class histogrammar.primitives.select.Select(quantity, cut=<Count 0.0>)[source]

Bases: histogrammar.defs.Factory, histogrammar.defs.Container

Filter or weight data according to a given selection.

This primitive is a basic building block, intended to be used in conjunction with anything that needs a user-defined cut. In particular, a standard histogram often has a custom selection, and this can be built by nesting Select -> Bin -> Count.

Select also resembles Fraction, but without the denominator.

The efficiency of a cut in a Select aggregator named x is simply x.cut.entries / x.entries (because all aggregators have an entries member).


Add two containers of the same type. The originals are unaffected.

__init__(quantity, cut=<Count 0.0>)

Create a Select that is capable of being filled and added.

  • quantity (function returning bool or float) – computes the quantity of interest from the data and interprets it as a selection (multiplicative factor on weight).
  • cut (Container) – will only be filled with data that pass the cut, and which are weighted by the cut.
Other Parameters:

entries (float) – the number of entries, initially 0.0.


List of sub-aggregators, to make it possible to walk the tree.


Copy this container, making a clone with no reference to the original.

static ed(entries, cut)

Create a Select that is only capable of being added.

  • entries (float) – the number of entries.
  • cut (Container) – the filled sub-aggregator.

Reference to the container’s factory for runtime reflection.

fill(datum, weight=1.0)

Increment the aggregator by providing one datum to the fill rule with a given weight.

Usually all containers in a collection of histograms take the same input data by passing it recursively through the tree. Quantities to plot are specified by the individual container’s lambda functions.

The container is changed in-place.


Fraction of weights that pass the quantity.


User’s entry point for reconstructing a container from JSON text.

static fromJsonFragment(json, nameFromParent)

staticmethod(function) -> method

Convert a function to be a static method.

A static method does not receive an implicit first argument. To declare a static method, use this idiom:

class C: def f(arg1, arg2, ...): ... f = staticmethod(f)

It can be called either on the class (e.g. C.f()) or on an instance (e.g. C().f()). The instance is ignored except for its class.

Static methods in Python are similar to those found in Java or C++. For a more advanced concept, see the classmethod builtin.

static ing(quantity, cut=<Count 0.0>)

Synonym for __init__.


Name of the concrete Factory as a string; used to label the container type in JSON.

plot(httpServer=None, **parameters)

Generate a VEGA visualization and serve it via HTTP.


Add a new Factory to the registry, introducing a new container type on the fly. General users usually wouldn’t do this, but they could. This method is used internally to define the standard container types.


Explicitly invoke histogrammar.specialized.addImplicitMethods on this object, usually right after construction (in each of the methods that construct: __init__, ed, ing, fromJsonFragment, etc).

Objects used as default parameter arguments are created too early for this to be possible, since they are created before the histogrammar.specialized module can be defined. These objects wouldn’t satisfy any of addImplicitMethod‘s checks anyway.


Return a copy of this container as though it was created by the ed function or from JSON (the “immutable form” in languages that support it, not Python).


Convert this container to dicts and lists representing JSON (dropping its fill method).

Note that the dicts and lists can be turned into a string with json.dumps.


Used internally to convert the container to JSON without its "type" header.


Create an empty container with the same parameters as this one. The original is unaffected.