mcspy 1.2.2

A Python Library for Mobile Crowdsensing Problems

A Python Library for Mobile Crowdsensing Problems, with random, Epsilon-Greedy and New_MAB methods to build a MCS system and its group.

Installation

pip install mcspy

Author contact

Han Yaohui

[e-mail]

Source Code

see https://github.com/Han-0107/mcspy

Script example

https://github.com/Han-0107/New_MAB_in_MCS

Functions

Basic Functions

1. constant_produce(num_of_system)
2. system_postprocess(relation_pre, workers, group_efficiency, times_total, num_of_group)
3. system_init(num_of_group, num_of_system)
4. normalization(x, num_of_system)
5. reselection_judge(workers, num_choice, i, num_of_group)
6. epsilon_produce(times)
7. random_unit(p)
8. list_init(start, stop, length)
9. result_produce(num_choice, pos_choice, workers, reselection_flag, num_of_group, relation_real, ability_of_workers)

Matrix Functions

1. matrix_assign(result_of_system, relation_total, relation_n, workers, num_of_group)
2. matrix_renewal(relation_n, relation_pre, relation_total, num_of_system)

Printing Functions

1. print_basic(relation_real, num_of_system, num_of_group, relation_var, abilities_var, ability_of_workers)
2. print_result(group_efficiency)
3. print_result_of_all(sum_of_result, iterations)
4. print_time(start, end)

Working Functions

1. group_work(workers, relation_real, num_of_group, ability_of_workers)
2. system_work_random(workers, num_of_group, num_of_system, relation_real, ability_of_workers)
3. system_work_epsilon(workers, min_index, person_efficiency, epsilon, num_of_system, num_of_group, relation_real, ability_of_workers)
4. system_work_mab(workers, min_index, person_efficiency, person_co, times, epsilon, num_of_system, num_of_group, relation_real, ability_of_workers):