nifty8.probing module#

class StatCalculator[source]#

Bases: object

Helper class to compute mean and variance of a set of inputs.

Notes

The memory usage of this object is constant, i.e. it does not increase with the number of samples added.
The code computes the unbiased variance (which contains a 1./(n-1) term for n samples).

__init__()[source]#

add(value)[source]#

Adds a sample.

Parameters:: value (any type that supports multiplication by a scalar and) – element-wise addition/subtraction/multiplication.

property mean#

the mean of all samples added so far.

Type:: value type

property var#

the unbiased variance of all samples added so far.

Type:: value type

approximation2endo(op, nsamples)[source]#

probe_diagonal(op, nprobes, random_type='pm1')[source]#

Probes the diagonal of an endomorphic operator.

The operator is called on a user-specified number of randomly generated input vectors $v_i$ , producing $r_i$ . The estimated diagonal is the mean of $r_i^\dagger v_i$ .

Parameters:

op (EndomorphicOperator) – The operator to be probed.
nprobes (int) – The number of probes to be used.
random_type (str) – The kind of random number distribution to be used for the probing. The default value pm1 causes the probing vector to be randomly filled with values of +1 and -1.

Returns:

The estimated diagonal.

Return type:

nifty8.field.Field

probe_with_posterior_samples(op, post_op, nprobes, dtype)[source]#

FIXME

Parameters:

op (EndomorphicOperator) – FIXME
post_op (Operator) – FIXME
nprobes (int) – Number of samples which shall be drawn.
dtype – the data type of the samples

Returns:

List of two fields: the mean and the variance.

Return type:

List of nifty8.field.Field