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<h1 class="title">Module <code>trend_classifier.visuals</code></h1>
</header>
<section id="section-intro">
<details class="source">
<summary>
<span>Expand source code</span>
</summary>
<pre><code class="python">import numpy as np
from matplotlib import pyplot as plt
from trend_classifier.types import FigSize
def _plot_detrended_signal(
x: list[float], y_de_trended: list[float], fig_size: FigSize = (10, 5)
) -> None:
"""Plot de-trended signal.
Args:
x: x values.
y_de_trended (np.ndarray): de-trended y values.
fig_size: size of the figure
"""
plt.subplots(figsize=fig_size)
plt.plot(x, y_de_trended, "b-") # noqa: FKA01
# add x- and y-axis labels
plt.xlabel("time", fontsize=14)
plt.ylabel("de-trended value", fontsize=14)
plt.show()
def _plot_segments(obj, fig_size: FigSize = (8, 4)) -> None:
"""Plot all segments and linear trend lines.
Args:
fig_size: size of the figure e.g. (8, 4)
"""
plt.subplots(figsize=fig_size)
plt.plot(obj.x, obj.y, color="#AAD", linestyle="solid")
for segment in obj.segments:
start = segment.start
stop = segment.stop
slopes = segment.slopes
xx = obj.x[start:stop]
yy = obj.y[start:stop]
fit = np.polyfit(x=xx, y=yy, deg=1)
fit_fn = np.poly1d(fit)
all_positive_slopes = all([v >= 0 for v in slopes])
all_negatives_slopes = all([v < 0 for v in slopes])
if fit[0] >= 0 and all_positive_slopes:
col = "g"
elif fit[0] < 0 and all_negatives_slopes:
col = "r"
else:
col = "#A66"
plt.vlines(start, min(obj.y), max(obj.y), "#CCC") # noqa: FKA01
plt.vlines(stop, min(obj.y), max(obj.y), "#CCC") # noqa: FKA01
plt.plot(
obj.x[start:stop],
fit_fn(obj.x[start:stop]),
color=f"{col}",
linestyle="--",
linewidth=3,
)
# add x- and y-axis labels
plt.xlabel("time", fontsize=14)
plt.ylabel("value", fontsize=14)
plt.show()
def _plot_segment(
obj,
idx: list[int] | int,
col: str = "red",
fig_size: FigSize = (10, 5),
) -> None:
"""Plot segment with given index or multiple segments with given indices.
Args:
idx: index of the segment or list of indices of segments
col: color of the segment
fig_size: size of the figure
"""
plt.subplots(figsize=fig_size)
plt.plot(obj.x, obj.y, color="#AAD", linestyle="solid")
if isinstance(idx, int):
idx = [idx]
for i in idx:
segment = obj.segments[i]
start = segment.start
stop = segment.stop
xx = obj.x[start:stop]
yy = obj.y[start:stop]
plt.plot(xx, yy, color=col, linestyle="-", linewidth=2)
plt.scatter(xx[0], yy[0], color="k", s=10)
plt.scatter(xx[-1], yy[-1], color="k", s=10)
# add x- and y-axis labels
plt.xlabel("time", fontsize=14)
plt.ylabel("value", fontsize=14)
plt.show()
def _plot_segment_with_trendlines_no_context(
obj,
idx: list[int] | int,
signal_color: str = "#ccc",
fig_size: FigSize = (10, 5),
) -> None:
"""Plot segment with given index or multiple segments with given indices.
Args:
idx: index of the segment or list of indices of segments
fig_size: size of the figure
"""
segment = obj.segments[idx]
segment_start = segment.start
segment_stop = segment.stop
xx = obj.x[segment_start:segment_stop]
yy = obj.y[segment_start:segment_stop]
plt.subplots(figsize=fig_size)
plt.plot(xx, yy, color=signal_color, linestyle="-", linewidth=2)
for i, (start, slope, offset) in enumerate(
zip(segment.starts, segment.slopes, segment.offsets) # noqa: FKA01
):
x = obj.x[start : obj.config.N + start]
y = slope * np.array(x) + offset
plt.plot(
x,
y,
linestyle="--",
linewidth=2,
label=f"trendline {i}",
)
# add x- and y-axis labels
plt.xlabel("time", fontsize=14)
plt.ylabel("value", fontsize=14)
plt.legend()
plt.show()</code></pre>
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<li><h3>Super-module</h3>
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<li><code><a title="trend_classifier" href="index.html">trend_classifier</a></code></li>
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