[英]Is it possible to get color gradients under curve in matplotlib?
There have been a handful of previous answers to similar questions (eg https://stackoverflow.com/a/22081678/325565 ), but they recommend a sub-optimal approach.之前有一些类似问题的答案(例如https://stackoverflow.com/a/22081678/325565 ),但他们推荐了一种次优方法。
Most of the previous answers recommend plotting a white polygon over a pcolormesh
fill.以前的大多数答案都建议在
pcolormesh
填充上绘制一个白色多边形。 This is less than ideal for two reasons:这不太理想,原因有两个:
pcolormesh
is fairly slow to draw and isn't smoothly interpolated. pcolormesh
绘制速度相当慢,并且不能顺利插入。 It's a touch more work, but there's a method that draws much faster and gives a better visual result: Set the clip path of an image plotted with imshow
.这是更多的工作,但有一种方法可以更快地绘制并提供更好的视觉效果:设置使用
imshow
绘制的图像的剪辑路径。
As an example:举个例子:
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.colors as mcolors
from matplotlib.patches import Polygon
np.random.seed(1977)
def main():
for _ in range(5):
gradient_fill(*generate_data(100))
plt.show()
def generate_data(num):
x = np.linspace(0, 100, num)
y = np.random.normal(0, 1, num).cumsum()
return x, y
def gradient_fill(x, y, fill_color=None, ax=None, **kwargs):
"""
Plot a line with a linear alpha gradient filled beneath it.
Parameters
----------
x, y : array-like
The data values of the line.
fill_color : a matplotlib color specifier (string, tuple) or None
The color for the fill. If None, the color of the line will be used.
ax : a matplotlib Axes instance
The axes to plot on. If None, the current pyplot axes will be used.
Additional arguments are passed on to matplotlib's ``plot`` function.
Returns
-------
line : a Line2D instance
The line plotted.
im : an AxesImage instance
The transparent gradient clipped to just the area beneath the curve.
"""
if ax is None:
ax = plt.gca()
line, = ax.plot(x, y, **kwargs)
if fill_color is None:
fill_color = line.get_color()
zorder = line.get_zorder()
alpha = line.get_alpha()
alpha = 1.0 if alpha is None else alpha
z = np.empty((100, 1, 4), dtype=float)
rgb = mcolors.colorConverter.to_rgb(fill_color)
z[:,:,:3] = rgb
z[:,:,-1] = np.linspace(0, alpha, 100)[:,None]
xmin, xmax, ymin, ymax = x.min(), x.max(), y.min(), y.max()
im = ax.imshow(z, aspect='auto', extent=[xmin, xmax, ymin, ymax],
origin='lower', zorder=zorder)
xy = np.column_stack([x, y])
xy = np.vstack([[xmin, ymin], xy, [xmax, ymin], [xmin, ymin]])
clip_path = Polygon(xy, facecolor='none', edgecolor='none', closed=True)
ax.add_patch(clip_path)
im.set_clip_path(clip_path)
ax.autoscale(True)
return line, im
main()
Please note Joe Kington deserves the lion's share of the credit here;请注意, Joe Kington 在此应得的大部分功劳; my sole contribution is
zfunc
.我唯一的贡献是
zfunc
。 His method opens to door to many gradient/blur/drop-shadow effects.他的方法为许多渐变/模糊/阴影效果打开了大门。 For example, to make the lines have an evenly blurred underside, you could use PIL to build an alpha layer which is 1 near the line and 0 near the bottom edge.
例如,要使线条具有均匀模糊的底面,您可以使用 PIL 构建一个 alpha 图层,该图层在线条附近为 1,在底部边缘附近为 0。
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.colors as mcolors
import matplotlib.patches as patches
from PIL import Image
from PIL import ImageDraw
from PIL import ImageFilter
np.random.seed(1977)
def demo_blur_underside():
for _ in range(5):
# gradient_fill(*generate_data(100), zfunc=None) # original
gradient_fill(*generate_data(100), zfunc=zfunc)
plt.show()
def generate_data(num):
x = np.linspace(0, 100, num)
y = np.random.normal(0, 1, num).cumsum()
return x, y
def zfunc(x, y, fill_color='k', alpha=1.0):
scale = 10
x = (x*scale).astype(int)
y = (y*scale).astype(int)
xmin, xmax, ymin, ymax = x.min(), x.max(), y.min(), y.max()
w, h = xmax-xmin, ymax-ymin
z = np.empty((h, w, 4), dtype=float)
rgb = mcolors.colorConverter.to_rgb(fill_color)
z[:,:,:3] = rgb
# Build a z-alpha array which is 1 near the line and 0 at the bottom.
img = Image.new('L', (w, h), 0)
draw = ImageDraw.Draw(img)
xy = (np.column_stack([x, y]))
xy -= xmin, ymin
# Draw a blurred line using PIL
draw.line(map(tuple, xy.tolist()), fill=255, width=15)
img = img.filter(ImageFilter.GaussianBlur(radius=100))
# Convert the PIL image to an array
zalpha = np.asarray(img).astype(float)
zalpha *= alpha/zalpha.max()
# make the alphas melt to zero at the bottom
n = zalpha.shape[0] // 4
zalpha[:n] *= np.linspace(0, 1, n)[:, None]
z[:,:,-1] = zalpha
return z
def gradient_fill(x, y, fill_color=None, ax=None, zfunc=None, **kwargs):
if ax is None:
ax = plt.gca()
line, = ax.plot(x, y, **kwargs)
if fill_color is None:
fill_color = line.get_color()
zorder = line.get_zorder()
alpha = line.get_alpha()
alpha = 1.0 if alpha is None else alpha
if zfunc is None:
h, w = 100, 1
z = np.empty((h, w, 4), dtype=float)
rgb = mcolors.colorConverter.to_rgb(fill_color)
z[:,:,:3] = rgb
z[:,:,-1] = np.linspace(0, alpha, h)[:,None]
else:
z = zfunc(x, y, fill_color=fill_color, alpha=alpha)
xmin, xmax, ymin, ymax = x.min(), x.max(), y.min(), y.max()
im = ax.imshow(z, aspect='auto', extent=[xmin, xmax, ymin, ymax],
origin='lower', zorder=zorder)
xy = np.column_stack([x, y])
xy = np.vstack([[xmin, ymin], xy, [xmax, ymin], [xmin, ymin]])
clip_path = patches.Polygon(xy, facecolor='none', edgecolor='none', closed=True)
ax.add_patch(clip_path)
im.set_clip_path(clip_path)
ax.autoscale(True)
return line, im
demo_blur_underside()
yields产量
I've tried something :我试过一些东西:
import matplotlib.pyplot as plt
import numpy as np
fig = plt.figure()
xData = range(100)
yData = range(100)
plt.plot(xData, yData)
NbData = len(xData)
MaxBL = [[MaxBL] * NbData for MaxBL in range(100)]
Max = [np.asarray(MaxBL[x]) for x in range(100)]
for x in range (50, 100):
plt.fill_between(xData, Max[x], yData, where=yData >Max[x], facecolor='red', alpha=0.02)
for x in range (0, 50):
plt.fill_between(xData, yData, Max[x], where=yData <Max[x], facecolor='green', alpha=0.02)
plt.fill_between([], [], [], facecolor='red', label="x > 50")
plt.fill_between([], [], [], facecolor='green', label="x < 50")
plt.legend(loc=4, fontsize=12)
plt.show()
fig.savefig('graph.png')
.. and the result: .. 结果:
Of course the gradient could go down to 0 by changing the range of feel_between
function.当然,通过改变
feel_between
函数的范围,梯度可以降到0。
just reopening this thread, so just re-opening this thread, ive used a vast majority of joe's code however i cant for the life of me figure out how to shade using 0 at the X axis instead of this upward sloping limit.只是重新打开这个线程,所以只是重新打开这个线程,我使用了绝大多数 joe 的代码,但是我一生都无法弄清楚如何在 X 轴上使用 0 而不是这个向上倾斜的限制来进行着色。
ideally in the belly of the data it should be weak colours and at the heavy positive and negative numbers the extreme colours, i would like the Line for where the shading starts/stops to be the horizontal (0) instead im getting this weird sloping axis which i just dont understand how to rectify.理想情况下,在数据的腹部,它应该是弱颜色,在大量的正负数处是极端颜色,我希望阴影开始/停止的线为水平(0)而不是我得到这个奇怪的倾斜轴我只是不明白如何纠正。
i have a previous chart which you can see (non gradient) what im trying to achieve.我有一个以前的图表,您可以看到(非渐变)我试图实现的目标。 and the red gradient chart im messing up.
和红色渐变图表我搞砸了。
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.colors as mcolors
from matplotlib.patches import Polygon
# Variables
AUM = df['#AHD_AUM'].head(104)
MM = df['#AHD_Managed_Money_Net'].head(104)
PRICE = df['#AHD_Price'].head(104)
DATES = df['DATES'].head(104)
# Date Friendly Variables for Plot
List_AUM = df['#AHD_AUM'].head(104).to_list()
List_MM = df['#AHD_Managed_Money_Net'].head(104).to_list()
List_DATES = df['DATES'].head(104).to_list()
X = 0 * df['#AHD_AUM'].head(104)
# Make a date list changing dates with numbers to avoid the issue with the plot
interpreting dates
for i in range(len(df['DATES'].head(104))):
count = i
df['count'][i] = 120 - i
# X and Y data variables changed to arrays as when i had these set as dates
matplotlib hates it
x = df['count'].head(104).to_numpy()
y = df['#AHD_Managed_Money_Net'].head(104).to_numpy()
#DD = AUM.to_numpy()
#MMM = MM.to_numpy()
def main():
for _ in range(len(DD)):
gradient_fill(x,y)
plt.show()
def gradient_fill(x,y, fill_color=None, ax=None, **kwargs):
"""
"""
if ax is None:
ax = plt.gca()
line, = ax.plot(x, y, **kwargs)
if fill_color is None:
fill_color = line.get_color()
zorder = line.get_zorder()
alpha = line.get_alpha()
alpha = 1.0 if alpha is None else alpha
z = np.empty((100, 1, 4), dtype=float)
rgb = mcolors.colorConverter.to_rgb(fill_color)
z[:,:,:3] = rgb
z[:,:,-1] = np.linspace(0, alpha, 100)[:,None]
xmin, xmax, ymin, ymax = x.min(), x.max(), y.min(), y.max()
im = ax.imshow(z, aspect='auto', extent=[xmin, xmax, ymin, ymax],
origin='lower', zorder=zorder)
xy = np.column_stack([x, y])
# xy = np.vstack([[xmin, ymin], xy, [xmax, ymin], [xmin, ymin]]) ### i dont
need this so i have just commented it out
clip_path = Polygon(xy, facecolor='none', edgecolor='none', closed=True)
ax.add_patch(clip_path)
im.set_clip_path(clip_path)
ax.autoscale(True)
return line, im
main()
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