攝影或3C

Python:如何將x 軸移動到 matplotlib 中繪圖的頂部? ax.xaxis.set_label_position(“top”) ; ax.xaxis.tick_top() ; ax.set_xticks( ticks=list1, label=list2, rotation=45) #幫刻度值取別名; 如何用loc參數設定title/label位置?存檔的圖片若被裁切如何設定? bbox_inches = ‘tight’

參考stack overflow

import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
#import seaborn as sbn

PI = np.pi
x = np.linspace(0,2*PI,100)
y = np.sin(x)

fig, ax = plt.subplots(1,1)
#這行可改為: ax=plt.axes()

#但 fig, ax = plt.subplots() 較好

#fig.savefig() 存檔時, 需要fig物件

ax.scatter(x,y)

#ax.set_xticks([0,PI/2,PI, 3*PI/2,PI],minor=False)
#ax.set_yticks(minor=True)

ax.invert_yaxis()
ax.set_xlabel(“angle”)
ax.xaxis.set_label_position(“top”) #這是把label移到頂端
ax.xaxis.tick_top() #這才是把刻度線移到頂部
ax.set_title(“sin function”,fontsize=18)

如果想讓橫軸顯示PI, 2PI……

如果想顯示符號的PI

x_ticks = np.arange(0, 2*np.pi+0.01, np.pi/4)

labels = [‘$0$’, r’$\pi/4$’ , r’$\pi/2$’, r’$3\pi/4$’, r’$\pi$’, r’$5\pi/4$’, r’$3\pi/2$’, r’$7\pi/4$’, r’$2\pi$’]

plt.xticks(x_ticks, labels=labels)

格式化轉義可參考此篇:

# 格式化轉義字符串首尾 r’$…$’ （matplotlib中）
# xticks(loc, labels): labels 格式化轉義方法 r’$-\frac{\pi}{2}$’ 留意分數的表示方式
# pi需要轉義才能顯示爲字符 pai. 若$-pi$ 則直接顯示-pi
# 如果沒有第二個[]參數，刻度值顯示如-3.142, -1.571…等浮點數，而不是-pi

如何用loc參數設定title/label位置?

import pandas as pd
import matplotlib.pyplot as plt
import matplotlib as mpl
fpath = r”C:\22056 EPP IL\IL.xlsx”
df = pd.read_excel(fpath,header=None)
df_ILvsFreq = df.iloc[:,[7,8]].reset_index(drop=True)
df_ILvsFreq_drop = df_ILvsFreq.dropna(axis=0,how=”all”).reset_index(drop=True)
df_data = df_ILvsFreq_drop.iloc[1:,:].reset_index(drop=True)
dfx = df_data[7]
dfy = df_data[8]

fig,ax = plt.subplots()
ax.plot(dfx,dfy)
ax.set_title(“Insertion Loss vs Frequency”,fontsize=16,loc=”center”)
#loc=”center” ,”right” , “left”

ax.set_xlabel(“Frequency(GHZ)”,loc=”right”)
ax.set_ylabel(“Insertion Loss(dB)”)

#ylabel的loc,可以設定”bottom” , “top”
ax.get_xaxis().set_minor_locator(mpl.ticker.AutoMinorLocator() )
ax.get_yaxis().set_minor_locator(mpl.ticker.AutoMinorLocator() )

#plt.minorticks_on()
ax.grid(visible=True,which=”major”,c=”k”,linewidth=1)
ax.grid(visible=True,which=”minor”,c=”k”,linewidth=0.5)
ax.xaxis.set_label_position(“top”) ;
ax.xaxis.tick_top()
fig.savefig(r”C:\22056 EPP IL\ILvsFreq”)

#fig.savefig(r”C:\22056 EPP IL\ILvsFreq”,bbox_inches = ‘tight’)

#存檔的圖片若有被截斷的狀況

#可以加參數bbox_inches = ‘tight’