"""
Copyright (C) 2013-2019 Calliope contributors listed in AUTHORS.
Licensed under the Apache 2.0 License (see LICENSE file).
plotting.py
~~~~~~~~~~~
Functionality to plot model data.
"""
import os
import re
import warnings
import plotly.offline as pltly
import jinja2
from calliope.exceptions import warn
from calliope.postprocess.plotting.capacity import plot_capacity
from calliope.postprocess.plotting.timeseries import plot_timeseries
from calliope.postprocess.plotting.transmission import plot_transmission
from calliope.postprocess.plotting.flows import plot_flows
from calliope.postprocess.plotting.util import type_of_script
def plot_summary(model, to_file=False, mapbox_access_token=None):
"""
Plot a summary containing timeseries, installed capacities, and
transmission plots. Returns a HTML string by default, returns None if
``to_file`` given (and saves the HTML string to file).
Parameters
----------
to_file : str, optional
Path to output file to save HTML to.
mapbox_access_token : str, optional
(passed to plot_transmission) If given and a valid Mapbox API
key, a Mapbox map is drawn for lat-lon coordinates, else
(by default), a more simple built-in map.
"""
subset = {"costs": ["monetary"]}
timeseries = _plot(*plot_timeseries(model, subset=subset), html_only=True)
capacity = _plot(*plot_capacity(model, subset=subset), html_only=True)
if "loc_coordinates" in model._model_data:
transmission = _plot(
*plot_transmission(
model, html_only=True, mapbox_access_token=mapbox_access_token
),
html_only=True,
)
else:
transmission = "<br><br><p>No location coordinates defined -<br>not plotting transmission.</p>"
template_path = os.path.join(
os.path.dirname(__file__), "..", "..", "config", "plots_template.html"
)
with open(template_path, "r") as f:
html_template = jinja2.Template(f.read())
if "solution_time" in model._model_data.attrs:
solution_time = model._model_data.attrs["solution_time"] / 60
time_finished = model._model_data.attrs["time_finished"]
result_stats = "taking {:.2f} minutes to solve, completed at {}".format(
solution_time, time_finished
)
else:
result_stats = "inputs only"
html = html_template.render(
model_name=model.model_config["name"],
calliope_version=model._model_data.attrs["calliope_version"],
result_stats=result_stats,
top=timeseries,
bottom_left=capacity,
bottom_right=transmission,
)
# Strip plotly-inserted style="..." attributes
html = re.sub(r'style=".+?"', "", html)
if to_file:
with open(to_file, "w") as f:
f.write(html)
else:
return html
def _plot(
data,
layout,
html_only=False,
to_file=False,
layout_updates=None,
plotly_kwarg_updates=None,
# kwargs are included as they get passed through from the
# plotting accessor method, but are not actually used
**kwargs,
):
# We will bee moving plotting out of Calliope core code (and a method of the model object)
# in 0.7.0; current implementation is now untested.
warnings.warn(
"Plotting will no longer be available as a method of the Calliope model object in"
"future versions of Calliope. In the meantime, as of v0.6.6, plotting is untested; this functionality should now be used with caution. We expect to reintroduce it as a seperate module in v0.7.0.",
FutureWarning,
)
plotly_kwargs = dict(
show_link=False,
config={
"displaylogo": False,
"modeBarButtonsToRemove": ["sendDataToCloud"],
},
)
if type_of_script() == "jupyter":
plotter = pltly.iplot
plotly_filename_key = "filename"
pltly.init_notebook_mode(connected=False)
else:
plotter = pltly.plot
plotly_filename_key = "image_filename"
plotly_kwargs["auto_open"] = True
plotly_kwargs["filename"] = "temp_plot.html"
if layout_updates:
layout = {**layout, **layout_updates}
if plotly_kwarg_updates:
plotly_kwargs = {**plotly_kwargs, **plotly_kwarg_updates}
if to_file:
filename, image_type = to_file.rsplit(".", 1)
# Plotly can only save certain file types
if image_type not in ["png", "jpeg", "svg", "webp"]:
raise TypeError(
"Unable to save plot as `{}`, choose from "
"[`png`, `jpeg`, `svg`, `webp`]".format(image_type)
)
if "updatemenus" in layout:
raise ValueError(
"Unable to save multiple arrays to SVG, pick one array only"
)
else:
plotly_kwargs.update(image=image_type)
plotly_kwargs[plotly_filename_key] = filename
if data:
if html_only:
return pltly.plot(
{"data": data, "layout": layout},
include_plotlyjs=False,
output_type="div",
**plotly_kwargs,
)
else:
plotter({"data": data, "layout": layout}, **plotly_kwargs)
else:
raise ValueError("No data to plot.")
[docs]class ModelPlotMethods:
def __init__(self, model):
self._model = model
_docstring_additions = """
html_only : bool, optional; default = False
Returns a html string for embedding the plot in a webpage
to_file : False or str, optional; default = False
Will save plot to file with the given name and extension.
`to_file='plot.svg'` to save to SVG, `to_file='plot.png'` for
a static PNG image.
Allowed file extensions are: ['png', 'jpeg', 'svg', 'webp'].
layout_updates : dict, optional
The given dict will be merged with the Plotly layout dict
generated by the Calliope plotting function, overwriting keys
that already exist.
plotly_kwarg_updates : dict, optional
The given dict will be merged with the Plotly plot function's
keyword arguments generated by the Calliope plotting function,
overwriting keys that already exist.
"""
def check_optimality(self):
termination = self._model._model_data.attrs.get(
"termination_condition", "did_not_yet_run"
)
# a MILP model which optimises to within the MIP gap, but does not fully
# converge on the LP relaxation, may return as 'feasible', not 'optimal'
if termination not in ["optimal", "did_not_yet_run", "feasible"]:
warn("Model termination condition was not optimal. Plotting may fail!")
[docs] def timeseries(self, **kwargs):
self.check_optimality()
data, layout = plot_timeseries(self._model, **kwargs)
return _plot(data, layout, **kwargs)
timeseries.__doc__ = plot_timeseries.__doc__.rstrip() + _docstring_additions
[docs] def capacity(self, **kwargs):
self.check_optimality()
data, layout = plot_capacity(self._model, **kwargs)
return _plot(data, layout, **kwargs)
capacity.__doc__ = plot_capacity.__doc__.rstrip() + _docstring_additions
[docs] def transmission(self, **kwargs):
self.check_optimality()
data, layout = plot_transmission(self._model, **kwargs)
return _plot(data, layout, **kwargs)
transmission.__doc__ = plot_transmission.__doc__.rstrip() + _docstring_additions
def flows(self, **kwargs):
self.check_optimality()
data, layout = plot_flows(self._model, **kwargs)
return _plot(data, layout, **kwargs)
flows.__doc__ = plot_flows.__doc__.rstrip() + _docstring_additions
[docs] def summary(self, **kwargs):
self.check_optimality()
return plot_summary(self._model, **kwargs)
summary.__doc__ = plot_summary.__doc__