Python update_img示例

示例#1

文件： cli_splinart.py 项目： mtrellet/python_packaging_2017

def circle(img):
    def xs_func():
        nsamples = 500
        return (np.random.random() + 2 * np.pi * np.linspace(0, 1, nsamples))%(2*np.pi)

    theta, path = spl.circle([.5, .5], .3, npoints=40)
    spl.update_img(img, path, xs_func, nrep=4000, x=theta, scale_value=.00005)

示例#2

文件： cli_splinart.py 项目： mtrellet/python_packaging_2017

def line(img):
    def xs_func():
        nsamples = 500
        return .001*np.random.random() + np.linspace(lo+.1,up-.1, nsamples)

    lo, up = .2, .8
    path = spl.line(lo, up, .5)
    spl.update_img(img, path, xs_func, nrep=1000, periodic=False)

示例#3

文件： cli_splinart.py 项目： slempereur/splinart_wrong

def line(img):
    """
    line
    """
    def xs_func():
        """
        xs function
        """
        nsamples = 500
        return .001 * np.random.random() + np.linspace(beg + .1, end - .1,
                                                       nsamples)

    beg, end = .2, .8
    path = spl.line(beg, end, .5)
    spl.update_img(img, path, xs_func, nrep=1000, periodic=False)

示例#4

def test_case(tmpdir, load_json):

    datadir, js = load_json
    np.random.seed(js["seed"])

    img_size, channels = 1000, 4
    img = np.ones((img_size, img_size, channels), dtype=np.float32)

    theta, path = spl.circle(js["center"], js["radius"])

    def xs_func():
        nsamples = 500
        return (np.random.random() + 2 * np.pi * np.linspace(0, 1, nsamples))%(2*np.pi)

    spl.update_img(img, path, xs_func, nrep=js["nrep"], x=theta)

    spl.save_img(img, tmpdir.dirname, 'output.png')

    assert filecmp.cmp(tmpdir.dirname + '/output.png', datadir + "/" + js["output"]) 

示例#5

文件： test_all.py 项目： gouarin/splinart

def test_circle_case():

    np.random.seed(42)

    img_size, channels = 1000, 4
    img = np.ones((img_size, img_size, channels), dtype=np.float32)

    theta, path = spl.circle([0.5, 0.5], 0.3)

    def xs_func():
        nsamples = 500
        return (np.random.random() +
                2 * np.pi * np.linspace(0, 1, nsamples)) % (2 * np.pi)

    spl.update_img(img, path, xs_func, nrep=4000, x=theta)

    fig = plt.figure()
    ax = fig.add_subplot(1, 1, 1)
    ax.imshow(img)
    return fig

示例#6

lo, up = .2, .8
path = []
color_lines = []
npoints = 20
for iy, y in enumerate(np.linspace(lo, up, 10)):
    npoints += 5
    path.append(spl.line(lo, up, y, npoints))
    color = np.random.random(4) * .3
    color[-1] = 1.
    color_lines.append(color)


def xs_func():
    nsamples = 500
    return .001 * np.random.random() + np.linspace(lo + .02, up - .02,
                                                   nsamples)


for i in range(len(path)):
    img1 = np.ones_like(img)
    spl.update_img(img1,
                   path[i],
                   xs_func,
                   nrep=1000,
                   periodic=False,
                   color=color_lines[i])
    mask = img1 < 1.
    img[mask] += img1[mask]

spl.save_img(img, "./output", "lines.png")

示例#7

RADIUS = .3
NREP = 4000

np.random.seed(SEED)
img_size, channels = 1000, 4
img = np.ones((img_size, img_size, channels), dtype=np.float32)

theta, path = spl.circle(CENTER, RADIUS)


def xs_func():
    nsamples = 500
    return (np.random.random() +
            2 * np.pi * np.linspace(0, 1, nsamples)) % (2 * np.pi)


spl.update_img(img, path, xs_func, nrep=NREP, x=theta)

spl.save_img(img, '.', 'circle.png')

js = json.dumps(
    {
        "circle": {
            "seed": SEED,
            "center": CENTER,
            "radius": RADIUS,
            "nrep": NREP,
            "output": "./circle.png"
        }
    },
    indent=4)

示例#8

文件： circles.py 项目： mtrellet/python_packaging_2017

for i in range(nb_circles):
    radius = .1 + np.random.random() * .1
    center = .2 + np.random.random(2) * .6
    theta, path = spl.circle(center, radius, npoints=75)
    theta_circles.append(theta)
    path_circles.append(path)
    color = np.random.random(4) * .3
    color[-1] = 1.
    color_circles.append(color)


def xs_func():
    nsamples = 500
    return (np.random.random() +
            2 * np.pi * np.linspace(0, 1, nsamples)) % (2 * np.pi)


for i in range(nb_circles):
    img1 = np.ones_like(img)
    spl.update_img(img1,
                   path_circles[i],
                   xs_func,
                   nrep=1000,
                   scale_value=.00005,
                   x=theta_circles[i],
                   color=color_circles[i])
    mask = img1 < 1.
    img[mask] += img1[mask]

spl.save_img(img, './output', 'circles.png')

示例#9

from __future__ import print_function, division, absolute_import
import numpy as np
import splinart as spl

img_size, channels = 1000, 4
img = np.ones((img_size, img_size, channels), dtype=np.float32)

theta, path = spl.circle([.5, .5], .3, npoints=40)


def xs_func():
    nsamples = 500
    return (np.random.random() +
            2 * np.pi * np.linspace(0, 1, nsamples)) % (2 * np.pi)


spl.update_img(img, path, xs_func, nrep=4000, x=theta, scale_value=.00005)

spl.save_img(img, './output', 'circle.png')

示例#10

文件： line.py 项目： mtrellet/python_packaging_2017

# Author:
#     Loic Gouarin <*****@*****.**>
#
# License: BSD 3 clause
from __future__ import print_function, division, absolute_import
import numpy as np
from six.moves import range
import splinart as spl

img_size, channels = 1000, 4
img = np.ones((img_size, img_size, channels), dtype=np.float32)

def xs_func():
    nsamples = 500
    return .001*np.random.random() + np.linspace(lo+.1,up-.1, nsamples)

lo, up = .2, .8
path = spl.line(lo, up, .5)

spl.update_img(img, path, xs_func, nrep=1000, periodic=False)

spl.save_img(img, "./output", "line.png")