Utilities

cana.utils.entropy(prob_vector, logbase=2.0)

Calculates the entropy given a probability vector

cana.utils.flip_binstate_bit_set(binstate, idxs)

Flips the binary value for a set of bits in a binary state.

Parameters

• binstate (string) – The binary state to flip.

• idxs (int) – The indexes of the bits to flip.

Returns

The flipped states

Return type

(list)

cana.utils.flip_bitset_in_strstates(strstates, idxs)

Flips the binary value for a set of bits in a binary state.

Parameters

• binstate (string) – The binary state to flip.

• idxs (int) – The indexes of the bits to flip.

Returns

The flipped states

Return type

(list)

Example

>>> flip_bit_in_strstates('000',[0, 2])
['100','001']

cana.utils.isclose(a, b, rel_tol=1e-09, abs_tol=0.0)

Python 2 doesn’t have math.isclose() Here is an equivalent function Use this to tell whether two float numbers are close enough considering using == to compare floats is dangerous! 2.0*3.3 != 3.0*2.2 in python!

Parameters

• a (float) – the first float number

• b (float) – the second float number

• rel_tol (float) – the relative difference threshold between a and b

• abs_tol (float) – absolute difference threshold. not recommended for float

Returns

bool

cana.utils.mindist_from_source(G, source)

TODO: description

cana.utils.ncr(n, r)

Return the combination number. The combination of selecting r items from n iterms, order doesn’t matter.

Parameters

• n (int) – number of elements in collection

• r (int) – length of combination

Returns

int

cana.utils.output_transitions(eval_line, input_list)

Returns an output list from combinatorically trying all input values

Parameters

• eval_line (string) – logic or arithmetic line to evaluate

• input_list (list) – list of input variables

Returns

list of all possible output transitions (list)

Example

RAS*=(GRB2 or PLCG1) and not GAP

>>> eval_line = "(GRB2 or PLCG1) and not GAP"
>>> input_list = ['GRB2', 'PLCG1', 'GAP']
>>> output_transitions(eval_line, input_list)
000
001
010
011
100
101
110
111

A variable is dynamically created for each member of the input list and assigned the corresponding value from each trail string. The original eval_line is then evaluated with each assignment which results in the output list [0, 0, 1, 0, 1, 0, 1, 0]

cana.utils.pathlength(p, weights, rule='sum')

Calculate the length of path p, with weighted edges, given the length rule of:

Ars:

weights:

rule (str):

‘sum’ - sum of edge weights along path ‘prod’ - product of edge weights along path ‘min’ - minimum of edge weights along path (weakest-link) ‘max’ - maximum of edge weights along path

TODO: update description

cana.utils.print_logic_table(outputs)

Print Logic Table

Parameters

outputs (list) – The transition outputs of the function.

Returns

a print-out of the logic table.

Return type

print

Example

>>> print_logic_table([0,0,1,1])
00 : 0
01 : 0
10 : 1
11 : 1

cana.utils.seq_upto(seq, obj)

TODO: description