Python绘图模板整理
日常科研绘图python绘图模板收集
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棒棒糖图
1 | from cProfile import label |
密度图(Python)
1 | def density(): |
y轴堆叠图
1 | import matplotlib.pyplot as plt |
1 | for i0 in range(1,10): |
这里只需要把(i0 - 1)*2去掉就可以实现非堆叠的效果。
变色圆环
有时候想画一个随着角度变化的密度图，这里就给出一个例子，主要就是将matplotlib官网中的例子进行了修改1
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45import matplotlib.tri as tri
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import rcParams
import os
config = {
"font.size": 30,
"mathtext.fontset":'stix',
"font.serif": ['SimSun'],
}
rcParams.update(config) # Latex 字体设置
#---------------------------------------
def pltring():
n_angles = 100
n_radii = 8
min_radius = 0.7
radii = np.linspace(min_radius, 0.95, n_radii)
angles = np.linspace(0, 2 * np.pi, n_angles, endpoint=False)
angles = np.repeat(angles[..., np.newaxis], n_radii, axis=1)
angles[:, 1::2] += np.pi / n_angles
x = (radii * np.cos(angles)).flatten()
y = (radii * np.sin(angles)).flatten()
z = (np.abs(np.sin(3 * angles))).flatten()
# Create the Triangulation; no triangles so Delaunay triangulation created.
triang = tri.Triangulation(x, y)
# Mask off unwanted triangles.
triang.set_mask(np.hypot(x[triang.triangles].mean(axis=1),
y[triang.triangles].mean(axis=1))
< min_radius)
# plt.figure(figsize=(12,12))
fig2, ax2 = plt.subplots(figsize=(10,10))
ax2.set_aspect('equal')
tpc = ax2.tripcolor(triang, z, shading='gouraud',cmap = "cividis_r")
cb = fig2.colorbar(tpc,fraction = 0.045)
cb.ax.tick_params(labelsize=20)
plt.yticks([-1,0,1],fontproperties='Times New Roman', size = 40)
plt.xticks([-1,0,1],fontproperties='Times New Roman', size = 40)
# plt.show()
picname = "phase-3.png"
plt.savefig(picname, dpi=100, bbox_inches = 'tight')
plt.close()
1 | def pltring(cont): |
高对称路径能带图
1 | import numpy as np |
密度图2
1 | def ldosplt(cont): |
线图+scatter
1 | import numpy as np |
自定义colorbar
1 | def plotchi2(numk): |
子图排列
1 | import numpy as np |
曲线填充
1 | import numpy as np |
密度图3
1 | import numpy as np |
密度等高线图
1 | import numpy as np |
限制绘图区域
1 | def plotVscr3(): |
费米点+矢量箭头
数据生成代码1
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45module code_param
implicit none
integer, parameter :: dp = kind(1.0)
real(dp),parameter::pi = acos(-1.0)
complex(dp),parameter::im = (0.,1.) ! Imagine unit
real(dp) delta_E
integer nkx,nky,ne
parameter(delta_E = 1e-4,nkx = 301,nky = 101,ne = 10)
end module code_param
!==============================================================================================================================================================
program main
use code_param
implicit none
call Gas_2D()
stop
end program main
!==============================================================================================================================================================
subroutine Gas_2D()
! 自由电子气测试
use code_param
implicit none
real(dp) t0,ek,kx,ky,mu
integer kn,ikx,iky,ik0
kn = 50
mu = 0.0
t0 = 1.0
open(30,file = "FS.dat")
open(31,file = "Arrow.dat")
do ikx = -kn,kn
do iky = -kn,kn
kx = pi * ikx/kn
ky = pi * iky/kn
ek = -t0 * (cos(kx) + cos(ky))
if(abs(ek - mu) .le. delta_E)then
write(30,"(20F15.8)")kx,ky,ek,sin(kx),sin(ky),sin(kx + ky),sqrt(sin(kx)**2 + sin(ky)**2)
end if
if(abs(ek - mu) .le. 1e-3 * delta_E)then
write(31,"(20F15.8)")kx,ky,ek,sin(kx),sin(ky),sin(kx + ky),sqrt(sin(kx)**2 + sin(ky)**2)
end if
end do
end do
close(30)
close(31)
end subroutine
绘图代码1
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111import numpy as np
import matplotlib.pyplot as plt
from matplotlib import rcParams
import os
import matplotlib.gridspec as gridspec
from matplotlib.path import Path
import matplotlib.colors as mcolors
plt.rc('font', family='Times New Roman')
config = {
"font.size": 30,
"mathtext.fontset":'stix',
"font.serif": ['SimSun'],
}
rcParams.update(config) # Latex 字体设置
#------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
def plotfs():
# 简单绘制个费米面
dataname = "FS.dat"
picname = os.path.splitext(dataname)[0] + ".png"
da = np.loadtxt(dataname)
plt.figure(figsize = (10,8))
# pair = da2[:,con1 - 1]
pair = da[:,4]
vmin, vmax = np.min(pair), np.max(pair)
norm = mcolors.TwoSlopeNorm(vmin = vmin, vcenter = 0, vmax = vmax)
sc = plt.scatter(da[:,0],da[:,1], c = da[:,4] ,s = 5, cmap = "seismic")
# sc = plt.scatter(da[:,0],da[:,1], c = da[:,3] ,s = 5, cmap = "seismic",norm = norm)
cb = plt.colorbar(sc,fraction = 0.1,ticks = [np.min(pair),0,np.max(pair)],extend='both',label = r"$\lambda$") # 调整colorbar的大小和图之间的间距
cb.ax.tick_params(size = 0)
cb.ax.set_yticklabels([format(np.min(pair),".1f"), format(0,".1f"),format(np.max(pair),".1f")])
valx = 0.5
valy = 0.5
plt.xlim(-valx,valx)
plt.ylim(-valy,valy)
plt.tick_params(direction = 'in' ,axis = 'x',width = 0,length = 10)
plt.tick_params(direction = 'in' ,axis = 'y',width = 0,length = 10)
# plt.axis('scaled')
ax = plt.gca()
ax.spines["bottom"].set_linewidth(1.5)
ax.spines["left"].set_linewidth(1.5)
ax.spines["right"].set_linewidth(1.5)
ax.spines["top"].set_linewidth(1.5)
# plt.show()
plt.savefig(picname, dpi = 300,bbox_inches = 'tight')
plt.close()
#------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
def plotfs_2():
# 绘制有颜色的
da1 = "FS.dat"
da2 = "Arrow.dat"
# picname = os.path.splitext(da1)[0] + ".png"
picname = "Results.png"
da1 = np.loadtxt(da1)
da2 = np.loadtxt(da2)
plt.figure(figsize = (10,8))
# pair = da2[:,con1 - 1]
pair = da1[:,4]
vmin, vmax = np.min(pair), np.max(pair)
norm = mcolors.TwoSlopeNorm(vmin = vmin, vcenter = 0, vmax = vmax)
sc = plt.scatter(da1[:,0],da1[:,1], c = da1[:,4] ,s = 5, cmap = "seismic")
# sc = plt.scatter(da[:,0],da[:,1], c = da[:,3] ,s = 5, cmap = "seismic",norm = norm)
cb = plt.colorbar(sc,fraction = 0.1,ticks = [np.min(pair),0,np.max(pair)],extend='both',label = r"$\lambda$") # 调整colorbar的大小和图之间的间距
cb.ax.tick_params(size = 0)
cb.ax.set_yticklabels([format(np.min(pair),".1f"), format(0,".1f"),format(np.max(pair),".1f")])
#----------------
# 矢量起点坐标 (kx,ky)
x0 = np.array(da2[:,0])
y0 = np.array(da2[:,1])
# 矢量方向(v0,u0)
v0 = np.array(da2[:,2]) * 10 # 向量场方向
u0 = np.array(da2[:,3]) * 10
magnitude = da2[:,5] # 控制箭头颜色
# plt.quiver(x0, y0, v0, u0, color='b', angles='xy', scale_units='xy', scale=2)
sc = plt.quiver(x0, y0, v0, u0, magnitude, cmap = 'plasma', angles='xy', scale_units='xy', scale = 10)
# vmin, vmax = np.min(magnitude), np.max(magnitude)
# norm = mcolors.TwoSlopeNorm(vmin = vmin, vcenter = 0, vmax = vmax)
cb = plt.colorbar(sc,fraction = 0.1,ticks = [np.min(magnitude),0,np.max(magnitude)],extend='both',label = r"$s_z$") # 调整colorbar的大小和图之间的间距
cb.set_label(r"$s_z$", labelpad = -35) # 设置 labelpad 调整距离
cb.ax.tick_params(size = 0)
cb.ax.set_yticklabels([format(np.min(magnitude),".1f"), format(0,".1f"),format(np.max(magnitude),".1f")])
# plt.quiver(x0, y0, v0, u0, magnitude, cmap='seismic', scale = 5)
# xtic = [-np.pi,0,np.pi]
# xticlab = ["$-\pi$","$0$","$\pi$"]
# plt.xticks(xtic,list(xticlab),fontproperties='Times New Roman', size = 40)
# plt.yticks(xtic,list(xticlab),fontproperties='Times New Roman', size = 40)
# valx = 0.5
# valy = 0.5
# plt.xlim(-valx,valx)
# plt.ylim(-valy,valy)
plt.tick_params(direction = 'in' ,axis = 'x',width = 0,length = 10)
plt.tick_params(direction = 'in' ,axis = 'y',width = 0,length = 10)
# plt.axis('scaled')
ax = plt.gca()
ax.spines["bottom"].set_linewidth(1.5)
ax.spines["left"].set_linewidth(1.5)
ax.spines["right"].set_linewidth(1.5)
ax.spines["top"].set_linewidth(1.5)
# plt.show()
plt.savefig(picname, dpi = 300,bbox_inches = 'tight')
plt.close()
#------------------------------------------------------------
if __name__=="__main__":
# plotfs()
plotfs_2()
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