magmap.stats.atlas_stats module

Low-level measurement of atlases and statistics generation.

Typically applied to specific types of atlases and less generalizable than measurements in :module:`vols`.

magmap.stats.atlas_stats.calc_sens_ppv(pos, true_pos, false_pos, false_neg)

Calculate sensitivity and positive predictive value (PPV), typically for assessing detection accuracy.

Parameters:

• pos (int) – Number of positives.

• true_pos (int) – Number of correct detections.

• false_pos (int) – Number of incorrect detections.

• false_neg (int) – Number of missed detections.

Returns:

Sensitivity, PPV, and summary string.

Return type:

float, float, str

magmap.stats.atlas_stats.meas_dice(mask1, mask2, img=None)

Measure Dice Similarity Coefficient (DSC) between two images.

Parameters:

• mask1 (np.ndarray) – Mask of first image.

• mask2 (np.ndarray) – Mask of second image with same shape as that of mask2.

• img (np.ndarray) – Intensity image whose values within each mask will be summed, of the same shape as that of the masks; defaults to None.

Returns:

float: DSC between the two images, either based directly on the mask volumes or weighted by intensities of img if given.

magmap.stats.atlas_stats.meas_improvement(path, col_effect, col_p, thresh_impr=0, thresh_p=0.05, col_wt=None, suffix=None, df=None)

Measure overall improvement and worsening for a column in a data frame.

Parameters:

• path (str) – Path of file to load into data frame.

• col_effect (str) – Name of column with metric to measure.

• col_p (str) – Name of column with p-values.

• thresh_impr (float) – Threshold of effects below which are considered improved.

• thresh_p (float) – Threshold of p-values below which are considered statistically significant.

• col_wt (str) – Name of column for weighting.

• suffix (str) – Output path suffix; defaults to None.

• df (pd.DataFrame) – Data fram to use instead of loading from path; defaults to None.

Returns:

Data frame with improvement measurements. The data frame will be saved to a filename based on path.

Return type:

pd.DataFrame

magmap.stats.atlas_stats.meas_landmark_dist(paths, spacing=None)

Measure distance between corresponding labels in two labels images.

Supports image transposition of the 2nd image by magmap.atlas.atlas_refiner() with settings from magmap.settings.config.transforms.

Parameters:

• paths (Sequence[str]) – Sequence of paths to image files loadable by SimpleITK.

• spacing (Optional[Sequence[float]], default: None) – Spacing/scaling in z,y,x; defaults to None.

Return type:

Optional[DataFrame]

Returns:

Data frame of output metrics.

magmap.stats.atlas_stats.meas_plot_coefvar(path, id_cols, cond_col, cond_base, metric_cols, composites, size_col=None, size=None, show=True)

Measure and plot coefficient of variation (CV) as a scatter plot.

CV is computed two ways:

• Based on columns and equation specified in composites, applied across all samples regardless of group

• For each metric in metric_cols, separated by groups

Parameters:

• path (str) – Path to data frame.

• id_cols (List[str]) – Sequence of columns to serve as index/indices.

• cond_col (str) – Name of the condition column.

• cond_base (str) – Name of the condition to which all other conditions will be normalized.

• metric_cols (List[str]) – Sequence of column names for which to compute z-scores.

• composites (List[Enum]) – Sequence of enums specifying the combination, typically from vols.MetricCombos.

• size_col (str) – Name of weighting column for coefficient of variation measurement; defaults to None.

• size (List[int]) – Sequence of width, height to size the figure; defaults to None.

• show (bool) – True to display the image; defaults to True.

magmap.stats.atlas_stats.meas_plot_zscores(path, metric_cols, extra_cols, composites, size=None, show=True)

Measure and plot z-scores for given columns in a data frame.

Parameters:

• path (str) – Path to data frame.

• metric_cols (List[str]) – Sequence of column names for which to compute z-scores.

• extra_cols (List[str]) – Additional columns to included in the output data frame.

• composites (List[Enum]) – Sequence of enums specifying the combination, typically from vols.MetricCombos.

• size (List[int]) – Sequence of width, height to size the figure; defaults to None.

• show (bool) – True to display the image; defaults to True.

magmap.stats.atlas_stats.plot_clusters_by_label(path, z, suffix=None, show=True, scaling=None)

Plot separate sets of clusters for each label.

Parameters:

• path (str) – Base path to blobs file with clusters.

• z (int) – z-plane to plot.

• suffix (str) – Suffix for path; defaults to None.

• show (bool) – True to show; defaults to True.

• scaling (List) – Sequence of scaling from blobs’ coordinate space to that of config.labels_img.

magmap.stats.atlas_stats.plot_intensity_nuclei(paths, labels, size=None, show=True, unit=None)

Plot nuclei vs. intensity as a scatter plot.

Parameters:

• paths (List[str]) – Sequence of paths to CSV files.

• labels (List[str]) – Sequence of label metrics corresponding to paths.

• size (List[int]) – Sequence of width, height to size the figure; defaults to None.

• show (bool) – True to display the image; defaults to True.

• unit (str) – Denominator unit for density plot; defaults to None.

Returns:

Data frame with columns matching labels for the given paths concatenated.

Return type:

pd.DataFrame

magmap.stats.atlas_stats.plot_region_development(metric, size=None, show=True)

Plot regions across development for the given metric.

Parameters:

• metric (str) – Column name of metric to track.

• size (List[int]) – Sequence of width, height to size the figure; defaults to None.

• show (bool) – True to display the image; defaults to True.

magmap.stats.atlas_stats.plot_unlabeled_hemisphere(path, cols, size=None, show=True)

Plot unlabeled hemisphere fractions as bar and line plots.

Parameters:

• path (str) – Path to data frame.

• cols (List[str]) – Sequence of columns to plot.

• size (List[int]) – Sequence of width, height to size the figure; defaults to None.

• show (bool) – True to display the image; defaults to True.

magmap.stats.atlas_stats.smoothing_peak(df, thresh_label_loss=None, filter_size=None)

Extract the baseline and peak smoothing quality rows from the given data frame matching the given criteria.

Parameters:

• df – Data frame from which to extract.

• thresh_label_loss (default: None) – Only check rows below or equal to this fraction of label loss; defaults to None to ignore.

• filter_size (default: None) – Only rows with the given filter size; defaults to None to ignore.

Returns:

New data frame with the baseline (filter size of 0) row and the row having the peak smoothing quality meeting criteria.