def plot_price_periods(
plot_prices: plt.Subplot,
options: ForecastOptions,
) -> None:
# set bg color for all graphs
for plot in [plot_prices]:
plot.set_facecolor(options.bg_color)
# Remove all spines
for spine in plot.spines.values():
spine.set_visible(False)
plot_prices.set_facecolor(options.bg_color)
plot_prices.set_ylim(PRICE_Y_LIM)
plot_prices.set_xlim([-1, 12])
plot_prices.axes.set_yticks(np.arange(0, 701, 100))
plot_prices.grid(
axis="y",
linestyle="-",
linewidth=0.5,
color=colors.PRICE_GRID_COLOR,
alpha=colors.PRICE_GRID_ALPHA,
)
forecast = options.forecast
for pattern in forecast.patterns:
for week in pattern.potential_weeks:
_create_week_area(plot_prices, week, pattern.pattern)
big_pattern = utils.get_pattern(forecast, models.PricePatterns.BIGSPIKE)
if big_pattern.chance > 0:
_create_pattern_line(
plot_prices,
spike_breakdown=[x for x in forecast.spikes.big.breakdown],
spike_pattern=big_pattern,
spike_color=colors.BIG_SPIKE_COLOR,
)
small_pattern = utils.get_pattern(forecast,
models.PricePatterns.SMALLSPIKE)
if small_pattern.chance > 0:
_create_pattern_line(
plot_prices,
spike_breakdown=[x for x in forecast.spikes.small.breakdown],
spike_pattern=small_pattern,
spike_color=colors.SMALL_SPIKE_COLOR,
)
bottom_axis = plot_prices.axes
# the x locations for the bars
indTods = np.arange(PRICE_PERIOD_COUNT)
# Add the time of day labels for each bar
bottom_axis.axes.set_xlim(plot_prices.get_xlim())
bottom_axis.axes.set_xticks(indTods)
bottom_axis.axes.set_xticklabels(PRICE_TODS)
bottom_axis.spines["bottom"].set_position(("axes", -0.01))
# Create weekday labels
weekday_labels = bottom_axis.twiny()
# We need to make sure the limits match to line up with the bars
weekday_labels.set_xlim(plot_prices.get_xlim())
# Place the weekdays between the AM / PM values
weekday_labels.set_xticks([0.5, 2.5, 4.5, 6.5, 8.5, 10.5])
# Set the labels
weekday_labels.set_xticklabels(PRICE_DAYS)
# Move the weekday labels down a littls
weekday_labels.spines["bottom"].set_position(("axes", -0.06))
_create_weekday_grid(weekday_labels)
# style price axes
plot_prices.tick_params(
axis="y",
labelcolor=colors.PRICE_LABEL_COLOR,
labelsize=LABEL_SIZE,
labeltop=False,
labelbottom=False,
labelright=True,
labelleft=True,
bottom=False,
top=False,
left=False,
)
# style TOD labels
bottom_axis.tick_params(
axis="x",
labelcolor=colors.DAY_LABEL_COLOR,
labelsize=LABEL_SIZE,
labeltop=False,
labelbottom=True,
labelright=False,
labelleft=False,
bottom=False,
top=False,
left=False,
)
# style weekday labels
weekday_labels.tick_params(
axis="both",
labelcolor=colors.DAY_LABEL_COLOR,
labelsize=LABEL_SIZE,
labelbottom=True,
labeltop=False,
bottom=False,
top=False,
left=False,
)
# Style tod and day label for current price period
current_period = _plot_current_prices(plot_prices, options.ticker)
if current_period != -1:
bbox = dict(
boxstyle="round,pad=0.5",
color=colors.DAY_LABEL_COLOR,
)
current_tod_label = bottom_axis.xaxis.get_ticklabels()[current_period]
current_tod_label.set_color("white")
current_tod_label.set_bbox(bbox)
_add_cursor(plot_prices, current_period)
all_spines = itertools.chain(
plot_prices.spines.values(),
weekday_labels.spines.values(),
)
for spine in all_spines:
spine.set_visible(False)
def plot_pattern_chances(plot: plt.Subplot, forecast: models.Forecast) -> None:
total = 0.0
valid_patterns = sorted(
(x for x in forecast.patterns if x.chance != 0),
key=lambda x: x.chance,
reverse=True,
)
for i, potential_pattern in enumerate(valid_patterns):
if i > 0:
# Add a little bit of space between sections
total += 0.01
chance = potential_pattern.chance
# If the chance gets below 2.5%, the bar disappears, so we need to have a
# minimum visual value for it.
adjusted_chance = max(potential_pattern.chance, 0.015)
pattern_color = colors.PATTERN_COLORS[potential_pattern.pattern]
plot.barh(
0.5,
height=0.8,
width=adjusted_chance,
left=total,
color=colors.color(*pattern_color, alpha=chance),
linewidth=0,
)
patten_name = PATTERN_NAMES[potential_pattern.pattern]
plot.annotate(
f"{patten_name}: {utils.format_chance(chance)}",
(total + (adjusted_chance / 2), 0.5),
color="white",
alpha=0.75,
fontsize=LABEL_SIZE * chance**0.9 + LABEL_SIZE / 2,
fontweight="bold",
ha="center",
va="center",
)
total += adjusted_chance
plot.set_xlim((0, total))
plot.set_ylim((0, 1))
# remove axis labels
plot.tick_params(
axis="both",
labeltop=False,
labelbottom=False,
labelright=False,
labelleft=False,
top=False,
bottom=False,
left=False,
right=False,
)
plot.patch.set_visible(False)
for spine in plot.spines.values():
spine.set_visible(False)