In [18]:
#Fig 2.3
x = np.linspace(1,8,7)
tmax = [77,72,75,73,66,64,59]
plt.plot(x, tmax, "o")
plt.grid()
This Version 3.0 is authored by Briana Ramirez, edited by Samuel Shen. Liu Yang, Sandra Villamar, and Joaquin Stawsky contributed codes to this version.
Video tutorial for the python code can be found at the following URL: https://www.youtube.com/channel/UC7D9i0kBMzPTHyEhU0h6W9g
This version is based upon the previous version described in the following box.
######################################################################################################################
#This Python Code for Climate Science is written for the book entitled "Climate Mathematics: Theory and Applications"#
#A Cambridge University Press book authored by SSP Shen and RCJ Somerville in July 2019 #
#The Python codes were based on the R codes written by Samuel Shen Distinguished Professor, #
#San Diego State University, USA and were translated from R by Louis Selstad, Stephen Shen, #
#Gregori Clarke, and Dakota Newmann and edited by Samuel Shen. #
######################################################################################################################
#FIRST TIME Python users*****
#These package need to be installed (on the terminal or anaconda interface) before importing them below.
#Follow this tutorial for package installation before
# https://towardsdatascience.com/importerror-no-module-named-xyz-45e4a5339e1b
#Change your file path to the folder where your downloaded data is stored
#MAC HELP: https://support.apple.com/guide/mac-help/go-directly-to-a-specific-folder-on-mac-mchlp1236/mac
#PC HELP: https://www.sony.com/electronics/support/articles/00015251
import os
# os.chdir("/Users/sshen/climmath/data")
os.chdir('/Users/HP/Documents/sshen/climmath/data')
%%javascript
IPython.OutputArea.prototype._should_scroll = function(lines) {
return false;
}
#Style Dictionary to standardize plotting scheme between different python scripts
import matplotlib.pyplot as plt
styledict = {'xtick.labelsize':20,
'xtick.major.size':9,
'xtick.major.width':1,
'ytick.labelsize':20,
'ytick.major.size':9,
'ytick.major.width':1,
'legend.framealpha':0.0,
'legend.fontsize':15,
'axes.labelsize':20,
'axes.titlesize':25,
'axes.linewidth':2,
'figure.figsize':(12,8),
'savefig.format':'jpg'}
plt.rcParams.update(**styledict)
#Function that creates personalized discrete Colormap
import numpy as np
from matplotlib import cm as cm1
from matplotlib.colors import ListedColormap, to_rgba
def newColMap(colors):
"""
This function creates a new color map from a list of colors given
as a parameter. Recommended length of list of colors is at least 6.
"""
first = np.repeat([to_rgba(colors[0])], 2, axis = 0)
last = np.repeat([to_rgba(colors[-1])], 2, axis = 0)
v = cm1.get_cmap('viridis', 16*(len(colors)-2))
newcolors = v(np.linspace(0, 1, 16*(len(colors)-2)))
for (i, col) in enumerate(colors[1:-1]):
newcolors[16*i : 16*(i+1), :] = to_rgba(col)
return ListedColormap(np.append(np.append(first,newcolors, axis=0), last, axis=0))
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.colors import rgb2hex
from matplotlib.patches import Polygon
import matplotlib.mlab as mlab
import pandas as pd
from cartopy import crs, mpl
import matplotlib.ticker as mticker
from cartopy.mpl.gridliner import LONGITUDE_FORMATTER, LATITUDE_FORMATTER
from mpl_toolkits.basemap import Basemap
# Having an issue with the import “mpl_toolkits.basemap” package?
# Unlike other package installations, this package requires additional steps to install.
# 1.Download basemap package from this website
# https://www.lfd.uci.edu/~gohlke/pythonlibs/#basemap
# *Note the package version needs to be the same as Python version
# 2.Run the following line in your terminal
# pip install basemap-1.2.2-cp37-cp37m-win_amd64.whl
from mpl_toolkits import mplot3d
import netCDF4
from netCDF4 import Dataset as ds
from urllib import request
import scipy as sp
from scipy import stats as stt
from sklearn import datasets, linear_model
from sklearn.neighbors import KernelDensity as kd
from sklearn.linear_model import LinearRegression
from random import randint
from scipy.stats import norm
import statsmodels
import sklearn
import math
import statistics
import sympy as sy
from sympy import symbols, diff
import statsmodels.api as sm
from datetime import date
Python As a Smart Calculator
# Basic arithmetic
1+4
5
# Basic arithmetic
2 + np.pi/4 - 0.8
1.9853981633974482
# Variable Assignment
x = -1
y = 2
z = 4
# x**y means x^y: x to the power of y
t = 2*x**y-z
t
-2
# Variable Assignment
u = 2
v = 3
u+v
5
# np.sin is the sine function in Python
np.sin(u*v)
-0.27941549819892586
Define a Sequence in Python
# Enter the temperature data
tmax = [77,72,75,73,66,64,59]
# Show the temperature data
tmax
[77, 72, 75, 73, 66, 64, 59]
# A Python sequence starts from 0 while R starts from 1
np.arange(9)
# A sequence is called an array in Python
array([0, 1, 2, 3, 4, 5, 6, 7, 8])
# np.arange(x,y) creates an array of numbers incremented by 1 between integer x and integer (y-1)
np.arange(1, 9)
array([1, 2, 3, 4, 5, 6, 7, 8])
# np.arange(x,y) can take negative and real numbers with a default increment of 1
np.arange(-5.5, 2)
array([-5.5, -4.5, -3.5, -2.5, -1.5, -0.5, 0.5, 1.5])
Define a Function in Python
# Define the x^2 function and call it samfctn(x)
def samfctn(x):
return x * x
samfctn(4)
16
#Fig 2.3
x = np.linspace(1,8,7)
tmax = [77,72,75,73,66,64,59]
plt.plot(x, tmax, "o")
plt.grid()
# Define a multivariate function "x+y-z/2"
def fctn2(x, y, z):
return x + y - z / 2;
fctn2(1, 2, 3)
1.5
Plot with Python
Plot the curve of y = sin(x) from -pi to 2*pi
# math.pi is the same as np.pi and scipy.pi, just using different packages
t = np.arange(-math.pi, 2*math.pi, 0.1)
plt.plot(t, np.sin(t), "o")
plt.grid()
plt.show()
Plot x-y data based on a formula
# Uniform division using 20 points
t = np.linspace(-3, 2, 20)
plt.plot(t, t ** 2)
plt.grid()
plt.show()
Plot 3D Surface
x = np.linspace(-1, 1, 100)
y = np.linspace(-1, 1, 100)
# Defines a formula for Z
def f(x, y):
return 1 - x**2 - y**2
X, Y = np.meshgrid(x, y)
# Renders z function on the x, y grid
Z = f(X, Y)
# Creates the 3D plot
fig = plt.figure()
ax = plt.axes(projection = '3d')
ax.contour3D(X, Y, Z, 30, cmap = 'binary')
plt.show()
Contour Plot
#Fig 2.4
x = np.linspace(-1, 1, 30)
y = np.linspace(-1, 1, 30)
X, Y = np.meshgrid(x, y)
Z = f(X, Y)
# Creates and colors the contour plot
plt.contourf(X, Y, Z, 20, cmap = 'cool') #cmap='color-scheme'
# Adds colorbar for color map of contours
plt.colorbar()
plt.show()
Plot 3D Contour Plot
x = np.linspace(-1, 1, 100)
y = np.linspace(-1, 1, 100)
# Defines a formula for Z
def f(x, y):
return 1 - x**2 - y**2
X, Y = np.meshgrid(x, y)
# Renders z function on the x, y grid
Z = f(X, Y)
# Creates the 3D plot
fig = plt.figure()
ax = plt.axes(projection = '3d')
ax.plot_surface(X, Y, Z, rstride=1, cstride=1,
cmap='viridis', edgecolor='none') #cmap = 'color'
# Labels the plot
ax.set_title('Contour surface')
ax.set_xlabel('x', labelpad=15)
plt.xticks(fontsize=14)
ax.set_ylabel('y', labelpad=15)
plt.yticks(fontsize=14)
ax.set_zlabel('z', labelpad=15)
ax.set_zticklabels([-1,-.75,-.5,-.25,0,.25,.5,.75,1],Fontsize=14)
ax.view_init(30)
plt.show()
<ipython-input-24-723a2fbd47ff>:26: UserWarning: FixedFormatter should only be used together with FixedLocator ax.set_zticklabels([-1,-.75,-.5,-.25,0,.25,.5,.75,1],Fontsize=14) <ipython-input-24-723a2fbd47ff>:26: MatplotlibDeprecationWarning: Case-insensitive properties were deprecated in 3.3 and support will be removed two minor releases later ax.set_zticklabels([-1,-.75,-.5,-.25,0,.25,.5,.75,1],Fontsize=14)