def patient_graph_server(input_dict):
p1, p2 = graph_CFTR(
run_model_CFTR(input_dict, 20000, 120000,
200000), 'Variants_Smoking_and_Alcohol_CFTR_plot',
'Duct Modeling Differential Equation Analysis (Variants + Smoking + Alcohol)'
)
wt_results = run_model_CFTR(init_cond, 20000, 120000, 200000)
return patient_plot_CFTR(p1, p2, wt_results, None, None)
def patient_graph(self):
input_dict = copy.deepcopy(self.input_dict)
p1, p2 = graph_CFTR(
run_model_CFTR(input_dict, 20000, 120000,
200000), 'Variants_Smoking_and_Alcohol_CFTR_plot',
'Duct Modeling Differential Equation Analysis (Variants + Smoking + Alcohol)'
)
wt_results = run_model_CFTR(init_cond, 20000, 120000, 200000)
self.graphs['Patient'] = patient_plot_CFTR(p1, p2, wt_results, None,
None)
def generate_xd_demo_data(self):
# Run Mmdel with no influences
self.data['WT CFTR'] = run_model_CFTR(init_cond, 20000, 120000, 200000)
# Run model with variant influences
if self.input_dict['variant_adj'] != None:
variant_input_dict = copy.deepcopy(self.input_dict)
variant_input_dict['smoke_adj'] = None
variant_input_dict['alcohol_adj'] = None
self.data['Variants CFTR'] = run_model_CFTR(
variant_input_dict, 20000, 120000, 200000)
# Run model with smoking and variants
if self.input_dict['variant_adj'] != None and self.input_dict[
'smoke_adj'] != None:
variant_and_smoking_input_dict = copy.deepcopy(self.input_dict)
variant_and_smoking_input_dict['alcohol_adj'] = None
self.data['Variants & Smoking CFTR'] = run_model_CFTR(
variant_and_smoking_input_dict, 20000, 120000, 200000)
def generate_CFTR_graphs(self):
input_dict = copy.deepcopy(self.input_dict)
if self.input_dict['variant_adj'] == None:
# WT Function
if self.input_dict['smoke_adj'] == None and self.input_dict[
'alcohol_adj'] == None:
self.graphs['Patient'] = graph_CFTR(
run_model_CFTR(input_dict, 20000, 120000,
200000), 'WT_plot',
'Duct Modeling Differential Equation Analysis (WT)')
# Only Smoking
if self.input_dict['smoke_adj'] != None and self.input_dict[
'alcohol_adj'] == None:
self.graphs['Patient'] = graph_CFTR(
run_model_CFTR(input_dict, 20000, 120000,
200000), 'Smoking_CFTR_plot',
'Duct Modeling Differential Equation Analysis (WT + Smoking)'
)
# Only Alcohol
if self.input_dict['smoke_adj'] == None and self.input_dict[
'alcohol_adj'] != None:
self.graphs['Patient'] = graph_CFTR(
run_model_CFTR(input_dict, 20000, 120000,
200000), 'Alcohol_CFTR_plot',
'Duct Modeling Differential Equation Analysis (WT + Alcohol)'
)
if self.input_dict['variant_adj'] != None:
# Only Variant Input
if self.input_dict['smoke_adj'] == None and self.input_dict[
'alcohol_adj'] == None:
self.graphs['Patient'] = graph_CFTR(
run_model_CFTR(input_dict, 20000, 120000,
200000), 'Variants_CFTR_plot',
'Duct Modeling Differential Equation Analysis (Variants)')
# Variants and Smoking
if self.input_dict['smoke_adj'] != None and self.input_dict[
'alcohol_adj'] == None:
self.graphs['Patient'] = graph_CFTR(
run_model_CFTR(input_dict, 20000, 120000,
200000), 'Variants_And_Smoking_CFTR_plot',
'Duct Modeling Differential Equation Analysis (Variants + Smoking)'
)
# Variants and Alcohol
if self.input_dict['smoke_adj'] == None and self.input_dict[
'alcohol_adj'] != None:
self.graphs['Patient'] = graph_CFTR(
run_model_CFTR(input_dict, 20000, 120000,
200000), 'Variants_And_Alcohol_CFTR_plot',
'Duct Modeling Differential Equation Analysis (Variants + Alcohol)'
)
# Variants, Smoking, and Alcohol
if self.input_dict['smoke_adj'] != None and self.input_dict[
'alcohol_adj'] != None:
self.graphs['Patient'] = graph_CFTR(
run_model_CFTR(input_dict, 20000, 120000, 200000),
'Variants_Smoking_and_Alcohol_CFTR_plot',
'Duct Modeling Differential Equation Analysis (Variants + Smoking + Alcohol)'
)
def generate_source_array(input_data, key):
'''
Construct Arrays from Duct Model System Equations to pass along to Bokeh's ColumnDataSource
Parameters
----------
input_data : dict
Basic model parameters. New cell class with parameters instantiated each time function is called.
key : str
String referring to ion concentration in question. Used as a key to pull from generated nested arrays.
Returns
-------
choice_array : array
Selected array denoted by key provided of length len(time)
'''
choice_array = run_model_CFTR(input_data, 20000, 120000, 200000)[0][key]
if key == 'time':
choice_array /= 20000
return choice_array
def generate_source_array(input_data, key):
choice_array = run_model_CFTR(input_data, 20000,
120000, 200000)[0][key]
if key == 'time':
choice_array /= 20000
return choice_array
def generate_WT_graphs(self):
self.graphs['WT CFTR'] = graph_CFTR(
run_model_CFTR(init_cond, 20000, 120000, 200000), 'WT_CFTR_plot',
'Duct Modeling Differential Equation Analysis (WT)')
show(self.graphs['WT CFTR'][0])