cytoflow.operations.xform_stat¶

Transforms a statistic. xform_stat has one class:

TransformStatisticOp – apply a function to a statistic, making a new statistic.

class cytoflow.operations.xform_stat.TransformStatisticOp[source]¶

Bases: traits.has_traits.HasStrictTraits

Apply a function to a statistic, creating a new statistic. The function can be applied to the entire statistic, or it can be applied individually to groups of the statistic. The function should take a pandas.Series as its only argument. Return type is arbitrary, but a to be used with the rest of cytoflow it should probably be a numeric type or an iterable of numeric types.

As a special case, if the function returns a pandas.Series with the same index that it was passed, it is interpreted as a transformation. The resulting statistic will have the same length, index names and index levels as the original statistic.

name¶

The operation name. Becomes the first element in the Experiment.statistics key tuple.

Type: Str

statistic¶

The statistic to apply the function to.

Type: Tuple(Str, Str)

function¶

The function used to transform the statistic. function must take a pandas.Series as its only parameter. The return type is arbitrary, but to work with the rest of cytoflow it should probably be a numeric type or an iterable of numeric types.. If statistic_name is unset, the name of the function becomes the second in element in the Experiment.statistics key tuple.

Type: Callable

statistic_name¶

The name of the function; if present, becomes the second element in the Experiment.statistics key tuple.

Type: Str

by¶

A list of metadata attributes to aggregate the input statistic before applying the function. For example, if the statistic has two indices Time and Dox, setting by = ["Time", "Dox"] will apply function separately to each subset of the data with a unique combination of Time and Dox.

Type: List(Str)

fill¶

Value to use in the statistic if a slice of the data is empty.

Type: Any (default = 0)

Examples

>>> stats_op = ChannelStatisticOp(name = "Mean",
...                               channel = "Y2-A",
...                               function = np.mean,
...                               by = ["Dox"])
>>> ex2 = stats_op.apply(ex)
>>> log_op = TransformStatisticOp(name = "LogMean",
...                               statistic = ("Mean", "mean"),
...                               function = np.log)
>>> ex3 = log_op.apply(ex2)

apply(experiment)[source]¶

Applies function to a statistic.

Parameters: experiment (Experiment) – The Experiment to apply the operation to
Returns: The same as the old experiment, but with a new statistic that results from applying function to the statistic specified in statistic.
Return type: Experiment