Briefly:
np.dot
is the dot product of two matrices.
|A B| . |E F| = |A*E+B*G A*F+B*H|
|C D| |G H| |C*E+D*G C*F+D*H|
Whereas np.multiply
does an element-wise multiplication of two matrices.
Briefly:
np.dot
is the dot product of two matrices.
|A B| . |E F| = |A*E+B*G A*F+B*H|
|C D| |G H| |C*E+D*G C*F+D*H|
Whereas np.multiply
does an element-wise multiplication of two matrices.
map
and filter
function in python is pretty different because they perform very differently. Let's have a quick example to differentiate them.
map function
Let's define a function which will take a string argument and check whether it presents in vowel letter sequences.
def lit(word):
return word in 'aeiou'
Now let's create a map function for this and pass some random string.
For left alignment
<img align="left" width="600" height="200" src="https://www.python.org/python-.png">
For right alignment
<img align="right" width="600" height="200" src="https://www.python.org/python-.png">
And for center alignment
We can delete a key from a Python dictionary by the some following approaches.
Using the del
keyword; it's almost the same approach like you did though -
myDict = {'one': 100, 'two': 200, 'three': 300 }
print(myDict) # {'one': 100, 'two': 200, 'three': 300}
if myDict.get('one') : del myDict['one']
print(myDict) # {'two': 200, 'three': 300}
NumPy 1.7 (when np.pad
was added) is pretty old now (it was released in 2013) so even though the question asked for a way without that function I thought it could be useful to know how that could be achieved using np.pad
.
It's actually pretty simple:
>>> import numpy as np
>>> a = np.array([[ 1., 1., 1., 1., 1.],
... [ 1., 1., 1., 1., 1.],
... [ 1., 1., 1., 1., 1.]])
>>> np.pad(a, [(0, 1), (0, 1)], mode='constant')
array([[ 1., 1., 1., 1., 1., 0.],
Set-up Raspberry Pi headlessly in Laptop, no HDMI no Monitor.
Some GitHub Extensions that I use. They may also enable you to improve your productivity on GitHub.
2 github-dashboard provides the ability to filter events on the Github.com activity dashboard.