smftools.analysis.plot.histograms

histograms.py — Interval distribution histograms with rolling mean, peak calling, and optional Gaussian fit overlay.

Functions

gaussian_fit_plot(values, output_path[, ...])	Histogram with least-squares Gaussian fit overlay.
plot_interval_histogram(values, output_path)	Plot a histogram with optional rolling-mean overlay and peak annotations.

smftools.analysis.plot.histograms.plot_interval_histogram(values, output_path, title='', xlabel='Value', color='#1f77b4', integer_bins=False, hist_config=None, dpi=300, figsize=(3.5, 2.5))

Plot a histogram with optional rolling-mean overlay and peak annotations.

Return type:

None

Parameters

valuesnp.ndarray

1-D float array of observations.

output_pathPath

File to write.

titlestr

Axes title.

xlabelstr

x-axis label.

colorstr

Bar fill color.

integer_binsbool

If True, one bar per integer value (for count histograms).

hist_configdict, optional

Config from smftools.analysis.config.hmm_histogram.HISTOGRAM_CONFIGS [layer][hist_type]. Keys: bin_size_bp, rolling_window_bp, peak_kwargs, rolling_color, peak_color.

smftools.analysis.plot.histograms.gaussian_fit_plot(values, output_path, title='', xlabel='Center-to-center distance (bp)', color='#1f77b4', hist_config=None, fit_config=None, dpi=300, figsize=(3.5, 2.5))

Histogram with least-squares Gaussian fit overlay.

fit_config fields: fit_range_bp (tuple[float,float]), fit_color (str).

Return type:

None