quant_analytics_flow.analytics package

Submodules

quant_analytics_flow.analytics.constants module

quant_analytics_flow.analytics.matrixanalytics module

square_root_symmetric_matrix(A)

Square root of positive semi-definite matrix

\[Q^T \cdot Q = A\]

using a singular value decomposition

Args:

A (tensor(shape=(N,N))): Symmetric 2-dimensional tensor

Returns:

Q (tensor(shape=(N,N))): Returns square root \(Q\)

quant_analytics_flow.analytics.maxsoft module

phi_smooth(x, y)

max_if(x, y)

hyperbolic(x)

Using the hyperbolic function

\[f(x) = \frac{1}{2} \left(x + \sqrt{1 + x^2} \right)\]

Args:

x (tensor(shape=(…))): M-dimensional tensor

Returns:

y (tensor(shape=(…))): Hyperbolic function

soft_max_hypterbolic(x, eps=1e-08)

Using the hyperbolic function to approximate \(\max(x,0)\)

\[g_(x) = f(x/\epsilon)\cdot \epsilon\]

Args:

x (tensor(shape=(…))): M-dimensional tensor eps (float64): scaling parameter

Returns:

y (tensor(shape=(…))): Hyperbolic function

quant_analytics_flow.analytics.norminv module

norminv(x)

Module contents