File comparison¶

TRSFX.compare.corr_heatmap(df, output=None, title=None, vmin=0.2, vmax=1.0, cmap='RdYlBu_r', figsize=(10, 8), mask=True, **kwargs)¶

Plot and save a correlation matrix as a heatmap.

Parameters:

df (DataFrame) – Square correlation matrix with matching row/column labels
output (str | Path | None) – Output file path. Defaults to ./correlation_heatmap.png
title (str | None) – Plot title
vmin (float) – Minimum value for color scale
vmax (float) – Maximum value for color scale
cmap (str) – Matplotlib/seaborn colormap name
figsize (Tuple[int, int]) – Figure dimensions as (width, height) in inches
mask (bool) – If True, mask values outside [vmin, vmax] range
kwargs – Additional arguments passed to sns.heatmap

Returns:

Matplotlib figure object

Return type:

Figure

TRSFX.compare.map_correlation(mtz_files, labels=None, time_step=None, time_ranges=False, f=None, phi=None, d_min=None)¶

Compute pairwise map-map correlation matrix from MTZ files.

Parameters:

mtz_files (Sequence[str | Path]) – Sequence of paths to MTZ files containing map coefficients
labels (Optional[Sequence[str]]) – Labels for each file. If None, uses filenames as labels
f (str | None) – F column name. If None, auto-detected from first file
phi (str | None) – Phase column name. If None, auto-detected from first file
d_min (float | None) – Resolution cutoff in Angstroms. If None, uses all reflections

Returns:

Square correlation matrix with labels as row/column indices

Return type:

DataFrame

TRSFX.compare.trace(pattern, output_csv, start_idx=0, end_idx=None, log_space=False, plot=False)¶

Globs HDF5 files matching a pattern, computes frame-to-frame correlations for each, and streams results to a CSV.

Parameters:

Return type:

None