import numpy as np

import urllib    # for reading information from a URL

import matplotlib.pyplot as plt
import matplotlib.image as mpimg

%matplotlib notebook

Download the file test1.dat from PHYS 310 website. Here's what's in the file:

# This line is a comment
#
#t x y
# ============
1.2 2.3 3.2
2.2 4.6 6.1
3.0 5.9 9.1

The file is in the format of a typical data file. Each line might be something like $(t,x,y)$.

Note that by default loadtxt ignores any lines in the data file that begin with the # character. (This can be changed.)

a = np.loadtxt("test1.dat")
a

array([[1.2, 2.3, 3.2],
       [2.1, 4.6, 6.1],
       [3. , 5.9, 9.1]])

It's often useful to break the data into single arrays for $t$, $x$, and $y$. One way to do this is with the transpose of a:

a.T

array([[1.2, 2.1, 3. ],
       [2.3, 4.6, 5.9],
       [3.2, 6.1, 9.1]])

t, x, y = a.T

t

array([1.2, 2.1, 3. ])

or loadtxt can get the columns of the data file directly:u

t, x, y = np.loadtxt("test1.dat", unpack=True)

Here's a copy of test2.csv

# This line is a comment
#
#t x y
# ============
, 1, 2, 3
comment in column 0, 2, 4, 6
, 3, 9, 27

b = np.loadtxt("test2.csv", delimiter = ',', usecols = (1,2,3), unpack = True)
b

array([[ 1.,  2.,  3.],
       [ 2.,  4.,  9.],
       [ 3.,  6., 27.]])

c = 2*a
c

array([[ 2.4,  4.6,  6.4],
       [ 4.2,  9.2, 12.2],
       [ 6. , 11.8, 18.2]])

np.savetxt('testout1.dat', c, header='sample header (optional)' )

Retrieve a data file from a URL¶

np.loadtxt() has now been upgraded to read directly from a URL:

link = 'http://www.eg.bucknell.edu/~phys310/jupyter/test1.dat'
f = urllib.request.urlopen(link)
data = np.loadtxt(f)
print(data)

[[1.2 2.3 3.2]
 [2.1 4.6 6.1]
 [3.  5.9 9.1]]

Retrieve and display a JPG image¶

urllib.request.urlretrieve(' http://www.atlasoftheuniverse.com/nebulae/m42.jpg','orion.jpg')

('orion.jpg', <http.client.HTTPMessage at 0x7f5530742490>)

img = mpimg.imread('orion.jpg')

plt.figure()
plt.imshow(img);

version_information is from J.R. Johansson (jrjohansson at gmail.com); see Introduction to scientific computing with Python for more information and instructions for package installation.

version_information is installed on the linux network at Bucknell

%load_ext version_information

%version_information numpy, matplotlib