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:
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)
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 –