env_test.py

#!/usr/bin/env python

# Run this script with: `python env_test.py`

import numpy as np # library for array operations
import matplotlib.pyplot as plt # library for plotting
from mpl_toolkits.basemap import Basemap # library for maps
#import cartopy.crs as ccrs # alternative library for maps


# 'Arrays' of objects
list_int = [1,2,3] # list
list_str = ['a','b','c'] # list
tupl_int = (4,5,6) # tuple

# One can change a list item (by index)
list_int[1] = 100.

# TODO Try changing a tuple value. What happens?
# ...

# TODO Try multiplying a list by 2. What happens?
# ...


# Define two arrays (range of values, or with list)
x = np.array([0.,1.,2.,3.,4.,5.,6.,7.,8.,9.])
y = np.arange(10,dtype='f') # specify type here
y *= 2. # multiply by 2


# Example of a for loop (note *indentation*)
for idx in range(len(x)):
    # Use a numpy built-in function
    y[idx] = np.sin(x[idx])**2


# Define boolean switch for plot (if True, plot is shown)
do_plot = False

# Check condition (again, note *indentation*)
if do_plot is True:  
    # Create a figure object
    plt.figure()
    # Do a line plot; if field is 2D, then contour is used
    plt.plot(x,y,color='black')
    plt.show()
 

# An example of function, with a block 
# description at the beginning
def myfunction(myvalue):
    """ Define a function with this 
    structure, as an indented block. 
    The strings in the () are the function 
    input parameters. 
    Make some calculation, then return 
    some output (it might be None) """
    myoutput = myvalue**2 # square
    return myoutput 

# Simply call any function with its name, 
# output(s) = function name (parameter1,...parameterN)
squared_value = myfunction(100)
print(squared_value)