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removed dataset removal code, and upgraded sampler #10

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removed dataset removal code, and upgraded sampler #10

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6951f2f
removed dataset removal code, and upgraded sampler
Jumperkables Jun 26, 2020
5774faf
fixed a refresh error, adding min(1000, args.num)
Jumperkables Jun 26, 2020
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50 changes: 40 additions & 10 deletions src/generate_dataset.py
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Original file line number Diff line number Diff line change
Expand Up @@ -9,13 +9,14 @@

import yaml
import time
import os
import os, sys, shutil
import math
from sklearn.model_selection._search import ParameterSampler, ParameterGrid
import numpy as np
import subprocess
import random
from simulate import simulate
import scipy.stats.distributions as dists

import argparse
parser = argparse.ArgumentParser(description='Generate ball simulations')
Expand All @@ -25,11 +26,16 @@
help='Path to save simulations')
args = parser.parse_args()

num_timesteps_per_simulation = 100
num_timesteps_per_simulation = 60
image_size = 64

# Parameters which can change per ball
per_ball_parameter_space = {
#"x":dists.uniform(0.1,0.9),
#"y":dists.uniform(0.1,0.9),
#"dx":dists.uniform(-0.5,0.4),
#"dy":dists.uniform(-0.5,0.4),
#"radius":dists.uniform(0.1,0.3),
"x":[0.1*i for i in range(1,10)],
"y":[0.1*i for i in range(1,10)],
"dx":[0.1*i for i in range(-5,5)],
Expand All @@ -38,20 +44,37 @@
"foreground_color":['#{0:x}{0:x}{0:x}'.format(x) for x in range(15,-1,-1)],
}

#per_ball_parameter_space = {
# "x":dists.uniform(0.1,0.9),
# "y":dists.uniform(0.1,0.9),
# "dx":dists.uniform(-0.5,0.4),
# "dy":dists.uniform(-0.5,0.4),
# "radius":dists.uniform(0.1,0.3),
# "foreground_color":['#{0:x}{0:x}{0:x}'.format(x) for x in range(15,-1,-1)]
#}

# Global parameters
parameter_space = {
"num_balls":range(1,4),
# "gx":[0.1*i for i in range(0,5)],
# "gy":[0.1*i for i in range(0,5)],
"num_balls":range(1,5),
#"gx":dists.uniform(0,0.04), # As long as at least one parameter is a distribution, the sampler will sample WITHOUT REPLACEMENT (important)
"gy":dists.uniform(0,0.02),
"background_color":['#{0:x}{0:x}{0:x}'.format(x) for x in range(0,16)],
}

## How the rest of the parameter space make look if you wish to sample from continuous space
#parameter_space = {
# "num_balls":range(1,4), # YOU CANNOT MAKE NUMBALLS A `dists.randint' distribution without changing your ``Building space'' code
# "gx":dists.uniform(0,0.4),
# "gy":dists.uniform(0,0.4),
# "background_color":['#{0:x}{0:x}{0:x}'.format(x) for x in range(0,16)]
#}

# Make dataset dir
try:
os.mkdir(args.output_path)
pass
except:
raise Exception("Folder " + args.output_path + " already exists.")
raise Exception("Folder " + args.output_path + " already exists.")

# write config
config = {}
Expand Down Expand Up @@ -82,12 +105,19 @@
# Render
simulation_num = 0
balls = []
sampler = ParameterGrid(parameter_space)

while simulation_num < args.number_of_simulations:
random_idx = random.randint(0, len(sampler)-1)
params = sampler[random_idx]
# If one of the parameters given is a scipy.stats.distributions object, then it will sample with replacement
sampler = ParameterSampler(parameter_space, min(1000, args.number_of_simulations))
sampler = list(sampler)
sampler_idx = 0


while simulation_num < args.number_of_simulations:
if(sampler_idx == min(1000, args.number_of_simulations)):
sampler_idx = 0
sampler = list(ParameterSampler(parameter_space, min(1000, args.number_of_simulations)))
params = sampler[sampler_idx]
sampler_idx += 1
good_simulation = True
for i in range(params["num_balls"]):

Expand Down