VirtualMicrobes.plotting package

Submodules

VirtualMicrobes.plotting.Graphs module

class VirtualMicrobes.plotting.Graphs.AttributeMap(mol_class_dict, reactions_dict, species_markers)

Bases: object

activation_color(effect, domain=(-1, 1))

color_mol(mol)

color_mol_class(mc)

color_protein(g)

color_reaction(r)

init_color_maps(species_markers)

init_mol_class_color_dict(mol_class_dict)

protein_type_line_style(type_)

class VirtualMicrobes.plotting.Graphs.BindingNetwork(base_save_dir, name, attribute_dict=None, size=(35, 35), **kwargs)

Bases: VirtualMicrobes.plotting.Graphs.Network

draw_network(self_marker=None, edge_effect='effect')

init_network(cell, with_self_marker=True)

layout_network_positions(prog)

Compute and store node positions using a layout algorithm.

Parameters:prog (str) – layout algorithm

class VirtualMicrobes.plotting.Graphs.Genome(base_save_dir, name, attribute_dict, size=(10, 10), show=True, **kwargs)

Bases: VirtualMicrobes.plotting.Graphs.Grapher

plot_genome_structure(cell, labels, video=None, max_size=None)

Render the genome structure as a circular (plasmid-like) representation. :param cell: which genome is plotted

exception VirtualMicrobes.plotting.Graphs.GraphNotFoundError(value)

Bases: VirtualMicrobes.plotting.Graphs.GraphingError

class VirtualMicrobes.plotting.Graphs.Grapher(base_save_dir, name, show=True, attribute_dict=None, clean=True, create=True)

Bases: object

backup_plots()

change_save_location(base_dir=None, name=None, clean=False, create=True)

class_version = '1.0'

init_attribute_mapper(mol_class_dict, reactions_dict, species_markers)

init_save_dir(clean=False, create=True)

save_dir

save_fig(name=None, labels=[], title=None, suffix='.svg', copy_labels=None, **kwargs)

Render and save a figure.

Parameters:

• name (str) – base name of the figure
• labels (iterable) – additional labels in file name
• title (str) – printable title of figure
• suffix (str) – file extension suffix
• copy_labels (iterable) – additional labels for the filename of a copy of the figure

Returns:

Return type:

list of filenames of the saved figure(s)

save_fig2(ext, name=None, title=None, **kwargs)

Render and save a figure.

Parameters:

• name (str) – base name of the figure
• title (str) – printable title of figure
• suffix (str) – file extension suffix

Returns:

Return type:

filename of the saved figure

save_video(video=None, frame=None)

Concat last plot to existing video (or, if first plot is made, make single framed video)

Parameters:

• video (str) – alias to ffmpeg that is found during initialisation
• frane (str) – frame number
• suffix (str) – file extension suffix

Returns:

Return type:

filename of the saved figure

update_figure(show=None)

upgrade(odict)

Upgrading from older pickled version of class to latest version. Version information is saved as class variable and should be updated when class invariants (e.g. fields) are added. (see also __setstate__)

Adapted from recipe at http://code.activestate.com/recipes/521901-upgradable-pickles/

exception VirtualMicrobes.plotting.Graphs.GraphingError(value)

Bases: exceptions.Exception

class VirtualMicrobes.plotting.Graphs.Graphs(base_save_dir, name, utility_path, mol_class_dict, reactions_dict, population_markers, species_markers, show, clean=True, create=True, **kwargs)

Bases: VirtualMicrobes.plotting.Graphs.Grapher

Produces static and online graphs of simulated data.

add_grid_graphs_data(time_point, pop_grid_data_dict, small_mol_names, data_store, scaling_dict_updates, markers_range_dict)

add_mol_evo_time_course_data(time_point, ext_res_conc_dict)

add_multigraph(graph)

add_pop_stats_data(time, most_fecundant_death_rate, most_fecundant_production, data_store, high_freq_cutoff=10)

add_prot_grid_graphs_data(time_point, small_mol_names, reaction_dict, data_store)

change_save_location(base_save_dir=None, name=None, clean=False, create=True)

init_binding_network(show=None, clean=True, **kwargs)

init_genome_structure(show=None, clean=True, **kwargs)

init_grid_graphs(mol_class_dict, markers=[], nr_cols_markers=3, show=None, mol_classes_per_row=4, clean=True, **kwargs)

init_metabolic_network(metabolites, conversions, imports, show=None, clean=True, **kwargs)

init_phylo_tree_graph(show=None, clean=True, **kwargs)

init_pop_stats(species_markers, reactions_dict, mol_class_dict, clean=True, show=None, **kwargs)

init_prot_grid_graphs(mol_class_dict, reactions_dict, nr_cols=4, show=None, mol_classes_per_row=4, reactions_per_row=4, clean=True, **kwargs)

init_scaling_dict()

init_time_course_graph(show=None, clean=True, **kwargs)

line_colors(name, nr)

plot_binding_network(*args, **kwargs)

Parameters:

• cell – Who to plot
• prog – (???)
• save – Save the figure Y/N
• write – Save the network file (gml, dot, json, etc.)

Nodes: Pumping enzymes are BLUE squares (ip = importing pump, e-p = exporting pump) Generic enzymes are BLUE / TURQUOISE circles Specific enzymes are GREEN / YELLOW / RED circles TFs are BROWN diamonds Thick borders indicates self-binding

Node-labels: Labels: Metabolites with brackets are building blocks Metabolites with asterisks are energy carriers

Edges: Width shows the basal level of transcription for the TF Colours distinquish inhibiting (blue) vs activating (red) effects. Intermediates are white-ish.

!! Note: still needs the ReST references worked out !!

plot_genome_structure(**kwargs)

plot_grid_concentrations(dat)

plot_grid_graphs(*args, **kwargs)

plot_metabolic_network(*args, **kwargs)

plot_mol_class_data(ax, mol_tc_dict, **plot_params)

plot_pop_stats(*args, **kwargs)

plot_prot_data(ax, prot_pert_type_tc_dict, **plot_params)

plot_time_course(*args, **kwargs)

class VirtualMicrobes.plotting.Graphs.MetabolicNetwork(base_save_dir, name, mol_class_dict, conversions, imports, size=(30, 30), attribute_dict=None, **kwargs)

Bases: VirtualMicrobes.plotting.Graphs.Network

color_reactions(conversions, imports, building_blocks=[], self_marker=None, reac_color_func=None, mol_color_func=None, edge_color_func=None)

draw_network(reactions_dict=None, self_marker=None, building_blocks=None)

init_network(mol_class_dict, conversions, imports)

layout_network_positions()

class VirtualMicrobes.plotting.Graphs.MultiGraph(base_save_dir, name, rows, cols, row_heigth=2, col_width=4, attribute_dict=None, show=True, **kwargs)

Bases: VirtualMicrobes.plotting.Graphs.Grapher

add_axis(name, pos, rows=1, cols=1, min_max_y=None, nr_lines=0, auto_scale=True, **plot_params)

add_lines(ax_name, nr_lines, **line_customization)

append_data(axes_name, xdata, ydata)

append_to_axes(axes_name, xdata, ydata, line_in=[], autoscale=True)

append_to_lines(axes_name, xdat, ydata_dict, autoscale=True)

colors = <Mock name='mock.cm.get_cmap()()' id='140282440675472'>

cols

customize_lines(lines, markers=None, line_styles=None, marker_sizes=None, marker_edge_widths=None, colors=None)

fill_grid(pos, rows, cols)

grid_free(pos, rows, cols)

line_markers = <Mock name='mock.MarkerStyle.filled_markers' id='140282438615760'>

line_styles = ['-', ':', '--', '-.']

marker_edge_widths = [0.1]

marker_sizes = [2.0]

rows

tight_layout(**kwargs)

within_grid(pos, rows, cols)

class VirtualMicrobes.plotting.Graphs.MultiGridGraph(base_save_dir, name, rows, cols, row_heigth=4, col_width=4, attribute_dict=None, show=True, **kwargs)

Bases: VirtualMicrobes.plotting.Graphs.MultiGraph

classdocs

add_axis(name, pos, rows=1, cols=1)

append_data(axes_name, time_point, data)

append_to_axes(axes_name, time_point, data)

plot_in_axes(axes_name, cm_name, matrix_data=None, data_range=None, color_bar=True)

set_data_range(axes_name, _range)

class VirtualMicrobes.plotting.Graphs.Network(base_save_dir, name, attribute_dict, size=(10, 10), show=True, **kwargs)

Bases: VirtualMicrobes.plotting.Graphs.Grapher

add_self(marker)

clear_graph()

color_edge_direction(i)

e_attr_list(attr, selectors=[])

edges_with_attr_list(selectors=[])

gene_node_id(gene)

gene_node_label(gene_node_id, depth=1)

init_network()

metabolite_edge_width(bb, cell_bb=False)

n_attr_list(attr, selectors=[])

nodes_with_attr_list(selectors=[])

redraw_network(**kwargs)

type_shape(reac_type)

write_to_file(name=None, labels=[], suffix='.gml', **kwargs)

class VirtualMicrobes.plotting.Graphs.PhyloTreeGraph(base_save_dir, name, attribute_dict, show=True, **kwargs)

Bases: VirtualMicrobes.plotting.Graphs.Grapher

Plot phylogenetic trees and represent the data in nodes with different layout styles.

compress_root_branch(root_branch_dist=20)

metabolic_type_layout(node)

metabolic_with_lod_layout(node)

mutation_rates_layout(node, mut_type)

node_layouts = ['metabolism', 'trophic_type', 'metabolic_with_lod']

rate_features = ['point_mut_rate', 'chromosomal_mut_rate', 'stretch_mut_rate', 'sequence_mut_rate', 'chromosome_dup_rate', 'chromosome_del_rate', 'tandem_dup_rate', 'stretch_del_rate', 'external_hgt_rate', 'internal_hgt_rate']

save_fig(feature='metabolism', name=None, labels=[], suffix='.svg', rescale=None, dpi=10, **kwargs)

Render tree with layout function depending on the selected feature for tree representation.

Parameters:

• feature – feature selects for a specific layout function, determining node style
• name – name for saving
• labels – labels to appear in save file name
• suffix – suffix of save file name

select_layout_fn(data_type)

trophic_type_layout(node, trophic_type)

update(tree)

Set new ete_tree.

update_figure(show=None, feature='metabolism', **kwargs)

write_to_file(name=None, labels=[], suffix='.nw', **kwargs)

exception VirtualMicrobes.plotting.Graphs.PositionOutsideGridError(value)

Bases: VirtualMicrobes.plotting.Graphs.GraphingError

Module contents