kstoneriv3

"""Visualization of Brownian bridge construction of a Brownian motion."""

import numpy as np
from matplotlib import pyplot as plt


T = 1
TAB10_CMAP = plt.get_cmap("tab10")
DEFAULT_COLOR = TAB10_CMAP(0)

kstoneriv3

from concurrent.futures import ProcessPoolExecutor, wait
import fire
from matplotlib import pyplot as plt
import numpy as np
import optuna
import os
import time
import torch

N_WORKERS = 10

kstoneriv3

from kurobako import solver
from kurobako.solver.optuna import OptunaSolverFactory
import optuna
from optuna.samplers import QMCSampler


def create_study(seed):
    sampler = QMCSampler(seed=seed, scramble=True, qmc_type="halton", warn_independent_sampling=False)
    return optuna.create_study(sampler=sampler)

kstoneriv3

import numpy
import scipy.ndimage
import matplotlib.pyplot as plt

from sklearn import datasets
from sklearn import decomposition

digits = datasets.load_digits()
images = digits.images
images = map(lambda x: scipy.ndimage.zoom(x, 2, order=1), images)

kstoneriv3

#!/usr/bin/env python
# coding: utf-8

import numpy as np
import matplotlib.pyplot as plt


# centered case
def LHS(n, d):
    samples = np.tile(np.arange(n, dtype=np.float64), (d, 1)).reshape(d, n)

kstoneriv3

#!/usr/bin/env python
# coding: utf-8

import numpy as np
import matplotlib.pyplot as plt


# centered case
def LHS(n, d):
    samples = np.tile(np.arange(n, dtype=np.float64), (d, 1)).reshape(d, n)

kstoneriv3

import lightgbm as lgb
import numpy as np

import pandas as pd
import sklearn.datasets
from sklearn.datasets import fetch_openml
import sklearn.metrics
from sklearn.model_selection import train_test_split

import optuna