from pyomo.environ import SolverFactory solver = SolverFactory('glpk') import pandas as pd import pyomo.environ as pyo # Create a model model = pyo.ConcreteModel() ## Define variables #model.x = pyo.Var(within=pyo.NonNegativeReals) #model.y = pyo.Var(within=pyo.NonNegativeReals) ## Define objective #model.obj = pyo.Objective(expr=model.x + model.y, sense=pyo.minimize) ## Define constraints #model.con1 = pyo.Constraint(expr=model.x + 2 * model.y >= 4) #model.con2 = pyo.Constraint(expr=model.x - model.y <= 1) ## Select solver #solver = pyo.SolverFactory('glpk') ## Solve the problem #result = solver.solve(model) ## Display results #print('Status:', result.solver.status) #print('Termination Condition:', result.solver.termination_condition) #print('Optimal x:', pyo.value(model.x)) #print('Optimal y:', pyo.value(model.y)) #print('Optimal Objective:', pyo.value(model.obj)) class Scheduler: def __init__(self, case_file_path, session_file_path, patient_file_path): """ Read case and session data into Pandas DataFrames Args: case_file_path (str): path to case data in CSV format session_file_path (str): path to theatre session data in CSV format """ try: self.df_cases = pd.read_csv(case_file_path) except FileNotFoundError: print("Case data not found.") try: self.df_sessions = pd.read_csv(session_file_path) except FileNotFoundError: print("Session data not found") try: self.df_patients = pd.read_csv(patient_file_path) except FileNotFoundError: print("Patient data not found") #self.model = self.create_model() def date2int(date): d0 = pd.to_datetime("25/11/2024", dayfirst=True) delta = (pd.to_datetime(date, dayfirst=True) - d0).days day = delta%7 week = int((delta - day)/7) return week,day path = '/home/hmag/code/pyomo/data' my = Scheduler(path+'/cases.csv', path+'/sessions.csv', path+'/patients.csv') print(my.df_cases) print(my.df_sessions) #print(my.df_patients) #for i in my.df_patients: # print(i) print(my.df_cases['Date'][0]) date = my.df_cases['Date'][0] print(date2int(date))