cytoflow.views.bar_chart¶
-
class
cytoflow.views.bar_chart.
BarChartView
[source]¶ Bases:
cytoflow.views.base_views.Base1DStatisticsView
Plots a bar chart of some summary statistic
-
statistic
¶ The name of the statistic to plot. Must be a key in the
statistics
attribute of theExperiment
being plotted.Type: (str, str)
-
error_statistic
¶ The name of the statistic used to plot error bars. Must be a key in the
statistics
attribute of theExperiment
being plotted.Type: (str, str)
-
scale
¶ The scale applied to the data before plotting it.
Type: {‘linear’, ‘log’, ‘logicle’}
-
variable
¶ The condition that varies when plotting this statistic: used for the x axis of line plots, the bar groups in bar plots, etc.
Type: str
-
subset
¶ An expression that specifies the subset of the statistic to plot.
Type: str
-
xfacet, yfacet
Set to one of the
conditions
in theExperiment
, and a new row or column of subplots will be added for every unique value of that condition.Type: String
-
huefacet
¶ Set to one of the
conditions
in the in theExperiment
, and a new color will be added to the plot for every unique value of that condition.Type: String
Examples
Make a little data set.
>>> import cytoflow as flow >>> 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()
Add a threshold gate
>>> ex2 = flow.ThresholdOp(name = 'Threshold', ... channel = 'Y2-A', ... threshold = 2000).apply(ex)
Add a statistic
>>> ex3 = flow.ChannelStatisticOp(name = "ByDox", ... channel = "Y2-A", ... by = ['Dox', 'Threshold'], ... function = len).apply(ex2)
Plot the bar chart
>>> flow.BarChartView(statistic = ("ByDox", "len"), ... variable = "Dox", ... huefacet = "Threshold").plot(ex3)
-
enum_plots
(experiment)[source]¶ Returns an iterator over the possible plots that this View can produce. The values returned can be passed to “plot”.
-
plot
(experiment, plot_name=None, **kwargs)[source]¶ Plot a bar chart
Parameters: - experiment (Experiment) – The
Experiment
to plot using this view. - title (str) – Set the plot title
- xlabel, ylabel (str) – Set the X and Y axis labels
- 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.
- sharex, sharey (bool) – If there are multiple subplots, should they share axes? Defaults to True.
- row_order, col_order, hue_order (list) – Override the row/column/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 col_wrap 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 ({“paper”, “notebook”, “talk”, “poster”}) – Which seaborn context to use? Controls the scaling of plot elements such as tick labels and the legend. Default is talk.
- despine (Bool) – Remove the top and right axes from the plot? Default is True.
- orientation ({‘vertical’, ‘horizontal’})
- lim ((float, float)) – Set the range of the plot’s axis.
- color (a matplotlib color) – Sets the colors of all the bars, even if there is a hue facet
- errwidth (scalar) – The width of the error bars, in points
- errcolor (a matplotlib color) – The color of the error bars
- capsize (scalar) – The size of the error bar caps, in points
Notes
Other
kwargs
are passed to matplotlib.axes.Axes.bar- experiment (Experiment) – The
-