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])