anova_stats