Plotting and Output Functions

class ShowPlot.Plot[source]

A class to create analysis output

PrintOutChimeraAttributeFileSCCC_Score(code_structure, sccc_list, listRB)[source]

Print out a Chimera attribute file that can be used for visual inspection of the information after Segment based cross-correlation (SCCC) calculation.

Arguments:
code_structure
name of the structure instance
sccc_list
SCCC score for each of the segment.
listRB
list of segment used for the SCCC calculation.
PrintOutChimeraCmdClusterAnalysis(cluster_output, path_dir, targetMap_location, file_name='chimera_cluster_color', load_map=True)[source]
Print out a Chimera command file that can be used for visual inspection of the information after the hierarchical clustering analysis.”.
Arguments:
cluster_output
List that contains the model and the related cluster index.
path_dir
path to ensemble directory
targetMap_location
path to target map location
file_name
Output file name
load_map
True will add the loading option to the command file.
PrintOutClusterAnalysis(cluster_output, file_name='cluster.out', write=False)[source]
Print our a txt file that contains the clustering information after hierarchical clustering analysis.”.
Arguments:
cluster_output
List that contains the model and the related cluster index.
file_name
Output file name
write
True will save the file.
SCCCHeatMap_fromSCCCList(sccc_list, trans=False)[source]
Return a matrix from a list of score.txt files as:
x= Structure Instances and y= Structure Instances segments scored
Arguments:
sccc_list
list of list of SCCC scores
trans
True will transpose the matrix.
SCCCHeatMap_fromSCCCfiles(list_file, trans=False)[source]
Return a matrix from a list of score.txt files as:
x= Structure Instances and y= Structure Instances segments scored
Arguments:
list_file
list of files
trans
True will transpose the matrix.
ShowGeneralMatrix(mxGen, file_name='HeatMap', save=False, range=(0, 1), figsize=(7, 5), cmap=<matplotlib.colors.LinearSegmentedColormap object>)[source]
Heat Map plot of a matrix.

Arguments:

mxGen
Generic Matrix. Use SCCCHeatMap_fromSCCCfiles or SCCCHeatMap_fromSCCCList to generate a matrix from a set of segment assessed with SCCC score.
name
Output file name (.pdf)
save
True will save a pdf file of the plot.
range
set the min and max score.
cmap
color palette to use. Choose form the one available in matplotlib or use cmp_Rainbow.
ShowHierarchicalClusterings(ranked_ensemble, mxRMSD, rms_cutoff, name='HierClustPlt', save=False, cluster_index=False, figsize=(4, 4), reverse=False)[source]
Plot the Calpha RMSD hierarchical clustering of the multiple “fits”.
Arguments:
ranked_ensemble
Input list of Structure Instances. It is list of fits obtained with Cluster.rank_fit_ensemble function.
mxRMSD
Pairwise RMSD matrix for all Structure Instance in the ensemble obtained as one Cluster.RMSD_ensemble function.
rms_cutoff
float, the Calpha RMSD cutoff based on which you want to cluster the solutions. For example 3.5 (for 3.5 A). Suggested value the mean of the pairwise RMSD matrix.
name
Output file name (.pdf)
save
True will save a pdf file of the plot.
cluster_index
True will return a list that contains the model and the related cluster index.
ShowRMSDmatrix(mxRMSD, name='RMSDmatrix', save=False)[source]
Plot the pairwise RMSD matrix for all Structure Instance in the ensemble.
Arguments:
mxRMSD
Pairwise RMSD matrix for all Structure Instance in the ensemble obtained as one Cluster.RMSD_ensemble function.
name
Output file name (.pdf)
save
True will save a pdf file of the plot.
cmp_Rainbow()[source]

return rainbow color map.