#!/usr/bin/env python3
"""rng normal [OPTIONS]
Uniform distribution - Generate random data from a normal distribution.
Options:
-d, --delta velocity of average per time unit [Default: 0]
-m, --mu average of distribution [Default: 0]
-n, --number number of random data points to generate [Default: 10]
-s, --sigma standard deviation of distribution [Default: 1]
Currently assumed that sigma is constant over time.
"""
import sys
import random
import itertools
from typing import Callable, List, Dict, Iterator
def cli_wrapper(**data: Dict):
"""Handler for the uniform distribution. Checks and cleans given options,
and performs optional reporting.
"""
_number = data["number"] if data["number"] is not None else 10
_init_mu = data["mu"] if data["mu"] is not None else 0.0
_sigma = data["sigma"] if data["sigma"] is not None else 1.0
_init_velocity = data["delta"] if data["delta"] is not None else 0.0
_acceleration = lambda x: x #constant acceleration
_distribution = distribution(
_init_mu,
_sigma,
_init_velocity,
_acceleration,
)
if data["report"]:
sys.stdout.write(
report_header(_init_mu, _sigma, _init_velocity, _acceleration)
)
if _number > 0:
for number in itertools.islice(_distribution, _number):
sys.stdout.write("{0:.4f}\n".format(number))
def distribution(
init_mu: float,
sigma: float,
init_velocity: float,
acceleration: Callable[[float], float],
) -> Iterator[float]:
mu = init_mu
velocity = init_velocity
while True:
yield random.normalvariate(mu, sigma)
mu += velocity
velocity = acceleration(velocity)
# use this in a report function later: μ±
def report_header(
init_mu: float,
sigma: float,
init_velocity: float,
acceleration: Callable[[float], float],
) -> str:
_msg = (
"Normal distribution",
" μ={0:.4f}, σ={1:.4f}".format(init_mu, sigma),
" dμ/dt={0:.4f}".format(init_velocity),
"Obs.:",
"========",
)
return "\n".join(_msg) + "\n"