impact.plotting module¶

impact.plotting.generic_timecourse(impact_core_instance_list=None)¶

impact.plotting.get_colors(number_of_colors, colors=None, cl_scales=['8', 'qual', 'Set1'])¶

impact.plotting.order_preserve_sort(seq, idfun=None)¶

impact.plotting.printGenericTimeCourse_plotly(replicateTrialList=None, dbName=None, strainsToPlot=[], titersToPlot=[], secondary_y_axis_titers=None, pts_per_hour=4, output_type='html', stage_indices=None, stage=None, cl_scales=['10', 'qual', 'Paired'], colors=None, yieldFlag=False, titerFlag=True, endpointFlag=False, sortBy='strain_id', img_scale=1, fig_height=None, column_width=400, number_of_columns=3, horizontal_spacing=0.2, vertical_spacing=0.4, row_height=300, format='web', single_subplot=False, plot_curve_fit=False)¶

Parameters:

replicateTrialList: ~class`titer` A list of replicate_id trials to be plotted dbName : str The name/path of the db if you will be loading data strainsToPlot : list A list of the strain identifiers, a concatenation of the strain.name+id_1+id_2 titersToPlot : list A list of the titers to plot output_type : str The type of output (html, file, image, iPython) stage_indices : list of index pairs defining stages The indices of stages to be defined. This will be moved elsewhere stage : int The stage of interest (as defined in stage_indices) cl_scales : list of color scale identifiers colors : list of str indicating the color ‘rgb(0, 0, 0)’ yieldFlag : bool True to plot yield titerFlag : bool True to plot titer endpointFlag : bool True to plot endpoint, otherwise plot timecourse sortBy : str Identifier to plot by (strain.name, id_1, id_2, None) img_scale : int The output scale of the image fig_height : float The height of the figure column_width : float The width of each column number_of_columns : int The number of columns horizontal_spacing : float The horizontal spacing between subplots vertical_spacing : float The vertical spacing between subplots row_height : float The height of a row in the plot format : str The format settings to use, the only option is poster

impact.plotting.print_generic_timecourse_plotly(replicate_trial_list, product, colors, pts_per_hour, showlegend_flag, fig, sortBy, pltNum, number_of_columns, single_subplot, axis_params, chart_fonts, height, legend_params, plot_curve_fit, data_to_plot='titer')¶

impact.plotting.render_output_ploty(output_type, fig, number_of_columns=None, column_width_multiplier=None, img_scale=None)¶

impact.plotting.svg_plot(fig, **kwargs)¶

Generates an svg plot from a plotly figure

Parameters:	fig: plotly figure

impact.plotting.time_profile_traces(replicate_trials=None, feature='titer', analyte='OD600', colors=None, cl_scales=['8', 'qual', 'Set1'], label=<function <lambda>>, legendgroup=<function <lambda>>, showlegend=True, pts_per_hour=60)¶

impact.plotting.time_profile_traces_single_trials(replicate_trial=None, feature='titer', analyte='OD600', colors=None, cl_scales=['8', 'qual', 'Set1'], label=<function <lambda>>, legendgroup=<function <lambda>>, showlegend=True, pts_per_hour=60)¶

Return traces for the single trials which compose a replicate for a single analyte

Parameters:	replicate_trial (`ReplicateTrial`): replicate to plot feature (str): feature to plot analyte (str): analyte to plot colors (list): colors to use, will use cl_scales if none cl_scales (dict): colorlover set of colors label (function): lambda function to get identifiers from data legendgroup (function): showlegend (bool) pts_per_hour