def plot_area(self, experiments, choice): filter_dict = fpi_util.categorize(experiments, choice) # Get the actual data from the fpiexperiment and assign them to the genotype categories genotype_dict = defaultdict(dict) genotype_dict.update((k, {}) for k in [item for item in Genotype]) for base_filter, genotypes in filter_dict.items(): for genotype, exp_list in genotypes.items(): genotype_dict[genotype][base_filter] = [] genotype_dict[genotype][base_filter] = [ exp.area for exp in exp_list if exp.area is not None ] fpi_util.clear_data(genotype_dict) # Compute the positions of the boxplots self._plot_dict(genotype_dict)
def plot_peak_latency(self, experiments, choice): filter_dict = fpi_util.categorize(experiments, choice) genotype_dict = defaultdict(dict) genotype_dict.update((k, {}) for k in [item for item in Genotype]) # Loading the data into the genotype dict for base_filter, genotypes in filter_dict.items(): for genotype, exp_list in genotypes.items(): genotype_dict[genotype][base_filter] = [] genotype_dict[genotype][base_filter] = [ exp.peak_latency for exp in exp_list if exp.peak_latency is not None ] fpi_util.clear_data(genotype_dict) self._plot_dict(genotype_dict)
def plot_peak_value(self, experiments, choice): filter_dict = fpi_util.categorize(experiments, choice) # Get the actual data from the fpiexperiment and assign them to the genotype categories # Get the actual data from the fpiexperiment and assign them to the genotype categories genotype_dict = defaultdict(dict) genotype_dict.update((k, {}) for k in [item for item in Genotype]) for base_filter, genotypes in filter_dict.items(): for genotype, exp_list in genotypes.items(): genotype_dict[genotype][base_filter] = [] genotype_dict[genotype][base_filter] = [ exp.max_df for exp in exp_list if exp.max_df is not None ] fpi_util.clear_data(genotype_dict) self._plot_dict(genotype_dict)
def plot_baseline(self, experiments, choice): """ :param experiments: FPIExperiment object list :param choice: A string returned from the util.BoxPlotChoices panel :return: """ # Get the options for the current category filter_dict = fpi_util.categorize(experiments, choice) # Get the actual data from the fpiexperiment and assign them to the genotype categories genotype_dict = defaultdict(dict) genotype_dict.update((k, {}) for k in [item for item in Genotype]) for base_filter, genotypes in filter_dict.items(): for genotype, exp_list in genotypes.items(): genotype_dict[genotype][base_filter] = [] genotype_dict[genotype][base_filter] = [ exp.mean_baseline for exp in exp_list if exp.mean_baseline is not None ] fpi_util.clear_data(genotype_dict) # Compute the positions of the boxplots self._plot_dict(genotype_dict)