microprobe.utils.distrib

microprobe.utils.distrib module

Functions

average(array[, weights])

param array

compute_weighted_profile_average(profile, …)

param profile

discrete_average(average_val)

param average_val

generate_plain_profile(elements)

param elements

generate_weighted_profile(elements, …[, …])

param elements

locality(values, locdef)

pstdev(data)

Calculates the population standard deviation

regular_seq(items)

param items

shuffle(slist, threshold)

param slist

sort_by_distance(regs, distdict, useddict, …)

param regs

sort_by_usage(regs, lastdict, dummy_defdict)

param regs

weighted_choice(items)

Returns a function that makes a weighted random choice from items.

Classes

Choice(items)

Classes diagram

Inheritance diagram of Choice


Functions

average(array, weights=None)[source]
Parameters

  • array –

  • weights –

compute_weighted_profile_average(profile, attribute)[source]
Parameters

  • profile –

  • attribute –

discrete_average(average_val)[source]
Parameters

average_val –

generate_plain_profile(elements)[source]
Parameters

elements –

generate_weighted_profile(elements, attribute, targetvalue, maxvalue=None, minvalue=None)[source]
Parameters

  • elements –

  • attribute –

  • targetvalue –

  • maxvalue – (Default value = None)

  • minvalue – (Default value = None)

locality(values, locdef)[source]
pstdev(data)[source]

Calculates the population standard deviation

regular_seq(items)[source]
Parameters

items –

shuffle(slist, threshold)[source]
Parameters

  • slist –

  • threshold –

sort_by_distance(regs, distdict, useddict, distance, dummy_instr, dummy_idx)[source]
Parameters

  • regs –

  • distdict –

  • useddict –

  • distance –

  • dummy_instr –

  • dummy_idx –

sort_by_usage(regs, lastdict, dummy_defdict)[source]
Parameters

  • regs –

  • lastdict –

  • dummy_defdict –

weighted_choice(items)[source]

Returns a function that makes a weighted random choice from items.

Parameters

items –