def plot_ghi_curves(
clearsky_ghi: np.ndarray,
station_ghi: np.ndarray,
pred_ghi: typing.Optional[np.ndarray],
window_start: datetime.datetime,
window_end: datetime.datetime,
sample_step: datetime.timedelta,
horiz_offset: datetime.timedelta,
ax: plt.Axes,
station_name: typing.Optional[typing.AnyStr] = None,
station_color: typing.Optional[typing.AnyStr] = None,
current_time: typing.Optional[datetime.datetime] = None,
) -> plt.Axes:
"""Plots a set of GHI curves and returns the associated matplotlib axes object.
This function is used in ``draw_daily_ghi`` and ``preplot_live_ghi_curves`` to create simple
graphs of GHI curves (clearsky, measured, predicted).
"""
assert clearsky_ghi.ndim == 1 and station_ghi.ndim == 1 and clearsky_ghi.size == station_ghi.size
assert pred_ghi is None or (pred_ghi.ndim == 1
and clearsky_ghi.size == pred_ghi.size)
hour_tick_locator = matplotlib.dates.HourLocator(interval=4)
minute_tick_locator = matplotlib.dates.HourLocator(interval=1)
datetime_fmt = matplotlib.dates.DateFormatter("%H:%M")
datetime_range = pd.date_range(window_start, window_end, freq=sample_step)
xrange_real = matplotlib.dates.date2num(
[d.to_pydatetime() for d in datetime_range])
if current_time is not None:
ax.axvline(x=matplotlib.dates.date2num(current_time),
color="r",
label="current")
station_name = f"measured ({station_name})" if station_name else "measured"
ax.plot(xrange_real, clearsky_ghi, ":", label="clearsky")
if station_color is not None:
ax.plot(xrange_real,
station_ghi,
linestyle="solid",
color=station_color,
label=station_name)
else:
ax.plot(xrange_real,
station_ghi,
linestyle="solid",
label=station_name)
datetime_range = pd.date_range(window_start + horiz_offset,
window_end + horiz_offset,
freq=sample_step)
xrange_offset = matplotlib.dates.date2num(
[d.to_pydatetime() for d in datetime_range])
if pred_ghi is not None:
ax.plot(xrange_offset, pred_ghi, ".-", label="predicted")
ax.xaxis.set_major_locator(hour_tick_locator)
ax.xaxis.set_major_formatter(datetime_fmt)
ax.xaxis.set_minor_locator(minute_tick_locator)
hour_offset = datetime.timedelta(hours=1) // sample_step
ax.set_xlim(xrange_real[hour_offset - 1], xrange_real[-hour_offset + 1])
ax.format_xdata = matplotlib.dates.DateFormatter("%Y-%m-%d %H:%M")
ax.grid(True)
return ax
