`splicejac.plot.plotting_util`

plotting utilities

Module Contents

`plot_setup`(adata[, cmap])	Assign a color to each cluster from a colormap
`jac_regr_cons`(adata, cluster)	Check the consistency of Jacobian regression by computing element-wise distance between Jacobians from different
`compare_wrong_signs`(j1, j2[, eps])	Count fraction of wrong signs between two matrices
`count_wrong_signs`(adata, cluster[, eps])	Quantify the fraction of wring signs between Jacobians of different simulations for the same cell state
`count_pos_eig`(adata, cluster)	Count the number of positive eigenvalues of the Jacobians of different simulations for the same cell state

splicejac.plot.plotting_util.plot_setup(adata, cmap=plt.cm.Set2.colors)

Assign a color to each cluster from a colormap Results are stored in adata.uns[‘colors’]

adata: ~anndata.AnnData: count matrix
cmap: pyplot colormap (default: plt.cm.Set2.colors): Colormap for cell state. To use another colormap, provide argument following the same syntax: plt.cm. + chosen_colormap + .colors. A list of accepted colormaps can be found at: https://matplotlib.org/stable/tutorials/colors/colormaps.html

None

splicejac.plot.plotting_util.jac_regr_cons(adata, cluster)

Check the consistency of Jacobian regression by computing element-wise distance between Jacobians from different simulations for the same cell state

dev: a list of element-wise difference between all pairs of Jacobians

splicejac.plot.plotting_util.compare_wrong_signs(j1, j2, eps=0.9)

Count fraction of wrong signs between two matrices

j1: ~numpy.ndarray: matrix 1
j2: ~numpy.ndarray: matrix 2
eps: float (default: 0.9): cutoff quantile to select only the largest elements (in absolute value) in the two matrices in the range [0,1]

perc_sign: percentage of wrong signs between the two matrices

splicejac.plot.plotting_util.count_wrong_signs(adata, cluster, eps=0.9)

Quantify the fraction of wring signs between Jacobians of different simulations for the same cell state

adata: ~anndata.AnnData: count matrix
cluster: str: cell state
eps: float (default: 0.9): cutoff quantile to select only the largest elements (in absolute value) in the two matrices in the range [0,1]

wrong_sign: a list of wrong sign percentages between all pairs of Jacobians

splicejac.plot.plotting_util.count_pos_eig(adata, cluster)

Count the number of positive eigenvalues of the Jacobians of different simulations for the same cell state

pos_eig: list with number of positive eigenvalues for each Jacobian matrix