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)