ecoli.analysis.antibiotics_colony.timeseries

ecoli.analysis.antibiotics_colony.timeseries.make_tag_video(data, metadata, tag_colors, out_prefix, conc=False, min_color=(0, 0, 0), show_membrane=False, highlight_agent=None)[source]

Make a video of snapshot images that span a replicate for a condition. In each of these videos, cells will be will be colored with highlight_color and intensity corresponding to their value of highlight_column.

Parameters:

  • data (pandas.DataFrame) – DataFrame where each row is an agent and each column is a variable of interest. Must have these columns: ‘Time’, ‘Death’, ‘Agent ID’, ‘Boundary’, ‘Condition’, and ‘Seed’. 1 condition/seed at a time.

  • metadata (dict[str, dict[str, dict[str, Any]]]) – Nested dictionary where each condition is an outer key and each initial seed is an inner key. Each seed point to a dictionary with the following keys: ‘bounds’ is of the form [x, y] and gives the dimensions of the spatial environment and ‘fields’ is a dictionary timeseries of the ‘fields’ Store for that condition and initial seed

  • tag_colors (dict[str, Any]) – Mapping column names in data to either RGB tuples or dictionaries containing the cmp and norm keys for the matplotlib.colors.Colormap and matplotlib.colors.Normalize instances to use for that tag If dictionaries are used, the min_color key is overrriden

  • conc (bool) – Whether to normalize by volume before plotting

  • min_color (Any) – Color for cells with lowest highlight_column value (default black)

  • out_prefix (str) – Prefix for output filename

  • show_membrane (bool) – Whether to draw outline for agents

  • figsize – Desired size of entire figure

  • highlight_agent – Mapping of agent IDs to membrane_color and membrane_width. Useful for highlighting specific agents, with rest using defaults

Return type:

None

ecoli.analysis.antibiotics_colony.timeseries.plot_field_snapshots(data, metadata, highlight_lineage=None, highlight_color=(1, 0, 0), min_pct=1, max_pct=1, colorbar_decimals=1, return_fig=False, n_snapshots=5, figsize=(9, 1.75))[source]

Plot a row of snapshot images that span a replicate for each condition. In each of these images, the cell corresponding to a highlighted lineage is colored while the others are white.

Parameters:

  • data (pandas.DataFrame) – DataFrame where each row is an agent and each column is a variable of interest. Must have these columns: ‘Time’, ‘Death’, ‘Agent ID’, ‘Boundary’, ‘Condition’, and ‘Seed’. 1 condition/seed at a time.

  • metadata (dict[str, dict[str, dict[str, Any]]]) – Nested dictionary where each condition is an outer key and each initial seed is an inner key. Each seed point to a dictionary with the following keys: ‘bounds’ is of the form [x, y] and gives the dimensions of the spatial environment and ‘fields’ is a dictionary timeseries of the ‘fields’ Store for that condition and initial seed

  • highlight_lineage (str | None) – Agent ID to plot lineage trace for

  • highlight_color (tuple) – Color to plot highlight lineage with (default red)

  • min_pct – Percent of minimum field concentration to use as minimum value in colorbar (1 = 100%)

  • max_pct – Percent of maximum field concentration to use as maximum value in colorbar (1 = 100%)

  • colorbar_decimals – Number of decimals to include in colorbar labels.

  • return_fig – Whether to return the Figure

  • n_snapshots – Number of equally-spaced (temporally) snapshots

  • figsize – Desired size of entire figure

Return type:

None

ecoli.analysis.antibiotics_colony.timeseries.plot_tag_snapshots(data, metadata, tag_colors, snapshot_times, conc=False, min_color=(1, 1, 1), out_prefix=None, show_membrane=False, return_fig=False, figsize=(9, 1.75), highlight_agent=None)[source]

Plot a row of snapshot images that span a replicate for each condition. In each of these images, cells will be will be colored with highlight_color and intensity corresponding to their value of highlight_column.

Parameters:

  • data (pandas.DataFrame) – DataFrame where each row is an agent and each column is a variable of interest. Must have these columns: ‘Time’, ‘Death’, ‘Agent ID’, ‘Boundary’, ‘Condition’, and ‘Seed’. 1 condition/seed at a time.

  • metadata (dict[str, dict[int, dict[str, Any]]]) – Nested dictionary where each condition is an outer key and each initial seed is an inner key. Each seed point to a dictionary with the following keys: ‘bounds’ is of the form [x, y] and gives the dimensions of the spatial environment and ‘fields’ is a dictionary timeseries of the ‘fields’ Store for that condition and initial seed

  • tag_colors (dict[str, Any]) – Mapping column names in data to either RGB tuples or dictionaries containing the cmp and norm keys for the matplotlib.colors.Colormap and matplotlib.colors.Normalize instances to use for that tag If dictionaries are used, the min_color key is overrriden

  • conc (bool) – Whether to normalize by volume before plotting

  • snapshot_times (ndarray[Any, dtype[float64]]) – Times (in seconds) to make snapshots for

  • min_color (Any) – Color for cells with lowest highlight_column value (default white)

  • out_prefix (str | None) – Prefix for output filename

  • show_membrane (bool) – Whether to draw outline for agents

  • return_fig (bool) – Whether to return figure. Only use with one tag.

  • figsize – Desired size of entire figure

  • highlight_agent – Mapping of agent IDs to membrane_color and membrane_width. Useful for highlighting specific agents, with rest using defaults

Return type:

None

ecoli.analysis.antibiotics_colony.timeseries.plot_timeseries(data, axes, columns_to_plot, highlight_lineage, conc=False, mark_death=False, background_lineages=True, filter_time=True, background_color=(0.5, 0.5, 0.5), background_alpha=0.5, background_linewidth=0.1)[source]

Plot selected traces with specific lineage highlighted and others in gray.

Parameters:

  • data (pandas.DataFrame) – DataFrame where each row is an agent and each column is a variable of interest. Must have these columns: ‘Time’, ‘Death’, ‘Agent ID’, ‘Boundary’, ‘Condition’, and ‘Seed’. The first experimental condition in the ‘Condition’ column is treated as a control and plotted in gray. Include at most 2 conditions and 1 seed per condition. If more than 1 condition is supplied, either ensure that they do not share any time points or run with the restrict_data option set to true.

  • axes (list[Axes]) – Columns are plotted sequentially on these Axes.

  • columns_to_plot (dict[str, tuple]) – Dictionary of columns in data to plot sequentially on axes. Each column name corresponds to a RGB tuple to color the trace of the highlighted lineage on that plot.

  • highlight_lineage (str) – Agent ID to plot lineage trace for. Alternatively, one of ‘mean’ or ‘median’.

  • conc (bool) – Whether to normalize data by volume and convert to nM

  • mark_death (bool) – Mark cells that die with red X on time step of death

  • background_lineages (bool) – Whether to plot traces for other lineages (gray).

  • filter_time (bool) – Apply default time filter for data (take first 11550 seconds from assumed control condition and 11550-26000 seconds from all other conditions)

  • background_color (tuple) – Color used to plot traces for non-highlighted agents

  • background_alpha (float) – Alpha used to plot traces for non-highlighted agents

  • background_linewidth (float) – Linewidth for non-highlighted agent traces

Return type:

None