cytoflow.views.stats_2d#

Plots two statistics on a scatter plot.

Stats2DView – the IView class that makes the plot.

class cytoflow.views.stats_2d.Stats2DView[source]#

Bases: Base2DStatisticsView

Plot two statistics on a scatter plot. A point (X,Y) is drawn for every pair of elements with the same value of variable; the X value is from xfeature and the Y value is from yfeature.

variable#

The condition that varies when plotting this statistic: used for the x axis of line plots, the bar groups in bar plots, etc. Must be a level in the statistic’s index.

Type:

Str

xfeature#

The name of the column to plot on the X axis.

Type:

Str

xerror_low#

The name of the column containing the low values for the X error bars. If xerror_low is set, xerror_high must be set as well.

Type:

Str

xerror_high#

The name of the column containing the high values for the X error bars. If xerror_high is set, xerror_low must be set as well.

Type:

Str

yfeature#

The name of the column to plot on the Y axis.

Type:

Str

yerror_low#

The name of the column containing the low values for the Y error bars. If yerror_low is set, yerror_high must be set as well.

Type:

Str

yerror_high#

The name of the column containing the high values for the Y error bars. If yerror_high is set, yerror_low must be set as well.

Type:

Str

xscale#

The scale applied to X axis.

Type:

{‘linear’, ‘log’, ‘logicle’}

yscale#

The scale applied to Y axis.

Type:

{‘linear’, ‘log’, ‘logicle’}

statistic#

The statistic to plot. Must be a key in Experiment.statistics.

Type:

Str

xfacet#

Set to one of the index levels in the statistic being plotted, and a new column of subplots will be added for every unique value of that index level.

Type:

String

yfacet#

Set to one of the index levels in the statistic being plotted, and a new row of subplots will be added for every unique value of that index level.

Type:

String

huefacet#

Set to one of the index levels in the statistic being plotted, and a new colored artist (line, bar, etc) will be added for every unique value of that index level.

Type:

String

subset#

An expression that specifies the subset of the statistic to plot. Passed unmodified to pandas.DataFrame.query.

Type:

str

huescale#

How should the color scale for huefacet be scaled?

Type:

{‘linear’, ‘log’, ‘logicle’}

Examples

Make a little data set.

>>> import cytoflow as flow
>>> import pandas as pd
>>> import_op = flow.ImportOp()
>>> import_op.tubes = [flow.Tube(file = "Plate01/RFP_Well_A3.fcs",
...                              conditions = {'Dox' : 10.0}),
...                    flow.Tube(file = "Plate01/CFP_Well_A4.fcs",
...                              conditions = {'Dox' : 1.0})]
>>> import_op.conditions = {'Dox' : 'float'}
>>> ex = import_op.apply()

Create two new statistics

>>> ch_op = flow.ChannelStatisticOp(name = 'MeanSDByDox',
...                     channel = 'Y2-A',
...                     function = lambda x: pd.Series({'Geo.Mean' : flow.geom_mean(x),
...                                                     'Geo.SD' : flow.geom_sd(x)}),
...                     by = ['Dox'])
>>> ex2 = ch_op.apply(ex)

Plot the statistics

>>> flow.Stats2DView(variable = 'Dox',
...                  statistic = 'MeanSDByDox',
...                  xfeature = 'Geo.Mean',
...                  xscale = 'log',
...                  yfeature = 'Geo.SD',
...                  yscale = 'log').plot(ex2)
../../_images/cytoflow-views-stats_2d-3.png
plot(experiment, plot_name=None, **kwargs)[source]#

Plot a chart of two statistics’ values as a common variable changes.

Parameters:

  • experiment (Experiment) – The Experiment to plot using this view.

  • title (str) – Set the plot title

  • xlabel (str) – Set the X axis label

  • ylabel (str) – Set the Y axis label

  • huelabel (str) – Set the label for the hue facet (in the legend)

  • legend (bool) – Plot a legend for the color or hue facet? Defaults to True.

  • legend_out (bool) – Plot the legend outside of the plot or grid? Defaults to True.

  • sharex (bool) – If there are multiple subplots, should they share X axes? Defaults to True.

  • sharey (bool) – If there are multiple subplots, should they share Y axes? Defaults to True.

  • row_order (list) – Override the row facet value order with the given list. If a value is not given in the ordering, it is not plotted. Defaults to a “natural ordering” of all the values.

  • col_order (list) – Override the column facet value order with the given list. If a value is not given in the ordering, it is not plotted. Defaults to a “natural ordering” of all the values.

  • hue_order (list) – Override the hue facet value order with the given list. If a value is not given in the ordering, it is not plotted. Defaults to a “natural ordering” of all the values.

  • height (float) – The height of each row in inches. Default = 3.0

  • aspect (float) – The aspect ratio of each subplot. Default = 1.5

  • col_wrap (int) – If xfacet is set and yfacet is not set, you can “wrap” the subplots around so that they form a multi-row grid by setting this to the number of columns you want.

  • sns_style ({“darkgrid”, “whitegrid”, “dark”, “white”, “ticks”}) – Which seaborn style to apply to the plot? Default is whitegrid.

  • sns_context ({“notebook”, “paper”, “talk”, “poster”}) – Which seaborn context to use? Controls the scaling of plot elements such as tick labels and the legend. Default is notebook.

  • palette (palette name, list, or dict) – Colors to use for the different levels of the hue variable. Should be something that can be interpreted by seaborn.color_palette, or a dictionary mapping hue levels to matplotlib colors. See https://seaborn.pydata.org/tutorial/color_palettes.html for a good overview.

  • despine (Bool) – Remove the top and right axes from the plot? Default is True.

  • plot_name (str) – If this IView can make multiple plots, plot_name is the name of the plot to make. Must be one of the values retrieved from enum_plots.

  • xlim ((float, float)) – Set the range of the plot’s X axis.

  • ylim ((float, float)) – Set the range of the plot’s Y axis.

  • color (a matplotlib color) – The color to plot with. Overridden if huefacet is not None

  • linestyle ({‘solid’ | ‘dashed’, ‘dashdot’, ‘dotted’ | (offset, on-off-dash-seq) | ‘-’ | ‘–’ | ‘-.’ | ‘:’ | ‘None’ | ‘ ‘ | ‘’})

  • marker (a matplotlib marker style) – See http://matplotlib.org/api/markers_api.html#module-matplotlib.markers

  • markersize (int) – The marker size in points

  • markerfacecolor (a matplotlib color) – The color to make the markers. Overridden (?) if huefacet is not None

  • alpha (the alpha blending value, from 0.0 (transparent) to 1.0 (opaque))

Notes

Other kwargs are passed to matplotlib.pyplot.plot