Python Notes

5 minute read

Published:

Content

Python

import

import numpy as np
import matplotlib
import matplotlib.pyplot as plt
from matplotlib.font_manager import FontProperties
from matplotlib.ticker import MultipleLocator
import os
import plotly.graph_objects as go
import scipy as sp

For testing

a=np.array([[1,2,3],[4,5,6],[7,8,9]]) 
b=np.array([1,2,3])

Join elements of list into string with same connector

'_'.join(a)

Latex coding into string

r'$\lambda$'

Format string

  • f'{a}' Symbol a will be substitute with value of a in float
  • f'{abc:f5} Character length of 5
  • f'{abc:>5} Justified to the right with character length of 5
  • f'{abc:<5} Justified to the left with character length of 5

Write file

f = open('filename', mode='w')

for line in list:

f.write(line+'\n')

Or

f.writelines(list)

New method:

with open(input_file, 'r') as f: 
  contents = f.readlines()
for line_index, line in enumerate(contents):

with open(input_file, 'w') as f: 
contents = ''.join(contents)

f.write(contents)

Numpy

Returns the indices that would sort an array.

  • np.argsort(array_name, axis=0, kind=None, order=None) axis=0 sort by row, axis=1 sort by column
  • np.sort(array_name, axis=0, kind=None, order=None) return sorted array
  • array[np.argsort(array[2])] gives sorted array by array[2]

Size of array

np.size(a, axis=0)

  • axis=0 : number of rows
  • axis=1 : number of columns

Delete specific elements of vector

np.delete(a, 3)

3 is index of the element to be deleted

Fitting

p=np.polyfit(x,y,3) cubic fitting 
e=np.linspace(min,max,steps) 
ax.plot(e,np.polyval(p,e))

Least square (Ax=>b)

np.linalg.lstsq(A,y,rcond=None/'warn')

Returns a list The resulting vector x is [0]

Solve a group of linear equations (Ax=b)

np.linalg.solve(A,b)

Returns vector x

Higher order Interpolation

  • f=sp.interpolate.PchipInterpolator(x,y) Piecewise Cubic Hermite Interpolating Polynomial
  • f=sp.interpolate.CubicSpline(x,y)
  • f=sp.interpolate.make_interp_spline(x,y,k=3)
  • minimum = sp.optimize.fmin(f,3.1)[0]

Matplotlib

fig,ax = plt.subplots(1,1,figsize=(6,5), dpi=200, sharex=True, sharey=True,width_ratios=[1])
plt.style.use("default")
plt.rcParams["lines.linewidth"] = 2
plt.rcParams["axes.linewidth"] = 1
plt.rcParams["xtick.major.width"] = 1
plt.rcParams["ytick.major.width"] = 1
plt.rcParams["xtick.minor.width"] = 1
plt.rcParams["ytick.minor.width"] = 1
xmajorLocator = MultipleLocator(5)
ax.xaxis.set_major_locator(xmajorLocator)
ymajorLocator = MultipleLocator(5)
ax.yaxis.set_major_locator(ymajorLocator)
font = FontProperties(fname="../arial.ttf", size=12)

Marker

markermap = ["*", "D", "o", "s", "^"]

ax.plot(x, y, marker='*', markersize=20) Hollow marker: markerfacecolor='none',markeredgecolor=colormap

fill between

ax.fill_between(x,y,0,alpha=0.6)

Figure title, label

  • fig.supxlabel('')
  • fig.supylabel('')
  • fig.suptitle(''")

Real Colormap

colormap = ax.plot(x, y, color=plt.cm.get_cmap('colormapname')(np.linspace(0,1,n)
ax.plot(x, y, color=colormap[num])

Value of n is depended on how many data point (lines) going to plot

Create a twin Axes sharing the xaxis. (Double y axis is created)

axes.twinx()

Legend change the sequence/ customize labels

c = c1 + c2 
labs = [cc.get_label() for cc in c] 
ax.legend(c, labs, loc='upper left', fontsize=14, ncol=3)

Or

handles, labels = plt.gca().get_legend_handles_labels() 
plt.legend([handles[i] for i in order], [labels[i] for i in order])

Vertical line

ax.vlines()

Y axis on right side

ax.yaxis.tick_right() 
ax.yaxis.set_label_position('right')

Texts under x ax (ticks)

ax.set_xticklabels()

Location of the short lines of x ax (ticks)

ax.set_xticks([])

Color of frame

  • ax.spines['bottom'].set_color('#dddddd')
  • ax.spines['top'].set_color('#dddddd')
  • ax.spines['right'].set_color('red')
  • ax.spines['left'].set_color('red')
  • ax.spines['left'].set_color('none')

Color of ticks

ax.xaxis.label.set_color('red') 
ax.tick_params(axis='x', colors='red')

Font setting

font = FontProperties(fname="YaHei.ttf", size=12) 
ax.plot(x, y, label="Chinese") 
ax.legend(prop=font) 
for index_ele,ele in enumerate(ax.get_yticklabels()): 
  ele.set_fontproperties(font) 
ax.set_title("Chinese", fontsize=18, fontproperties=font)

First line of the script above is inserted automatically when initialization py file

The “size” parameter only influence to the font size of legend

Subplots tight

fig.tight_layout()
fig.subplots_adjust(wspace=0, hspace=0.4)

Inset plot

axinset = ax.inset_axes([0.35,0.15,0.3,0.5],xlim=(-8.7,-7.8),ylim=(0.94,0.99)) 
ax.indicate_inset_zoom(axinset, edgecolor="black")

Rectangle

import matplotlib.patches as patches 
rec=Patches.Rectangle(xy, width, height, angle=0.0,linewidth=1, edgecolor='r', facecolor='none') 
ax.add_patch(rec)

Transparent background

plt.savefig('demo.png', transparent=True,bbox_inches='tight')

Remove scientific notation

ax.ticklabel_format(style='plain')

Scientific notation fontsize

ax.yaxis.offsetText.set_fontsize(24)

Chinese characters displaying

From matplotlib.font_manager import FontProperties
font = FontProperties(fname="XXX.ttf", size=12) # .ttf is located under same folder with .py
# size=12 only influence ax.legend
ax.plot(x, y, label="Chinese")
ax.legend(prop=font)
ax.set_title("Chinese", fontsize=18, fontproperties=font)

OS

input file

input_file = ''
work_dir = input_file[:len(input_file)-input_file[::-1].index('/')]
input_file = input_file[len(input_file)-input_file[::-1].index('/'):]
os.chdir(work_dir)

Change directory

os.chdir('path')

  • For Windows, path should be like 'C:\\User\\Desktop\\Temp'
  • For Linux, path should be like '/home/yongnali08/Desktop/Temp'

Get current work directory

os.getcwd()

List directory

os.listdir()

Split file name into name part and extension part

os.path.splitext(filename)

Example: filename.py

Return of os.path.splitext('filename.py') is ‘filename’ and ‘.py’

Rename file

os.rename(original name, new name)

NetCDF4

Extract Data from .nc

from netCDF4 import Dataset

nc = Dataset("nc_file_name.nc") 
nc.variables['variable_name'] # output of this terms is an array

Plotly

Plot

import plotly.graph_objects as go 
figgo = go.Figure()
figgo.add_trace(go.Scatter(x=x,y=y,name=name,line=dict(color='#000000',width=4),opacity=0.5,mode='markers'))
figgo.add_trace(go.Scatter(x=x2,y=y2,name=name2,line=dict(color='#AAAAAA',width=6),mode='lines'))) 
figgo.add_trace(go.Scatter(x=x,y=y,line_color="#454545")) 
fig.show()

Subplot

import plotly.graph_objects as go 
from plotly.subplots import make_subplots 
figgo = go.Figure() 
figgo=make_subplots(rows=1,cols=1,shared_xaxes=True,vertical_spacing=0.02,insets=[dict(cell=(1,1),w=0.3,l=0.35,h=0.5,b=0.15)])

Interactive plot in one line (for interactive window)

import plotly.graph_objects as go 
go.Figure().add_trace(go.Scatter(x=x,y=y,name=name,line=dict(color='#000000',width=4))).add_trace(go.Scatter(x=x2,y=y2,name=name2,line=dict(color='#AAAAAA',width=6))).show()

Check data, remove line

figgo.data

Fill between

go.Scatter(x=x,y=y1,fill='tonexty') 
go.Scatter(x=x,y=y2)

Fill area between y2 and y1 (y2>y1)

go.Scatter(x=x,y=y,fill='tozeroy')

Fill area between y and x axis (y=0)

Layout

figgo.update_layout(title=title, xaxis_title=xaxis, yaxis_title=yaxis, legend_title=legend)
figgo.update_layout(legend=dict(y=0.99,x=0.01),xaxis=dict(range=[-10.1,-9.9]),yaxis=dict(range=[0.43,0.52]))
figgo.update_xaxes(type='log') 
figgo.add_trace(go.Scatter(x,y,showlegend=False))

subplot layout update

figgo.update_layout(xaxis2=dict(range=[-10.1,-9.9]),yaxis2=dict(range=[0.43,0.52]))

xaxis2 yaxis2 for subplot