Module: gmap

In this module are all functions to calculate a Gaussian weighted contact map. For the gaussian weight at a specific position \(x\), use function BioHelpers.modules.gmap.gaussSum().

Examples

In the first example we calculate the \(PPV\) of a predicted contact map, compared to a native map. In this example we make no use of the Gaussian weighting.

Example PPV
 1import BioHelpers_FABER.gmap as gmap
 2import BioHelpers_FABER.bio_mod as bm
 3
 4predicted_contacts =  #List of predicted contacts
 5native_contacts = #List of native contacts
 6
 7#-- Calculation from TP --
 8tp = gmap.TP(predicted_contacts, native_contacts)
 9all_positive = sum([e[2] for e in predicted_contacts])
10print("PPV", tp/all_positive)
11
12#-- Calculation w/ function --
13print("PPV", gmap.ppv(predicted_contacts, native_contacts))

Members

BioHelpers_FABER.gmap.ceff(map: list[list[float]]) → float

Calculation of the effective contacts

Parameters:

map (list) – Map with points of the form [x,y,val]

Returns:

sum over all val

Return type:

float

BioHelpers_FABER.gmap.gauss(x: list, center: list, var: float) → float

Gauss function at point x with mean center

Parameters:

  • x (list) – Point of Gaussian distr.

  • center (list) – mean point of Gaussian distr.

  • var (float) – Variance

Returns:

Value of Gaussian distr.

Return type:

float

BioHelpers_FABER.gmap.gaussSum(x: list, con: list, var: float) → float

Summation of all Gaussian distributions at point x

Parameters:

  • x (list) – Point of summation (e.g. [3,5])

  • con (list) – List of all contacts

  • var (float) – Variance of the Gaussian distributions

Returns:

Summation of all Gaussian distr. at point x

Return type:

float

BioHelpers_FABER.gmap.gaussWeightCon(contacts: list, var: float) → list

“Intermediate function with only contacts”

BioHelpers_FABER.gmap.gaussWeightMap(init: list, var: float) → list

Create a full Gauss map

Parameters:

  • init (list) – Initial contact map of the form [[x1,y1,val],….] and val \(\in [0,1]\)

  • var (float) – Variance

Returns:

Full Gaussian contact map, reweighted with the weight function for each contact point.

Return type:

list

BioHelpers_FABER.gmap.ppv(c: list, m: list) → float

Calculation of the positive predicted value

Parameters:

  • c (list) – Predicted Contact map

  • m (list) – Native Contact map

Returns:

Ratio(\(PPV\)) \(\frac{TP}{TP+FP}\)

Return type:

float

BioHelpers_FABER.gmap.ppv_mat(c: ndarray, m: ndarray, tot=0) → float

“Calculation if the positive predicted value for matrices”

BioHelpers_FABER.gmap.tp(c: list[list[int]], m: list[list[int]]) → float

Calculation of True Positive (TP) value

Parameters:

  • c (list) – all contacts

  • m (list) – native contact map as list

Returns:

\(TP = \sum_{x,y}c(x,y) \times m(x,y)\)

Return type:

float

BioHelpers_FABER.gmap.tp_mat(c: ndarray, m: ndarray) → float

Calculation of True Positive (TP) value

Parameters:

  • c (numpy array) – all contacts

  • m (numpy array) – native contact map as list

Returns:

\(TP = \sum_{x,y}c(x,y) \times m(x,y)\)

Return type:

float

BioHelpers_FABER.gmap.weightFunction(x: float) → float

weightFunction Weight function, here \(f(x) = 1/x\)