Merge pull request #162 from TAMUparametric/paper

Paper

src/energiapy/components/case_study.py

@@ -13,17 +13,19 @@
 from dataclasses import dataclass
 from typing import Union, Set, Dict, Tuple
 import copy
+from warnings import warn
+
 from ..components.scenario import Scenario
 from ..components.process import Process
 from ..components.resource import Resource
 from ..components.location import Location
-from ..components.result import Result
+from ..components.result import Result, Results
 
 from ..model.formulate import formulate as formulate_casestudy
 from ..model.solve import solve as solve_casestudy
 from ..model.formulate import Objective, ModelClass
 from ..model.constraints.constraints import Constraints
-from pyomo.environ import ConcreteModel, Suffix
+from pyomo.environ import ConcreteModel
 
 
 @dataclass
@@ -35,12 +37,16 @@ class CaseStudy:
         scenarios: Can be a list of scenarios generated apriori or a single scenario that you want to vary
         vary (str, optional): if single scenario, what needs to be varied. e.g. demand. Defaults to None
         vary_as (str, optional): what values to assign while varying. Should be a list of values to take. Defaults to None
+        formulations_dict (dict, optional): dictionary with pyomo instances. Defaults to None 
+        results_dict (Results, optional): Results type object, has multiple Result objects embedded. Defaults to None
 
     """
     name: str
     scenarios: Union[list, Scenario]
     vary: str = None
     vary_as: list = None
+    formulations_dict: dict = None
+    results_dict: Results = None
 
     def __post_init__(self):
 
@@ -99,11 +105,15 @@ def solve(self, solver: str, interface: str = 'pyomo', saveformat: str = None, p
         Returns:
             Result: result type object
         """
+        if self.formulations_dict is None:
+            warn('Instances have not been formulated yet, use .formulate() first')
+
         instances = list(self.formulations_dict.values())
         names = list(self.formulations_dict.keys())
 
-        self.results_dict = {names[i]: solve_casestudy(instance=instances[i], scenario=self.scenarios[i],
-                                                       solver=solver, name=names[i], interface=interface, saveformat=saveformat,
-                                                       print_solversteps=print_solversteps, log=log) for i in range(len(names))}
+        self.results_dict = Results(name=self.name + '_results', results={names[i]: solve_casestudy(instance=instances[i], scenario=self.scenarios[i],
+                                                                                                    solver=solver, name=names[
+            i], interface=interface, saveformat=saveformat,
+            print_solversteps=print_solversteps, log=log) for i in range(len(names))})
 
         return self.results_dict

src/energiapy/components/result.py

@@ -13,6 +13,7 @@
 import json
 import pickle
 from dataclasses import dataclass
+from typing import Dict
 
 
 @dataclass
@@ -145,3 +146,14 @@ def __hash__(self):
 
     def __eq__(self, other):
         return self.name == other.name
+
+
+@dataclass
+class Results:
+    """Contains multiple Result objects
+    Args:
+        name: name of the results object, inherits from CaseStudy
+        results: dictionary of Result objects. 
+    """
+    name: str
+    results: Dict[str, Result]

src/energiapy/plot/plot_location.py

@@ -0,0 +1,248 @@
+"""plotting module for location
+"""
+
+__author__ = "Rahul Kakodkar"
+__copyright__ = "Copyright 2023, Multi-parametric Optimization & Control Lab"
+__credits__ = ["Rahul Kakodkar", "Efstratios N. Pistikopoulos"]
+__license__ = "MIT"
+__version__ = "1.0.8"
+__maintainer__ = "Rahul Kakodkar"
+__email__ = "cacodcar@tamu.edu"
+__status__ = "Production"
+
+import matplotlib.pyplot as plt
+from matplotlib import rc
+
+from ..components.location import Location
+from ..components.process import Process
+from ..components.resource import Resource
+from ..components.case_study import CaseStudy
+from ..components.scenario import Scenario
+from ..utils.plot_utils import axis_formatter
+
+
+def capacity_factor(location: Location, process: Process, fig_size: tuple = (12, 6), font_size: int = 16, color: str = 'blue', usetex: bool = False):
+    """generates a plot for varying capacity factor of process
+
+    Args:
+        process (Process): process energiapy object
+        location (Location): location energiapy object
+        font_size (int, optional): font size. Defaults to 16.
+        fig_size (tuple, optional): figure size. Defaults to (12,6).
+        color (str, optional): color of plot. Defaults to 'blue'.
+        usetex (bool, optional): False, if using latex font, need Tex set up (prone to errors). Defaults to 'False'.
+    """
+
+    rc('font', **{'family': 'serif',
+       'serif': ['Computer Modern'], 'size': font_size})
+    rc('text', usetex=False)
+    fig, ax = plt.subplots(figsize=fig_size)
+    y_ = list(location.capacity_factor[process.name].values())
+    x_ = list(range(len(y_)))
+    ax.plot(x_, y_, linewidth=0.5, color=color)
+    ax = axis_formatter(axes=ax, xcord=x_, axis_labels='M')
+    plt.title(f'Conversion factor for {process.label} in {location.label}')
+    plt.ylabel("Normalized capacity factor")
+    plt.xlabel("Scheduling Horizon")
+    plt.grid(alpha=0.3)
+    plt.rcdefaults()
+    return
+
+
+def price_factor(resource: Resource, location: Location, fig_size: tuple = (12, 6), font_size: int = 16, color: str = 'blue', usetex: bool = False):
+    """generates a plot for varying price factor for purchase of resource
+
+    Args:
+        resource (Resource): resource energiapy object
+        location (Location): location energiapy object
+        font_size (int, optional): font size. Defaults to 16.
+        fig_size (tuple, optional): figure size. Defaults to (12,6).
+        color (str, optional): color of plot. Defaults to 'blue'.
+        usetex (bool, optional): False, if using latex font, need Tex set up (prone to errors). Defaults to 'False'.
+    """
+    rc('font', **{'family': 'serif',
+       'serif': ['Computer Modern'], 'size': font_size})
+    rc('text', usetex=False)
+    fig, ax = plt.subplots(figsize=fig_size)
+    y_ = list(location.price_factor[resource.name].values())
+    x_ = list(range(len(y_)))
+    ax.plot(x_, y_, linewidth=0.5, color=color)
+    ax = axis_formatter(axes=ax, xcord=x_, axis_labels='M')
+    plt.title(f'Price factor for {resource.label} in {location.label}')
+    plt.ylabel("Normalized cost factor")
+    plt.xlabel("Scheduling Horizon")
+    plt.grid(alpha=0.3)
+    plt.rcdefaults()
+    return
+
+
+def demand_factor(resource: Resource, location: Location,
+                  fig_size: tuple = (12, 6), font_size: int = 16, color: str = 'blue', usetex: bool = False):
+    """generates a plot for varying demand factor of resource
+
+    Args:
+        resource (Resource): resource energiapy object
+        location (Location): location energiapy object
+        font_size (int, optional): font size. Defaults to 16.
+        fig_size (tuple, optional): figure size. Defaults to (12,6).
+        color (str, optional): color of plot. Defaults to 'blue'.
+        usetex (bool, optional): False, if using latex font, need Tex set up (prone to errors). Defaults to 'False'.
+    """
+    rc('font', **{'family': 'serif',
+       'serif': ['Computer Modern'], 'size': font_size})
+    rc('text', usetex=False)
+    fig, ax = plt.subplots(figsize=fig_size)
+    y_ = list(location.demand_factor[resource.name].values())
+    x_ = list(range(len(y_)))
+    ax.plot(x_, y_, linewidth=0.5, color=color)
+    ax = axis_formatter(axes=ax, xcord=x_, axis_labels='M')
+    plt.title(f'Demand factor for {resource.label} in {location.label}')
+    plt.ylabel("Normalized demand factor")
+    plt.xlabel("Scheduling Horizon")
+    plt.grid(alpha=0.3)
+    plt.rcdefaults()
+    return
+
+
+def capex_factor(process: Process, location: Location,
+                 fig_size: tuple = (12, 6), font_size: int = 16, color: str = 'blue'):
+    """generates a plot for varying technology capital expenditure
+
+    Args:
+        process (Process): process energiapy object
+        location (Location): location energiapy object
+        font_size (int, optional): font size. Defaults to 16.
+        fig_size (tuple, optional): figure size. Defaults to (12,6).
+        color (str, optional): color of plot. Defaults to 'blue'.
+        usetex (bool, optional): False, if using latex font, need Tex set up (prone to errors). Defaults to 'False'.
+    """
+    rc('font', **{'family': 'serif',
+       'serif': ['Computer Modern'], 'size': font_size})
+    rc('text', usetex=False)
+    fig, ax = plt.subplots(figsize=fig_size)
+    y_ = list(location.capex_factor[process.name].values())
+    x_ = list(range(len(y_)))
+    ax.plot(x_, y_, linewidth=0.5, color=color)
+    ax = axis_formatter(axes=ax, xcord=x_, axis_labels='M')
+    plt.title(f'Capex factor for {process.label} in {location.label}')
+    plt.ylabel("Normalized capex factor")
+    plt.xlabel("Scheduling Horizon")
+    plt.grid(alpha=0.3)
+    plt.rcdefaults()
+    return
+
+
+def vopex_factor(process: Process, location: Location,
+                 fig_size: tuple = (12, 6), font_size: int = 16, color: str = 'blue'):
+    """generates a plot for varying technology variable operational expenditure
+
+    Args:
+        process (Process): process energiapy object
+        location (Location): location energiapy object
+        font_size (int, optional): font size. Defaults to 16.
+        fig_size (tuple, optional): figure size. Defaults to (12,6).
+        color (str, optional): color of plot. Defaults to 'blue'.
+        usetex (bool, optional): False, if using latex font, need Tex set up (prone to errors). Defaults to 'False'.
+    """
+    rc('font', **{'family': 'serif',
+       'serif': ['Computer Modern'], 'size': font_size})
+    rc('text', usetex=False)
+    fig, ax = plt.subplots(figsize=fig_size)
+    y_ = list(location.vopex_factor[process.name].values())
+    x_ = list(range(len(y_)))
+    ax.plot(x_, y_, linewidth=0.5, color=color)
+    ax = axis_formatter(axes=ax, xcord=x_, axis_labels='M')
+    plt.title(f'Vopex factor for {process.label} in {location.label}')
+    plt.ylabel("Normalized vopex factor")
+    plt.xlabel("Scheduling Horizon")
+    plt.grid(alpha=0.3)
+    plt.rcdefaults()
+    return
+
+
+def fopex_factor(process: Process, location: Location,
+                 fig_size: tuple = (12, 6), font_size: int = 16, color: str = 'blue'):
+    """generates a plot for varying technology fixed operational expenditure
+
+    Args:
+        process (Process): process energiapy object
+        location (Location): location energiapy object
+        font_size (int, optional): font size. Defaults to 16.
+        fig_size (tuple, optional): figure size. Defaults to (12,6).
+        color (str, optional): color of plot. Defaults to 'blue'.
+        usetex (bool, optional): False, if using latex font, need Tex set up (prone to errors). Defaults to 'False'.
+    """
+    rc('font', **{'family': 'serif',
+       'serif': ['Computer Modern'], 'size': font_size})
+    rc('text', usetex=False)
+    fig, ax = plt.subplots(figsize=fig_size)
+    y_ = list(location.fopex_factor[process.name].values())
+    x_ = list(range(len(y_)))
+    ax.plot(x_, y_, linewidth=0.5, color=color)
+    ax = axis_formatter(axes=ax, xcord=x_, axis_labels='M')
+    plt.title(f'Fopex factor for {process.label} in {location.label}')
+    plt.ylabel("Normalized fopex factor")
+    plt.xlabel("Scheduling Horizon")
+    plt.grid(alpha=0.3)
+    plt.rcdefaults()
+    return
+
+
+def availability_factor(resource: Resource, location: Location,
+                        fig_size: tuple = (12, 6), font_size: int = 16, color: str = 'blue', usetex: bool = False):
+    """generates a plot for varying availability factor of resource
+
+    Args:
+
+        resource (Resource): resource energiapy object
+        location (Location): location energiapy object
+        font_size (int, optional): font size. Defaults to 16.
+        fig_size (tuple, optional): figure size. Defaults to (12,6).
+        color (str, optional): color of plot. Defaults to 'blue'.
+        usetex (bool, optional): False, if using latex font, need Tex set up (prone to errors). Defaults to 'False'.
+    """
+    rc('font', **{'family': 'serif',
+       'serif': ['Computer Modern'], 'size': font_size})
+    rc('text', usetex=False)
+    fig, ax = plt.subplots(figsize=fig_size)
+    y_ = list(
+        location.availability_factor[resource.name].values())
+    x_ = list(range(len(y_)))
+    ax.plot(x_, y_, linewidth=0.5, color=color)
+    ax = axis_formatter(axes=ax, xcord=x_, axis_labels='M')
+    plt.title(f'Demand factor for {resource.label} in {location.label}')
+    plt.ylabel("Normalized availability factor")
+    plt.xlabel("Scheduling Horizon")
+    plt.grid(alpha=0.3)
+    plt.rcdefaults()
+    return
+
+
+def revenue_factor(resource: Resource, location: Location,
+                   fig_size: tuple = (12, 6), font_size: int = 16, color: str = 'blue', usetex: bool = False):
+    """generates a plot for varying revenue factor of resource
+
+    Args:
+
+        resource (Resource): resource energiapy object
+        location (Location): location energiapy object
+        font_size (int, optional): font size. Defaults to 16.
+        fig_size (tuple, optional): figure size. Defaults to (12,6).
+        color (str, optional): color of plot. Defaults to 'blue'.
+        usetex (bool, optional): False, if using latex font, need Tex set up (prone to errors). Defaults to 'False'.
+    """
+    rc('font', **{'family': 'serif',
+       'serif': ['Computer Modern'], 'size': font_size})
+    rc('text', usetex=False)
+    fig, ax = plt.subplots(figsize=fig_size)
+    y_ = list(
+        location.revenue_factor[resource.name].values())
+    x_ = list(range(len(y_)))
+    ax.plot(x_, y_, linewidth=0.5, color=color)
+    ax = axis_formatter(axes=ax, xcord=x_, axis_labels='M')
+    plt.title(f'Demand factor for {resource.label} in {location.label}')
+    plt.ylabel("Normalized revenue factor")
+    plt.xlabel("Scheduling Horizon")
+    plt.grid(alpha=0.3)
+    plt.rcdefaults()
+    return

src/energiapy/plot/plot_scenario.py

@@ -1,4 +1,4 @@
-"""plotting module
+"""plotting module for scenarios
 """
 
 __author__ = "Rahul Kakodkar"