今天把基本的畫圖技巧都學了一遍,以下是自己綜合後基本會用到的畫圖技巧:
import
numpy as np
from
pylab
import
*
import
matplotlib.pyplot as plt
import
random
# Draw plot one:
number
=
256
x
=
np.linspace(
-
np.pi,np.pi,number)
y
=
np.sin(x)
plt.subplot(
2
,
1
,
1
)
# (行,列,活跃区)
cr
=
np.random.random()
cg
=
np.random.random()
cb
=
np.random.random()
plt.plot(x,y,color
=
(cr, cg, cb ),linewidth
=
2.0
, label
=
'sin(x)'
)
legend(loc
=
'upper left'
)
plt.xlabel(
'x'
,fontsize
=
10
)
plt.ylabel(r
'$\Delta$'
,fontsize
=
10
)
xlim(x.
min
()
*
1.1
,x.
max
()
*
1.1
)
ylim(y.
min
()
*
1.1
,y.
max
()
*
1.1
)
number2
=
100
xx
=
np.random.rand(number2)
yy
=
np.random.rand(number2)
color
=
np.random.rand(number2)
size
=
20
marker
=
'o'
colormap
=
plt.cm.get_cmap(
'BuPu_r'
)
# _r let color of colorbar up-side-down
plt.subplot(
2
,
1
,
2
)
plt.subplots_adjust(hspace
=
0.4
)
plt.scatter(xx,yy,size,color,marker,colormap)
plt.xlabel(r
'XX'
,fontsize
=
10
)
plt.ylabel(r
'YY'
,fontsize
=
10
)
plt.colorbar()
plt.show()
# View all cmaps in python:
plt.colormaps()
import
numpy as np
import
matplotlib.pyplot as plt
n
=
100000
x
=
np.random.standard_normal(n)
# Normal distribution in x
y
=
2.0
+
3.0
*
x
+
4.0
*
np.random.standard_normal(n)
# Normal distribution in y
plt.hexbin(x,y)
plt.colorbar()
plt.show()
其中畫圖的顏色,在plt.plot()裡面用的繪圖顏色原則:
在colormap裡的顏色使用原則:
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