Related
I'm writing an algorithm that rotates a square matrix 90º degrees in-place, without using a second matrix. It works, but I've got one small problem that is troubling me.
So the basic, working algorithm is:
def rotate(matrix):
n = len(matrix)
# reverse rows
matrix.reverse()
# reflect
start = 0
for row in range(n):
for col in range(start, n):
matrix[row][col], matrix[col][row] = matrix[col][row], matrix[row][col]
start = start + 1
The idea is to pass a matrix defined as a list of lists, like [[1, 2, 3], [4, 5, 6], [7, 8, 9]].
Example input/output:
>>> some_matrix = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
>>> rotate(some_matrix)
>>> print(some_matrix)
[[7, 4, 1], [8, 5, 2], [9, 6, 3]]
Great. So, I was wondering if I could replace matrix.reverse() with something maybe a little more intuitive, like simply using slice indexing. So I wrote a new rotate, like this:
def rotate2(matrix):
n = len(matrix)
# reverse rows
matrix = matrix[::-1]
# reflect
start = 0
for row in range(n):
for col in range(start, n):
matrix[row][col], matrix[col][row] = matrix[col][row], matrix[row][col]
start = start + 1
Which SHOULD give me the same results, based on:
>>> a = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
>>> b = a
>>> b = b[::-1]
>>> a.reverse()
>>> print(a)
[[7, 8, 9], [4, 5, 6], [1, 2, 3]]
>>> print(b)
[[7, 8, 9], [4, 5, 6], [1, 2, 3]]
>>> print(a==b)
True
However, when I use rotate2 on the same input/output example, I get:
>>> some_matrix = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
>>> rotate2(some_matrix)
>>> print(some_matrix)
[[9, 6, 3], [8, 5, 2], [7, 4, 1]]
So what am I missing here?
matrix = matrix[::-1] creates a new list and assigns it to the local name matrix; it does not modify the original list in-place.
matrix.reverse(), on the other hand, does modify the original list.
Consider these simple functions:
def r1(m):
m = m[::-1]
def r2(m):
m.reverse()
>>> x = [[1,2], [3,4]]
>>> r1()
>>> x
[[1,2], [3,4]]
>>> r2()
>>> x
[[3,4],[1,2]]
I have a nested list like this which:
list = [[1,2,3], [2,5,7,6], [1,-1], [5,7], [6,3,7,4,3], [2, 5, 1, -5]]
What I am trying to do is to remove nested lists, where the value within these lists are both positive and negative. I have tried doing it by list comprehension, but I couldn't figure it out.
def method(list):
return [obj for obj in list if (x for x in obj if -x not in obj)]
The obtained results should be like:
list = [[1,2,3], [2,5,7,6], [5,7], [6,3,7,4,3]]
Assuming you want lists where elements are either all negative or all positive you can use all predefined function to check for both possibilities
result = [L for L in x if all(y>0 for y in L) or all(y<0 for y in L)]
EDIT:
In the comments you clarified what is a valid list (e.g. [-1, 2] is valid)... with this new formulation the test should be
result = [L for L in x if all(-y not in L for y in L)]
where each single test is however now quadratic in the size of the list. Using set this problem can be removed
result = [L for L in x if all(-y not in S for S in (set(L),) for y in L)]
Using list comprehension you can do something like:
def method2(list):
return [obj for obj in list if (all(n>0 for n in obj) or all(n<0 for n in obj))]
that, with your example, give as output:
[[1, 2, 3], [2, 5, 7, 6], [5, 7], [6, 3, 7, 4, 3]]
In general is better to split the task by steps:
Given list find the positives (positives function)
Given list find the negatives and multiply them by -1 (negatives function)
If the intersection of both positives and negatives is not empty remove.
So, you could do:
def positives(ls):
return set(l for l in ls if l > 0)
def negatives(ls):
return set(-1*l for l in ls if l < 0)
list = [[1, 2, 3], [2, 5, 7, 6], [1, -1], [5, 7], [6, 3, 7, 4, 3], [2, 5, 1, -5]]
result = [l for l in list if not negatives(l) & positives(l)]
print(result)
Output
[[1, 2, 3], [2, 5, 7, 6], [5, 7], [6, 3, 7, 4, 3]]
As a side note you should not use list as a variable name as it shadows the built-int list function.
Your generator should yield whether the condition to filter an object applies.
You then feed the generator to an aggregator to determine if obj should be filtered.
the aggregator could be any or all, or something different.
# assuming obj should be filtered if both x and the inverse of x are in obj
def method_with_all(src):
return [obj for obj in src if all(-x not in obj for x in obj)]
def method_with_any(src):
return [obj for obj in src if any(-x in obj for x in obj)]
you can filter out the lists that have both negative and positive elements:
def keep_list(nested_list):
is_first_positive = nested_list[0] > 0
for element in nested_list[1:]:
if (element > 0) != is_first_positive:
return False
return True
my_list = [[1,2,3], [2,5,7,6], [1,-1], [5,7], [6,3,7,4,3], [2, 5, 1, -5]]
print(list(filter(keep_list, my_list)))
output:
[[1, 2, 3], [2, 5, 7, 6], [5, 7], [6, 3, 7, 4, 3]]
Numpy can be used as well. My solution here is similar to the "all"-operation suggested by others but coded explicitly and only needs one condition. It checks whether the sign of the all the elements equals the sign of the first element (could be any other as well).
from numpy import *
def f(b):
return [a for a in b if sum(sign(array(a)) == sign(a[0])) == len(a)]
For your case...
data = [[1,2,3], [2,5,7,6], [1,-1], [5,7], [6,3,7,4,3], [2, 5, 1, -5]]
print(f(data))
...it will return:
[[1, 2, 3], [2, 5, 7, 6], [5, 7], [6, 3, 7, 4, 3]]
I would like a list to be stored into another list from right to left diagonally without importing anything if possible
eg. list =
[[1, 4, 6]
[6, 3, 7]
[2, 7, 9]]
say I'd like to store [6, 3, 2] into another list, how would i go about doing it? I have tried many ways for hours and still cant find a solution
With a list comprehension:
l =[[1, 4, 6],
[6, 3, 7],
[2, 7, 9]]
diagonal = [row[-i] for i, row in enumerate(l, start=1)]
print(diagonal)
Output
[6, 3, 2]
The following snipped
l =[[1, 4, 6],
[6, 3, 7],
[2, 7, 9]]
d = len(l)
a = []
for i in range(0,d):
a.append(l[i][d-1-i])
print(a)
results in the output you expected:
[6, 3, 2]
You can use a list comprehension and use list indexing twice to select your row and column:
L = [[1, 4, 6],
[6, 3, 7],
[2, 7, 9]]
n = len(L)
res = [L[i][n-i-1] for i in range(n)]
# [6, 3, 2]
An alternative formulation is to use enumerate as per #OlivierMelançon's solution.
If you can use a 3rd party library, you can use NumPy to extract the diagonal of a flipped array:
import numpy as np
arr = np.array(L)
res = np.diag(np.fliplr(arr))
# array([6, 3, 2])
When you want to create a list out from another list, list comprehension is a very good way to go.
a = yourlist
print([a[i][(i+1)*-1] for i in range(len(a))])
This list comprehension loops through the lists taking the the furthes back integer and the second furthes back and so on.
Using numpy and rotate (90)
import numpy as np
list = [[1, 4, 6],[6, 3, 7],[2, 7, 9]]
np.diag(np.rot90(array))
Output :
array([6, 3, 2])
or without using numpy:
list = [[1, 4, 6],[6, 3, 7],[2, 7, 9]]
res=[]
i=-1
for elm in list :
res.append(elm[i])
i-=1
print res
#[6, 3, 2]
I'm very new to python (using python3) and I'm trying to add numbers from one list to another list. The only problem is that the second list is a list of lists. For example:
[[1, 2, 3], [4, 5, 6]]
What I want is to, say, add 1 to each item in the first list and 2 to each item in the second, returning something like this:
[[2, 3, 4], [6, 7, 8]]
I tried this:
original_lst = [[1, 2, 3], [4, 5, 6]]
trasposition_lst = [1, 2]
new_lst = [x+y for x,y in zip(original_lst, transposition_ls)]
print(new_lst)
When I do this, I get an error
can only concatenate list (not "int") to list
This leads me to believe that I can't operate in this way on the lists as long as they are nested within another list. I want to do this operation without flattening the nested list. Is there a solution?
One approach using enumerate
Demo:
l = [[1, 2, 3], [4, 5, 6]]
print( [[j+i for j in v] for i,v in enumerate(l, 1)] )
Output:
[[2, 3, 4], [6, 7, 8]]
You can use enumerate:
l = [[1, 2, 3], [4, 5, 6]]
new_l = [[c+i for c in a] for i, a in enumerate(l, 1)]
Output:
[[2, 3, 4], [6, 7, 8]]
Why don't use numpy instead?
import numpy as np
mat = np.array([[1, 2, 3], [4, 5, 6]])
mul = np.array([1,2])
m = np.ones(mat.shape)
res = (m.T *mul).T + mat
You were very close with you original method. Just fell one step short.
Small addition
original_lst = [[1, 2, 3], [4, 5, 6]]
transposition_lst = [1, 2]
new_lst = [[xx + y for xx in x] for x, y in zip(original_lst, transposition_lst)]
print(new_lst)
Output
[[2, 3, 4], [6, 7, 8]]
Reasoning
If you print your original zip it is easy to see the issue. Your original zip yielded this:
In:
original_lst = [[1, 2, 3], [4, 5, 6]]
transposition_lst = [1, 2]
for x,y in zip(original_lst, transposition_lst):
print(x, y)
Output
[1, 2, 3] 1
[4, 5, 6] 2
Now it is easy to see that you are trying to add an integer to a list (hence the error). Which python doesn't understand. if they were both integers it would add them or if they were both lists it would combine them.
To fix this you need to do one extra step with your code to add the integer to each value in the list. Hence the addition of the extra list comprehension in the solution above.
A different approach than numpy that could work even for lists of different lengths is
lst = [[1, 2, 3], [4, 5, 6, 7]]
c = [1, 2]
res = [[l + c[i] for l in lst[i]] for i in range(len(c))]
I have a problem with "pairing" arrays into one (by index). Here is an example:
INPUT:
inputArray = [[0, 1, 2, 3, 4], [2, 3, 5, 7, 8], [9, 6, 1]]
EXPECTED OUTPUT:
outputArray =
[[0,2,9],
[1,3,6],
[2,5,1],
[3,7,chooseRandom()],
[4,8,chooseRandom()]]
Questions:
How to avoid "out of range" "index error" problem
How to write chooseRandom() to choose N neighbour
Answers:
[SOLVED] Solutions provided by #jonrsharpe & #Christian & #Decency works as
expected
Clarification:
By N neighbour I mean:
I'm using python but feel free to share your thoughts in any language.
I think the following will do what you want:
from itertools import izip_longest # 'zip_longest' in Python 3.x
from random import choice
# Step 1
outputArray = list(map(list, izip_longest(*inputArray)))
# Step 2
for index, arr in enumerate(outputArray):
if any(item is None for item in arr):
valid = [item for item in arr if item is not None]
outputArray[index] = [choice(valid) if item is None else item
for item in arr]
This has two steps:
Combine all sub-lists of inputArray to the length of the longest sub-array, filling with None: [[0, 2, 9], [1, 3, 6], [2, 5, 1], [3, 7, None], [4, 8, None]]; and
Work through the outputArray, finding any sub-lists that contain None and replacing the None with a random choice from the other items in the sub-list that aren't None.
Example output:
[[0, 2, 9], [1, 3, 6], [2, 5, 1], [3, 7, 3], [4, 8, 8]]
Here's my approach to the problem, in Python 3.4. I don't really know what you mean by "choose N neighbour" but it should be pretty easy to write that however you'd like in the context below.
inputArray = [[0, 1, 2, 3, 4], [2, 3, 5, 7, 8], [9, 6, 1]]
import itertools
zipped = itertools.zip_longest(*inputArray, fillvalue=None)
outputArray = [list(item) for item in zipped]
# [[0, 2, 9], [1, 3, 6], [2, 5, 1], [3, 7, None], [4, 8, None]]
# Now replace the sentinel None in our sublists
for sublist in outputArray:
for i, element in enumerate(sublist):
if element is None:
sublist[i] = chooseRandom()
print(outputArray)
Not the most pythonic way, but you could try using this code snipped, read the comments in the code below:
import itertools, random
inputArray = [ [0, 1, 2, 3, 4], [2, 3, 5, 7, 8], [9, 6, 1] ]
outputArray = []
max_length = max(len(e) for e in inputArray) # maximum length of the sublists in <inputArray>
i = 0 # to keep the index of sublists of <outputArray>
for j in range(max_length):
outputArray.append([]) # add new sublist
for e in inputArray: # iterate through each element of <inputArray>
try:
outputArray[i].append(e[j]) # try to append the number, if an exception is raised
# then the code in the <except> clause will be executed
except IndexError as e:
outputArray[i].append(random.randint(0, 10)) # add the random number
i += 1 # increase the sublists index on each iteration
print outputArray
# [[0, 2, 9], [1, 3, 6], [2, 5, 1], [3, 7, 3], [4, 8, 7]]
Note:
You may want to change the part
random.randint(0, 10)
to get the "N neighbour".
Let me know whether you like this code:
import random
array = [[0, 1, 2, 3, 4], [2, 3, 5, 7, 8], [9, 6, 1]]
max_len = max([len(l) for l in array])
dictionary = {}
for l in array:
for i in range(0,len(l)):
if dictionary.has_key(i):
dictionary[i].append(l[i])
else:
dictionary[i] = [l[i]]
for i in range(len(l),max_len):
if dictionary.has_key(i):
dictionary[i].append(random.choice(l))
else:
dictionary[i] = [random.choice(l)]
print dictionary.values()