tava-simulator

Simulator for finding the best hyperparameters of Tava

What is the best hyperparameter

A hyperparameter is a parameter whose value is given by nature and used to control the system process.

In this simulator, user can change some hyperparameter(s) in the Tava system and track metric(s)

• like income per cost
• to find best hyperparameters that makes output of metric(s) high (or low) .

How to use

Install requirements

pip install -r requirements.txt

Help

python src/main.py -h

usage: main.py [-h] [--fee F] [--additional A] [--time T] [--active P]
               [--missing M] [--users U] [--round R] [--balance B]
               [--mechanism S] [--coef C] [--power X] [--exp E]

Hyperparameters

optional arguments:
  -h, --help      show this help message and exit
  --fee F         default rent fee
  --additional A  additional fee per 1h
  --balance B     default balance
  --time T        default rent time
  --active P      active ratio
  --missing M     missing ratio
  --users U       number of users
  --round R       number of rounds (h)
  --mechanism S   incentive system (0: linear, 1: power, 2: exponential)
  --coef C        incentive coef.
  --power X       incentive power
  --exp E         incentive exp.

More details here: arguments.py

Example

python src/main.py --round=2000 --users=200 --time=2

Logs

Logs will be saved in ./logs after executing ./src/main.py or run.sh.

• run.sh is the batch of ./src/main.py with multiple (diff.) params.

Visualization

Help

python src/visualization.py -h

usage: visualization.py [-h] [--log L] [--show]

Name of log file

optional arguments:
  -h, --help  show this help message and exit
  --log L     name of log file
  --show      show figs

More details here: visualization.py

Example

python src/visualization.py --log="log_1591204931_mechanism_0.json" --show

> Setting: Namespace(log='log_1591204931_mechanism_0.json', show=True)

• TODO: auto save figs using logs in ./logs.

How it works

• --users is the number of users. Default value is 100.
• --round is the number of rounds. Default value is 1000.
  • 1 round = 1 hour in simulation.
• --balance is the initial balance per user. Default value is 10**6.
  • TODO: Applying Pareto distribution.

Total fees

• if total_spent_time < --time: total_fees = --fee
• else: total_fees = (total_spent_time - --time) * --additional + --fee

Random factors

• --active is the proportions of active users per round.
• --missing is the probability of missing a device(bike, etc.) per round.

Mechanisms

Number	Mechanism	Description	Notes
0	Linear	y = x * --coef	Default
1	Power	y = (x ** --power) * --coef	-
2	Exp.	y = (--exp ** x) * --coef	-

More details here: mechanisms.py