Added python package architecture for main file

Corpus/main.py

@@ -0,0 +1,114 @@
+from component import *
+from pipe import *
+
+from pyomo.environ import *
+import pandas as pd
+
+
+class Modesto:
+    def __init__(self, graph):
+        """
+        This class allows setting up optimization problems for district energy systems
+
+        :param graph: Object containing structure of the network,
+        structure and parameters describing component models and
+        design parameters
+        """
+
+        self.model = AbstractModel()
+        # self.user_data = pd.DataFrame({'A' : []}) # TODO Better way to initialize empty df?
+        # self.weather_data = pd.DataFrame({'A' : []})
+
+    def build_opt(self):
+        """
+        Build the structure of the optimization problem
+        Sets up the equations without parameters
+
+        :return:
+        """
+        pass
+
+    def fill_opt(self):
+        """
+        Fill the optimization problem with all necessary parameters
+
+        :return:
+        """
+        pass
+
+    def solve(self):
+        """
+        Solve a new optimization
+
+        :return:
+        """
+        pass
+
+    def get_sol(self, name):
+        """
+        Get the solution of a variable
+
+        :param name: Name of the variable
+        :return: A list containing the optimal values throughout the entire horizon of the variable
+        """
+        pass
+
+    def opt_settings(self, objective=None, horizon=None, time_step=None, pipe_type=None):
+        """
+        Change the setting of the optimization problem
+
+        :param objective: Name of the optimization objective
+        :param horizon: The horizon of the problem, in seconds
+        :param time_step: The time between two points, in secinds
+        :param pipe_type: The name of the type of pipe model to be used
+        :return:
+        """
+        pass
+
+    def change_user_behaviour(self, comp, kind, new_data):
+        """
+        Change the user behaviour of a certain component
+
+        :param comp: Name of the component
+        :param kind: Name of the kind of user data (e.g. mDHW)
+        :param new_data: The new data, in a dataframe (index is time)
+        :return:
+        """
+        # TODO Is resampling possible for the new data in case it doesn't have the correct time step?
+        pass
+
+    def change_weather(self, new_data):
+        """
+        Change the weather
+
+        :param new_data: The new data that describes the weather, in a dataframe (index is time),
+        columns are the different required signals
+        :return:
+        """
+
+        # TODO Is resampling possible for the new data in case it doesn't have the correct time step?
+        pass
+
+    def change_design_param(self, comp, param, val):
+        """
+        Change a design parameter
+
+        :param comp: Name of the component
+        :param param: name of the parameter
+        :param val: New value of the parameter
+        :return:
+        """
+        pass
+
+    def change_initial_cond(self, comp, state, val):
+        """
+        Change the initial condition of a state
+
+        :param comp: Name of the component
+        :param state: Name of the state
+        :param val: New initial value of the state
+        :return:
+        """
+        pass
+
+