NumPy & SciPy Flashcards
create three-dimensional array of floats
import numpy
x = y = z = 5
zeros((x, y, z), np.float)
get array/matrix dimensions
a.shape
get array/matrix datatype
a.dtype
given an array a, make a new array of same dimension and data type
x = zeros(a.shape, a.dtype)
create a list of uniformly spaced coordinates
linspace(start, end, steps)
construct array from list
array(list)
construct 2D-array from two lists
array([x, y])
from array to list
a.tolist()
convert to array
asarray(list)
change array dimensions
a.shape = (3, 2) a = a.reshape(3, 2)
get number of elements in array
a.size
set a[2] and a[3] equal to 5
a[2:4] = 5
set last element equal to first
a[-1] = a[0]
set all elements of array equal to 0
a[:] = 0
a[:, :] = 0
a.fill(0)
print column k
print a[:, k]
print row l
print a[l, :]
a[:, ::2]
returns first and even indexed elements in all rows
a[:, 2::2]
returns even indexed elements in all rows
list[:] is a … of the data
array[:] is a … of the data
copy
reference
copy array
b = a.copy()
loop over 2D-array
for y in xrange(a.shape[0]):
for x in xrange(a.shape[1]):
print a[y, x]
perform 2x + 1 on every element in a
a = 2*a + 1 # this is much faster than element-wise operations
power function
x**2
exponential function
exp(a)
square root function
sqrt(a)
get mean, variance and standard deviation of array a
a. mean(), mean(a)
a. var(), var(a)
a. std(), std(a)
covariance
cov(x, y)
change type of array/matrix
a.astype(int)
module for curve plotting
matplotlib
