#! usr/bin/env python3
# -*- coding: utf-8 -*-
"""
**This module includes the following display utils:**
- plot_node_energetic_flows() : enables one to plot the energy flows through
an EnergyNode
- plot_energy_mix() : enables one to plot the energy flows connected to a
node
- plot_quantity() : enables one to plot easily a Quantitiy
- plot_quantity_bar() : enables one to plot easily a Quantitiy as a bar
- sum_quantities_in_quantity() : enables one to to plot several quantities
in one once the optimisation is done
..
Copyright 2018 G2Elab / MAGE
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
"""
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
from ...energy.energy_nodes import EnergyNode
from ...energy.units.production_units import ProductionUnit
from ...energy.units.storage_units import StorageUnit
from ...energy.units.consumption_units import ConsumptionUnit
from ..optimisation.elements import Quantity
__docformat__ = "restructuredtext en"
[docs]def plot_node_energetic_flows(node):
"""
**Description**
This function allows to plot the energy flows through an EnergyNode
The display is realized :
- with histograms for production and storage flow
- with dashed curve for consumption flow
:param node: EnergyNode
"""
matplotlib.style.use('seaborn')
if not isinstance(node, EnergyNode):
raise TypeError('The element {0} should be an EnergyNode.'.format(node))
energy_fig = plt.figure()
print(
"\nPreparing to plot the energetic flows through the node {0}.".format(
node.name))
cons = energy_fig.add_subplot(111)
previous_energy_production = [0] * node.time.LEN # Build the base to the
# bar graph
# For all production units connected to the node
flows = node.get_flows
for flow in flows:
print(("\tAdd power from {0}.".format(flow.parent.name)))
label = flow.parent.name
parent = flow.parent
# Get the power profiles
if isinstance(flow.value, list):
energy_flow = flow.value
elif isinstance(flow.value, dict):
energy_flow = list(flow.value.values())
# If production or import
if isinstance(parent, ProductionUnit) or node.is_import_flow(flow):
try:
plt.bar(node.time.I * node.time.DT, energy_flow,
width=0.8 * node.time.DT,
bottom=[previous_energy_production[t] for t
in range(node.time.LEN)],
label=label)
except IndexError:
plt.bar(node.time.I * node.time.DT, energy_flow,
width=0.8 * node.time.DT,
bottom=[previous_energy_production[t] for t
in range(node.time.LEN)],
label=label)
for t in range(node.time.LEN):
previous_energy_production[t] += energy_flow[t]
# If consumption or export
elif isinstance(parent, ConsumptionUnit) or node.is_export_flow(flow):
cons.plot(node.time.I * node.time.DT, energy_flow, marker='.',
label=label,
linewidth=0.8, linestyle='--')
# If storage
elif isinstance(parent, StorageUnit):
energy_discharge = list(max(-1 * p, 0) for p in energy_flow)
energy_charge = list(min(-1 * p, 0) for p in energy_flow)
# Plot the discharge
try:
plt.bar(node.time.I * node.time.DT, energy_discharge,
width=0.8 * node.time.DT,
bottom=[previous_energy_production[t] for t
in range(node.time.LEN)],
label=label + 'discharge')
except IndexError:
plt.bar(node.time.I * node.time.DT, energy_discharge,
width=0.8 * node.time.DT,
bottom=[previous_energy_production[t] for t
in range(node.time.LEN)],
label=label)
for t in range(node.time.LEN):
previous_energy_production[t] += energy_discharge[t]
# Plot the charge
plt.bar(node.time.I * node.time.DT, energy_charge,
width=0.8 * node.time.DT,
label=label + ' charge')
# for flow in node._exports:
# export = list(flow.value.values())
# cons.plot(export, marker='x', label='export')
plt.title(
'Power flow for the units connected to the node {0}'.format(node.name))
if node.time.DT == 1:
plt.xlabel('Time (hours)')
plt.ylabel("Hourly mean power (kW)")
elif node.time.DT == 24:
plt.xlabel('Time (days)')
plt.ylabel("Daily total energy (kWh)")
plt.legend()
return plt
[docs]def plot_energy_mix(node):
if not isinstance(node, EnergyNode):
raise TypeError('The element {0} should be an EnergyNode.'.format(node))
data = []
legend = []
_, ax = plt.subplots()
plt.axis('equal') # Should be a circle
flows = node.get_flows
for flow in flows:
if isinstance(flow.parent, ProductionUnit):
energy_prod = sum(flow.value.values())
data.append(energy_prod)
legend.append(flow.parent.name)
ax.pie(data, labels=legend, autopct='%1.1f%%')
plt.title('Energy mix of the node {0}'.format(node.name))
plt.legend()
[docs]def plot_quantity(time, quantity, fig=None, ax=None, color=None, label=None,
title=None):
"""
**Description**
Function that plots a OMEGAlpes.general.optimisation.elements.Quantity
**Parameters**
- time: TimeUnit for the studied horizon as defined in general.time
- quantity: OMEGAlpes.general.optimisation.elements.Quantity
- fig: Figure as defined in matplotlib.pyplot.Figure
- ax: axes as defined in matplotlib.pyplot.Axes
- color: color of the plot
- label: label for the quantity
- title: title of the plot
**Returns**
- arg1 the matplotlib.pyplot.Figure handle object
- arg2 the matplotlib.pyplot.Axes handle object
- arg3 the matplotlib.pyplot.Line2D handle object
"""
v = getattr(quantity, 'value')
if fig is None:
fig = plt.figure()
ax = fig.add_subplot(111)
if isinstance(fig, plt.Figure):
if ax is None:
ax = fig.add_subplot(111)
elif not isinstance(ax, plt.Axes):
raise ValueError(
'ax should be either NoneType or matplotlib.pyplot.Axes')
if isinstance(v, (list, np.ndarray)):
try:
ld = ax.plot(time.I * time.DT, v, 'x-', color=color,
label=label)
fig.canvas.draw()
except ValueError:
ld = ax.plot(np.arange(0, len(v) * time.DT, time.DT), v, 'x-',
color=color, label=label)
elif isinstance(v, dict):
ind = list(v.keys())
val = list(v.values())
lst = np.array([ind, val]).transpose()
# lst = np.array([ind, val], ndmin=2)
lst = lst[lst[:, 0].argsort()]
ind = lst[:, 0]
val = lst[:, 1]
ld = ax.plot(ind * time.DT, val, 'x-', color=color, label=label)
else:
raise TypeError(
'Type {0} is not supported for the plot'.format(
type(v)))
if title is None:
plt.title('Evolution of {0} over the studied period'.format(
quantity.name))
elif isinstance(title, str):
plt.title(title)
else:
TypeError('title should be either None or a string')
return ld, ax, fig
[docs]def plot_quantity_bar(time, quantity, fig=None, ax=None, color=None,
label=None, title=None):
"""
**Description**
Function that plots a OMEGALPES.general.optimisation.elements.Quantity
as a bar
**Attributes**
- quantity is the OMEGALPES.general.optimisation.elements.Quantity
- fig could be None, a matplotlib.pyplot.Figure or Axes for multiple
plots
**Returns**
- arg1 the matplotlib.pyplot.Figure handle object
- arg2 the matplotlib.pyplot.Axes handle object
- arg3 the matplotlib.pyplot.Line2D handle object
"""
v = getattr(quantity, 'value')
if fig is None:
fig = plt.figure()
ax = fig.add_subplot(111)
if isinstance(fig, plt.Figure):
if ax is None:
ax = fig.add_subplot(111)
elif not isinstance(ax, plt.Axes):
raise ValueError(
'ax should be either NoneType or matplotlib.pyplot.Axes')
if isinstance(v, (list, np.ndarray)):
try:
ld = ax.bar(time.I * time.DT, v, color=color, label=label)
fig.canvas.draw()
except ValueError:
ld = ax.bar(np.arange(0, len(v) * time.DT, time.DT), v,
color=color, label=label)
elif isinstance(v, dict):
ind = list(v.keys())
val = list(v.values())
lst = np.array([ind, val]).transpose()
# lst = np.array([ind, val], ndmin=2)
lst = lst[lst[:, 0].argsort()]
ind = lst[:, 0]
val = lst[:, 1]
ld = ax.bar(ind * time.DT, val, color=color, label=label)
else:
raise TypeError(
'Type {0} is not supported for the plot'.format(
type(v)))
if title is None:
plt.title('Evolution of {0} over the studied period'.format(
quantity.name))
elif isinstance(title, str):
plt.title(title)
else:
TypeError('title should be either None or a string')
return ld, ax, fig
[docs]def sum_quantities_in_quantity(quantities_list=[],
tot_quantity_name='sum_quantity'):
"""
**Description**
Function that creates a new quantity gathering several values of
quantities
Should be used in order to plot several quantities in one once the
optimisation is done
**Attributes**
* quantities : a list of Quantities
(OMEGALPES.general.optimisation.elements.Quantity)
* tot_quantity_name : string : name of the new quantity
**Returns**
- tot_quantity : the new quantity created and filled
"""
tot_q_value = [0] * quantities_list[0].vlen
qunit = quantities_list[0].unit
for q in quantities_list:
if isinstance(q, Quantity):
if q.unit == qunit:
for i in range(q.vlen):
tot_q_value[i] = tot_q_value[i] + q.value[i]
else:
TypeError("The unit {0} of the quantity {1} is not the same "
"as the first quantity {2} which unit is {3}"
"".format(q.unit, q.name, quantities_list[0].name,
qunit))
else:
TypeError("{0} should be a Quantity and is a {1}".format(q.name,
q.__class__))
tot_quantity = Quantity(value=tot_q_value, name=tot_quantity_name,
description='create a new quantity gathering '
'various quantities')
return tot_quantity