本文整理汇总了Python中matplotlib.colors.hsv_to_rgb方法的典型用法代码示例。如果您正苦于以下问题：Python colors.hsv_to_rgb方法的具体用法？Python colors.hsv_to_rgb怎么用？Python colors.hsv_to_rgb使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在模块matplotlib.colors的用法示例。

在下文中一共展示了colors.hsv_to_rgb方法的23个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于我们的系统推荐出更棒的Python代码示例。

示例1: rainbow

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# 需要导入模块: from matplotlib import colors [as 别名]

# 或者: from matplotlib.colors import hsv_to_rgb [as 别名]

def rainbow(n):

"""

Returns a list of colors sampled at equal intervals over the spectrum.

Parameters

----------

n : int

The number of colors to return

Returns

-------

R : (n,3) array

An of rows of RGB color values

Notes

-----

Converts from HSV coordinates (0, 1, 1) to (1, 1, 1) to RGB. Based on

the Sage function of the same name.

"""

from matplotlib import colors

R = np.ones((1,n,3))

R[0,:,0] = np.linspace(0, 1, n, endpoint=False)

#Note: could iterate and use colorsys.hsv_to_rgb

return colors.hsv_to_rgb(R).squeeze()

开发者ID:birforce，项目名称:vnpy_crypto，代码行数:26，

示例2: main

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# 需要导入模块: from matplotlib import colors [as 别名]

# 或者: from matplotlib.colors import hsv_to_rgb [as 别名]

def main(imgsize):

y, x = np.ogrid[6: -6: imgsize*2j, -6: 6: imgsize*2j]

z = x + y*1j

z = RiemannSphere(Klein(Mobius(Klein(z))))

# define colors in hsv space

H = np.sin(z[0]*np.pi)**2

S = np.cos(z[1]*np.pi)**2

V = abs(np.sin(z[2]*np.pi) * np.cos(z[2]*np.pi))**0.2

HSV = np.stack((H, S, V), axis=2)

# transform to rgb space

img = hsv_to_rgb(HSV)

fig = plt.figure(figsize=(imgsize/100.0, imgsize/100.0), dpi=100)

ax = fig.add_axes([0, 0, 1, 1], aspect=1)

ax.axis('off')

ax.imshow(img)

fig.savefig('kaleidoscope.png')

开发者ID:neozhaoliang，项目名称:pywonderland，代码行数:20，

示例3: colorize_image

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# 需要导入模块: from matplotlib import colors [as 别名]

# 或者: from matplotlib.colors import hsv_to_rgb [as 别名]

def colorize_image(self, flow_x, flow_y):

if self.hsv_buffer is None:

self.hsv_buffer = np.empty((flow_x.shape[0], flow_x.shape[1],3))

self.hsv_buffer[:,:,1] = 1.0

self.hsv_buffer[:,:,0] = (np.arctan2(flow_y,flow_x)+np.pi)/(2.0*np.pi)

self.hsv_buffer[:,:,2] = np.linalg.norm( np.stack((flow_x,flow_y), axis=0), axis=0 )

# self.hsv_buffer[:,:,2] = np.log(1.+self.hsv_buffer[:,:,2]) # hopefully better overall dynamic range in final video

flat = self.hsv_buffer[:,:,2].reshape((-1))

m = np.nanmax(flat[np.isfinite(flat)])

if not np.isclose(m, 0.0):

self.hsv_buffer[:,:,2] /= m

return colors.hsv_to_rgb(self.hsv_buffer)

开发者ID:daniilidis-group，项目名称:mvsec，代码行数:18，

示例4: visualise_latent

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# 需要导入模块: from matplotlib import colors [as 别名]

# 或者: from matplotlib.colors import hsv_to_rgb [as 别名]

def visualise_latent(Z, identifier):

"""

visualise a SINGLE point in the latent space

"""

seq_length = Z.shape[0]

latent_dim = Z.shape[1]

if latent_dim > 2:

print('WARNING: Only visualising first two dimensions of latent space.')

h = np.random.random()

colours = np.array([hsv_to_rgb((h, i/seq_length, 0.96)) for i in range(seq_length)])

# plt.plot(Z[:, 0], Z[:, 1], c='grey', alpha=0.5)

for i in range(seq_length):

plt.scatter(Z[i, 0], Z[i, 1], marker='o', c=colours[i])

plt.savefig('./experiments/plots/' + identifier + '_Z.png')

plt.clf()

plt.close()

return True

# --- to do with the model --- #

开发者ID:ratschlab，项目名称:RGAN，代码行数:23，

示例5: _get_rgb_phase_magnitude_array

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# 需要导入模块: from matplotlib import colors [as 别名]

# 或者: from matplotlib.colors import hsv_to_rgb [as 别名]

def _get_rgb_phase_magnitude_array(

phase, magnitude, rotation=None, magnitude_limits=None, max_phase=2 * np.pi

):

phase = _find_phase(phase, rotation=rotation, max_phase=max_phase)

phase = phase / (2 * np.pi)

if magnitude_limits is not None:

np.clip(magnitude, magnitude_limits[0], magnitude_limits[1], out=magnitude)

magnitude_max = magnitude.max()

if magnitude_max == 0:

magnitude_max = 1

magnitude = magnitude / magnitude_max

S = np.ones_like(phase)

HSV = np.dstack((phase, S, magnitude))

RGB = hsv_to_rgb(HSV)

return RGB

开发者ID:pyxem，项目名称:pyxem，代码行数:18，

示例6: drawClusters

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# 需要导入模块: from matplotlib import colors [as 别名]

# 或者: from matplotlib.colors import hsv_to_rgb [as 别名]

def drawClusters(stat, ops):

Ly = ops['Lyc']

Lx = ops['Lxc']

ncells = len(stat)

r=np.random.random((ncells,))

iclust = -1*np.ones((Ly,Lx),np.int32)

Lam = np.zeros((Ly,Lx))

H = np.zeros((Ly,Lx,1))

for n in range(ncells):

isingle = Lam[stat[n]['ypix'],stat[n]['xpix']]+1e-4 < stat[n]['lam']

y = stat[n]['ypix'][isingle]

x = stat[n]['xpix'][isingle]

Lam[y,x] = stat[n]['lam'][isingle]

#iclust[ypix,xpix] = n*np.ones(ypix.shape)

H[y,x,0] = r[n]*np.ones(y.shape)

S = np.ones((Ly,Lx,1))

V = np.maximum(0, np.minimum(1, 0.75 * Lam / Lam[Lam>1e-10].mean()))

V = np.expand_dims(V,axis=2)

hsv = np.concatenate((H,S,V),axis=2)

rgb = hsv_to_rgb(hsv)

return rgb

开发者ID:MouseLand，项目名称:suite2p，代码行数:26，

示例7: create_masks_of_cells

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# 需要导入模块: from matplotlib import colors [as 别名]

# 或者: from matplotlib.colors import hsv_to_rgb [as 别名]

def create_masks_of_cells(self, mean_img):

H = np.zeros_like(mean_img)

S = np.zeros_like(mean_img)

columncol = self.parent.colors['istat'][0]

for n in np.arange(np.shape(self.parent.iscell)[0]):

if self.parent.iscell[n] == 1:

ypix = self.parent.stat[n]['ypix'].flatten()

xpix = self.parent.stat[n]['xpix'].flatten()

H[ypix, xpix] = np.random.rand()

S[ypix, xpix] = 1

pix = np.concatenate(((H[:, :, np.newaxis]),

S[:, :, np.newaxis],

mean_img[:, :, np.newaxis]), axis=-1)

pix = hsv_to_rgb(pix)

return pix

开发者ID:MouseLand，项目名称:suite2p，代码行数:19，

示例8: flow_visualize

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# 需要导入模块: from matplotlib import colors [as 别名]

# 或者: from matplotlib.colors import hsv_to_rgb [as 别名]

def flow_visualize(flow, max_range = 1e3):

""" Original code from SINTEL toolbox, by Jonas Wulff.

"""

import matplotlib.colors as colors

du = flow[:, :, 0]

dv = flow[:, :, 1]

[h,w] = du.shape

max_flow = min(max_range, np.max(np.sqrt(du * du + dv * dv)))

img = np.ones((h, w, 3), dtype=np.float64)

# angle layer

img[:, :, 0] = (np.arctan2(dv, du) / (2 * np.pi) + 1) % 1.0

# magnitude layer, normalized to 1

img[:, :, 1] = np.sqrt(du * du + dv * dv) / (max_flow + 1e-8)

# phase layer

#img[:, :, 2] = valid

# convert to rgb

img = colors.hsv_to_rgb(img)

# remove invalid point

img[:, :, 0] = img[:, :, 0]

img[:, :, 1] = img[:, :, 1]

img[:, :, 2] = img[:, :, 2]

return img

开发者ID:lvzhaoyang，项目名称:RefRESH，代码行数:24，

示例9: _single_hsv_to_rgb

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# 需要导入模块: from matplotlib import colors [as 别名]

# 或者: from matplotlib.colors import hsv_to_rgb [as 别名]

def _single_hsv_to_rgb(hsv):

"""Transform a color from the hsv space to the rgb."""

from matplotlib.colors import hsv_to_rgb

return hsv_to_rgb(array(hsv).reshape(1, 1, 3)).reshape(3)

开发者ID:birforce，项目名称:vnpy_crypto，代码行数:6，

示例10: hue_linspace_colors

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# 需要导入模块: from matplotlib import colors [as 别名]

# 或者: from matplotlib.colors import hsv_to_rgb [as 别名]

def hue_linspace_colors(n, sat=1.0, light=0.5):

return (hsv_to_rgb(np.dstack((

np.linspace(0., 1., n, endpoint=False),

np.ones(n) * sat,

np.ones(n) * light)))[0] * 255).astype(np.uint8)

开发者ID:tneumann，项目名称:skinning_decomposition_kavan，代码行数:7，

示例11: main

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# 需要导入模块: from matplotlib import colors [as 别名]

# 或者: from matplotlib.colors import hsv_to_rgb [as 别名]

def main():

M = np.zeros((IMAGE_SIZE, IMAGE_SIZE), np.complex)

y, x = np.ogrid[YMAX: YMIN: IMAGE_SIZE*SUPER_SAMPLING*1j,

XMIN: XMAX: IMAGE_SIZE*SUPER_SAMPLING*1j]

z = x + y*1j

for c in tqdm.tqdm(z.flatten()):

if escape(c):

for z in iterate(c):

x, y = complex_to_pixel(z)

if 0 <= x < IMAGE_SIZE and 0 <= y < IMAGE_SIZE:

M[x, y] += c

M /= (SUPER_SAMPLING * SUPER_SAMPLING)

hue = (np.angle(M) / np.pi + 1) / 2

x = np.minimum(1, np.absolute(M) / 18.0)

H = hue

S = np.maximum(np.minimum(1, 2 * (1 - np.tan(x))), 0)

V = np.minimum(1, 2 * np.sin(x))

V = np.power(V / np.max(V), 1/1.6)

HSV = np.stack((H, S, V), axis=2)

img = hsv_to_rgb(HSV)

fig = plt.figure(figsize=(IMAGE_SIZE/100.0, IMAGE_SIZE/100.0), dpi=100)

ax = fig.add_axes([0, 0, 1, 1], aspect=1)

ax.axis("off")

ax.imshow(img, interpolation="bilinear")

plt.show()

fig.savefig("buddhabrot.png")

开发者ID:neozhaoliang，项目名称:pywonderland，代码行数:29，

示例12: rgb_from_hsv_data

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# 需要导入模块: from matplotlib import colors [as 别名]

# 或者: from matplotlib.colors import hsv_to_rgb [as 别名]

def rgb_from_hsv_data(hue, saturation, value):

"""Creates image in RGB format from HSV data."""

return hsv_to_rgb(hsv_image(hue, saturation, value))

开发者ID:neuro-ml，项目名称:deep_pipe，代码行数:5，

示例13: segmentation_probabilities

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# 需要导入模块: from matplotlib import colors [as 别名]

# 或者: from matplotlib.colors import hsv_to_rgb [as 别名]

def segmentation_probabilities(image, probabilities, hue):

return hsv_to_rgb(hsv_image(hue, probabilities, image))

开发者ID:neuro-ml，项目名称:deep_pipe，代码行数:4，

示例14: masked_segmentation_probabilities

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# 需要导入模块: from matplotlib import colors [as 别名]

# 或者: from matplotlib.colors import hsv_to_rgb [as 别名]

def masked_segmentation_probabilities(image, probabilities, hue, mask):

return hsv_to_rgb(hsv_image(hue, np.where(mask, probabilities, 0), np.where(mask, 1, image)))

开发者ID:neuro-ml，项目名称:deep_pipe，代码行数:4，

示例15: test_rgb_hsv_round_trip

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# 需要导入模块: from matplotlib import colors [as 别名]

# 或者: from matplotlib.colors import hsv_to_rgb [as 别名]

def test_rgb_hsv_round_trip():

for a_shape in [(500, 500, 3), (500, 3), (1, 3), (3,)]:

np.random.seed(0)

tt = np.random.random(a_shape)

assert_array_almost_equal(tt,

mcolors.hsv_to_rgb(mcolors.rgb_to_hsv(tt)))

assert_array_almost_equal(tt,

mcolors.rgb_to_hsv(mcolors.hsv_to_rgb(tt)))

开发者ID:miloharper，项目名称:neural-network-animation，代码行数:10，

示例16: visualize_flow

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# 需要导入模块: from matplotlib import colors [as 别名]

# 或者: from matplotlib.colors import hsv_to_rgb [as 别名]

def visualize_flow(flow, mode='Y'):

"""

this function visualize the input flow

:param flow: input flow in array

:param mode: choose which color mode to visualize the flow (Y: Ccbcr, RGB: RGB color)

:return: None

"""

if mode == 'Y':

# Ccbcr color wheel

img = flow_to_image(flow)

plt.imshow(img)

plt.show()

elif mode == 'RGB':

(h, w) = flow.shape[0:2]

du = flow[:, :, 0]

dv = flow[:, :, 1]

valid = flow[:, :, 2]

max_flow = max(np.max(du), np.max(dv))

img = np.zeros((h, w, 3), dtype=np.float64)

# angle layer

img[:, :, 0] = np.arctan2(dv, du) / (2 * np.pi)

# magnitude layer, normalized to 1

img[:, :, 1] = np.sqrt(du * du + dv * dv) * 8 / max_flow

# phase layer

img[:, :, 2] = 8 - img[:, :, 1]

# clip to [0,1]

small_idx = img[:, :, 0:3] < 0

large_idx = img[:, :, 0:3] > 1

img[small_idx] = 0

img[large_idx] = 1

# convert to rgb

img = cl.hsv_to_rgb(img)

# remove invalid point

img[:, :, 0] = img[:, :, 0] * valid

img[:, :, 1] = img[:, :, 1] * valid

img[:, :, 2] = img[:, :, 2] * valid

# show

plt.imshow(img)

plt.show()

return None

开发者ID:ChenyangLEI，项目名称:Fully-Automatic-Video-Colorization-with-Self-Regularization-and-Diversity，代码行数:43，

示例17: save_plot_sample

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# 需要导入模块: from matplotlib import colors [as 别名]

# 或者: from matplotlib.colors import hsv_to_rgb [as 别名]

def save_plot_sample(samples, idx, identifier, n_samples=6, num_epochs=None, ncol=2):

assert n_samples <= samples.shape[0]

assert n_samples % ncol == 0

sample_length = samples.shape[1]

if not num_epochs is None:

col = hsv_to_rgb((1, 1.0*(idx)/num_epochs, 0.8))

else:

col = 'grey'

x_points = np.arange(sample_length)

nrow = int(n_samples/ncol)

fig, axarr = plt.subplots(nrow, ncol, sharex=True, figsize=(6, 6))

for m in range(nrow):

for n in range(ncol):

# first column

sample = samples[n*nrow + m, :, 0]

axarr[m, n].plot(x_points, sample, color=col)

axarr[m, n].set_ylim(-1, 1)

for n in range(ncol):

axarr[-1, n].xaxis.set_ticks(range(0, sample_length, int(sample_length/4)))

fig.suptitle(idx)

fig.subplots_adjust(hspace = 0.15)

fig.savefig("./experiments/plots/" + identifier + "_epoch" + str(idx).zfill(4) + ".png")

plt.clf()

plt.close()

return

开发者ID:ratschlab，项目名称:RGAN，代码行数:30，

示例18: save_plot_vary_dimension

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# 需要导入模块: from matplotlib import colors [as 别名]

# 或者: from matplotlib.colors import hsv_to_rgb [as 别名]

def save_plot_vary_dimension(samples_list, idx, identifier, n_dim):

"""

"""

assert len(samples_list) == n_dim

sample_length = samples_list[0].shape[1]

x_points = np.arange(sample_length)

nrow = samples_list[0].shape[0]

sidelength = n_dim*1.5

fig, axarr = plt.subplots(nrow, n_dim, sharex=True, sharey=True, figsize=(sidelength, sidelength))

for dim in range(n_dim):

sample_dim = samples_list[dim]

axarr[0, dim].set_title(dim)

h = dim*1.0/n_dim # hue

for n in range(nrow):

sample = sample_dim[n, :, 0]

axarr[n, dim].plot(x_points, sample, color='black')

axarr[n, dim].spines["top"].set_visible(False)

axarr[n, dim].spines["bottom"].set_visible(False)

axarr[n, dim].spines["right"].set_visible(False)

axarr[n, dim].spines["left"].set_visible(False)

axarr[n, dim].tick_params(bottom='off', left='off')

axarr[n, dim].get_xaxis().set_visible(False)

axarr[n, dim].set_facecolor(hsv_to_rgb((h, 0 + 0.25*n/nrow, 0.96)))

axarr[-1, dim].xaxis.set_ticks(range(0, sample_length, int(sample_length/4)))

fig.suptitle(idx)

fig.subplots_adjust(hspace = 0.11, wspace=0.11)

fig.savefig("./experiments/plots/" + identifier + "_epoch" + str(idx).zfill(4) + ".png")

plt.clf()

plt.close()

return True

开发者ID:ratschlab，项目名称:RGAN，代码行数:34，

示例19: get_gamma_colors

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# 需要导入模块: from matplotlib import colors [as 别名]

# 或者: from matplotlib.colors import hsv_to_rgb [as 别名]

def get_gamma_colors(nr_colors):

hsv_colors = np.ones((nr_colors, 3))

hsv_colors[:, 0] = (np.linspace(0, 1, nr_colors, endpoint=False) + 2/3) % 1.0

color_conv = hsv_to_rgb(hsv_colors)

return color_conv

开发者ID:e2crawfo，项目名称:auto_yolo，代码行数:7，

示例20: _get_rgb_phase_array

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# 需要导入模块: from matplotlib import colors [as 别名]

# 或者: from matplotlib.colors import hsv_to_rgb [as 别名]

def _get_rgb_phase_array(phase, rotation=None, max_phase=2 * np.pi, phase_lim=None):

phase = _find_phase(phase, rotation=rotation, max_phase=max_phase)

phase = phase / (2 * np.pi)

S = np.ones_like(phase)

HSV = np.dstack((phase, S, S))

RGB = hsv_to_rgb(HSV)

return RGB

开发者ID:pyxem，项目名称:pyxem，代码行数:9，

示例21: hsv2rgb

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# 需要导入模块: from matplotlib import colors [as 别名]

# 或者: from matplotlib.colors import hsv_to_rgb [as 别名]

def hsv2rgb(cols):

cols = cols[:,np.newaxis]

cols = np.concatenate((cols, np.ones_like(cols), np.ones_like(cols)), axis=-1)

cols = (255 * hsv_to_rgb(cols)).astype(np.uint8)

return cols

开发者ID:MouseLand，项目名称:suite2p，代码行数:7，

示例22: rgb_masks

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# 需要导入模块: from matplotlib import colors [as 别名]

# 或者: from matplotlib.colors import hsv_to_rgb [as 别名]

def rgb_masks(parent, col, c):

for i in range(2):

#S = np.expand_dims(parent.rois['Sroi'][i],axis=2)

H = col[parent.rois['iROI'][i,0], :]

#H = np.expand_dims(H,axis=2)

#hsv = np.concatenate((H,S,S),axis=2)

#rgb = (hsv_to_rgb(hsv)*255).astype(np.uint8)

parent.colors['RGB'][i,c,:,:,:3] = H

开发者ID:MouseLand，项目名称:suite2p，代码行数:10，

示例23: __init__

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# 需要导入模块: from matplotlib import colors [as 别名]

# 或者: from matplotlib.colors import hsv_to_rgb [as 别名]

def __init__(self, iROI, parent=None, pos=None, diameter=None, color=None,

yrange=None, xrange=None):

# what type of ROI it is

self.iROI = iROI

self.xrange = xrange

self.yrange = yrange

if color is None:

self.color = hsv_to_rgb(np.array([np.random.rand() / 1.4 + 0.1, 1, 1]))

self.color = tuple(255 * self.color)

else:

self.color = color

if pos is None:

view = parent.p0.viewRange()

imx = (view[0][1] + view[0][0]) / 2

imy = (view[1][1] + view[1][0]) / 2

dx = (view[0][1] - view[0][0]) / 4

dy = (view[1][1] - view[1][0]) / 4

if diameter is None:

dx = np.maximum(3, np.minimum(dx, parent.Ly * 0.2))

dy = np.maximum(3, np.minimum(dy, parent.Lx * 0.2))

else:

dx = diameter

dy = diameter

imx = imx - dx / 2

imy = imy - dy / 2

else:

imy = pos[0]

imx = pos[1]

dy = pos[2]

dx = pos[3]

self.draw(parent, imy, imx, dy, dx)

self.position(parent)

self.ROI.sigRegionChangeFinished.connect(lambda: self.position(parent))

self.ROI.sigClicked.connect(lambda: self.position(parent))

self.ROI.sigRemoveRequested.connect(lambda: self.remove(parent))

开发者ID:MouseLand，项目名称:suite2p，代码行数:39，

注：本文中的matplotlib.colors.hsv_to_rgb方法示例整理自Github/MSDocs等源码及文档管理平台，相关代码片段筛选自各路编程大神贡献的开源项目，源码版权归原作者所有，传播和使用请参考对应项目的License；未经允许，请勿转载。