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I use Maxima CAS to create the list:
a:makelist(i,i,1,20);
result:
[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20]
I want to slim the list and leave only every third element. To find it I check index i of the list a :
mod(i,3)>0
to find elements.
My code :
l:length(a);
for i:1 thru l step 1 do if (mod(i,3)>0) then a:delete(a[i],a);
Of course it does not work because length of a is changing.
I can do it using second list:
b:[];
for i:1 thru l step 1 do if (mod(i,3)=0) then b:cons(a[i],b);
Is it the best method ?
There are different ways to solve this, as know already. My advice is to construct a list of the indices you want to keep, and then construct the list of elements from that. E.g.:
(%i1) a:makelist(i,i,1,20);
(%o1) [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20]
(%i2) ii : sublist (a, lambda ([a1], mod(a1, 3) = 0));
(%o2) [3, 6, 9, 12, 15, 18]
(%i3) makelist (a[i], i, ii);
(%o3) [3, 6, 9, 12, 15, 18]
The key part is the last step, makelist(a[i], i, ii), where ii is the list of indices you want to select. ii might be constructed in various ways. Here is a different way to construct the list of indices:
(%i4) ii : makelist (3*i, i, 1, 6);
(%o4) [3, 6, 9, 12, 15, 18]
One simple way (I do not know which one is best or faster) with compact code: makelist(a[3*i],i,1,length(a)/3)
Test example:
l1:makelist(i,i,1,12)$
l2:makelist(i,i,1,14)$
l3:[2,3,5,7,11,13,17,19,23,29]$
for a in [l1,l2,l3] do (
b:makelist(a[3*i],i,1,length(a)/3),
print(a,"=>",b)
)$
Result:
[1,2,3,4,5,6,7,8,9,10,11,12] => [3,6,9,12]
[1,2,3,4,5,6,7,8,9,10,11,12,13,14] => [3,6,9,12]
[2,3,5,7,11,13,17,19,23,29] => [5,13,23]
I have a ndarray like this one:
number_of_rows = 3
number_of_columns = 3
a = np.arange(number_of_rows*number_of_columns).reshape(number_of_rows,number_of_columns)
a
array([[0, 1, 2],
[3, 4, 5],
[6, 7, 8]])
But I want something like this:
array([[0, 100, 101],
[3, 102, 103],
[6, 7, 8]])
To do that I want to avoid to do it one by one, I rather prefer to do it in arrays or matrices, because later I want to extend the code.
Nothe I have change a submatrix of the initial matrix (in mathematical terms, in terms of this example ndarray). In the example the columns considered are [1,2] and the rows [0,1].
columns_to_keep = [1,2]
rows_to_keep = [0,1]
My first try was to do:
a[rows_to_keep,:][:,columns_to_keep] = np.asarray([[100,101],[102,103]])
However this doesn't modify the initial a, I am not having any error, so a=
array([[0, 1, 2],
[3, 4, 5],
[6, 7, 8]])
So I have implemented a piece of code that goes do the job:
b = [[100, 101],[102, 103]]
for i in range(len(rows_to_keep)):
a[i,columns_to_keep] = b[i]
Al thought the previous lines do the job I am wondering how to do it slicing and in a faster fashion. Also in a way that with:
columns_to_keep = [0,2]
rows_to_keep = [0,2]
the desired output is
array([[100, 1, 101],
[3, 4, 5],
[102, 7, 103]]).
Many thanks!
Indexing with lists like [1,2] is called advanced indexing. By itself it produces a copy, not a view. You have to use one indexing expression, not two to assign or change values. That is a[[1,2],:] is a copy, a[[1,2],:][:,[1,2]] += 100 modifies that copy, not the original a.
In [68]: arr = np.arange(12).reshape(3,4)
Indexing with slices; this is basic indexing:
In [69]: arr[1:,2:]
Out[69]:
array([[ 6, 7],
[10, 11]])
In [70]: arr[1:,2:] += 100
In [71]: arr
Out[71]:
array([[ 0, 1, 2, 3],
[ 4, 5, 106, 107],
[ 8, 9, 110, 111]])
Doing the same indexing with lists requires arrays that 'broadcast' against each other. ix_ is a handy way of generating these:
In [73]: arr[np.ix_([1,2],[2,3])]
Out[73]:
array([[106, 107],
[110, 111]])
In [74]: arr[np.ix_([1,2],[2,3])] -= 100
In [75]: arr
Out[75]:
array([[ 0, 1, 2, 3],
[ 4, 5, 6, 7],
[ 8, 9, 10, 11]])
Here's what ix_ produces - a tuple of arrays, one is (2,1) in shape, the other (1,2). Together they index a (2,2) block:
In [76]: np.ix_([1,2],[2,3])
Out[76]:
(array([[1],
[2]]), array([[2, 3]]))
For the continuous rows and columns case, you can use basic slicing like this:
In [634]: a
Out[634]:
array([[0, 1, 2],
[3, 4, 5],
[6, 7, 8]])
In [635]: b = np.asarray([[100, 101],[102, 103]])
In [636]: a[:rows_to_keep[1]+1, columns_to_keep[0]:] = b
In [637]: a
Out[637]:
array([[ 0, 100, 101],
[ 3, 102, 103],
[ 6, 7, 8]])
I want to create a list of items from a range using the map command. I have the following code that's supposed to take the range between two numbers (firstnum and secondnum) and a lambda statement that says to increment between the two numbers and create myList of the results (between the two ends of the range). However my syntax is wrong, not sure why...
["myList"] = map(lambda x, y: x + 1, range(firstnum..secondnum))
This would be valid syntax:
>>> list(map(lambda x: x + 1, range(2, 12)))
[3, 4, 5, 6, 7, 8, 9, 10, 11, 12]
But you can get the same result much simpler:
>>> list(range(3, 13))
[3, 4, 5, 6, 7, 8, 9, 10, 11, 12]
Or more general:
>>> firstnum = 2
>>> secondnum = 12
>>> (list(map(lambda x: x + 1, range(firstnum, secondnum))) ==
list(range(firstnum + 1, secondnum + 1)))
True
possible_list = []
bigger_list = []
new_list= [0, 25, 2, 1, 14, 1, 14, 1, 4, 6, 6, 7, 0, 10, 11]
for i in range(0,len(new_list)):
# if the next index is not greater than the length of the list
if (i + 1) < (len(new_list)):
#if the current value is less than the next value
if new_list[i] <= new_list[i+1]:
# add the current value to this sublist
possible_list.append(new_list[i])
# if the current value is greater than the next, close the list and append it to the lager list
bigger_list.append(possible_list)
print bigger_list
How do I find the longest consistent increment in the list called new_list?
I expect the result to be
[[0,2], [2], [1,14], [1,14], [1,4,6,6,7], [0,10,11]]
I can find the remaining solution from there myself.
One problem (but not the only one) with your code is that you are always adding the elements to the same possible_list, thus the lists in bigger_list are in fact all the same list!
Instead, I suggest using [-1] to access the last element of the list of subsequences (i.e. the one to append to) and [-1][-1] to access the last element of that subsequence (for comparing the current element to).
new_list= [0, 25, 2, 1, 14, 1, 14, 1, 4, 6, 6, 7, 0, 10, 11]
subseq = [[]]
for e in new_list:
if not subseq[-1] or subseq[-1][-1] <= e:
subseq[-1].append(e)
else:
subseq.append([e])
This way, subseq ends up the way you want it, and you can use max to get the longest one.
>>> subseq
[[0, 25], [2], [1, 14], [1, 14], [1, 4, 6, 6, 7], [0, 10, 11]]
>>> max(subseq, key=len)
[1, 4, 6, 6, 7]
I was wondering how i would go about counting combinations in a list. To be more precise i have a list that is comprised of smaller lists that are made up of 6 randomly chosen numbers and i want to count how many times each combinations occurs within the bigger list and then finally display the least occurring combination. So far i tried using Counter() but it seems it can't count lists.
here's an example of what i want to do:
list = [[1,2,3,4,5,6],[1,5,16,35,55,22],[1,2,3,4,5,6],[5,25,35,45,55,10],[1,5,16,35,55,22],[1,2,3,4,5,6],[9,16,21,22,23,6],[9,16,21,22,23,6]]
so after counting the combinations it should print the combination [5,25,35,45,55,10]
since it only occurred once in the list
FYI the list is going to randomly generated with around 1 billion combinations stored but given the range of numbers, there's only 175 million possible combinations
FYI 2 i'm extremely new to python
When you construct the Counter instance you can convert your lists to tuples; the latter are hashable, which is the property an object needs to be able to serve as a key of a dict.
>>> from collections import Counter
>>> l = [[1,2,3,4,5,6],[1,5,16,35,55,22],[1,2,3,4,5,6],[5,25,35,45,55,10],[1,5,16,35,55,22],[1,2,3,4,5,6],[9,16,21,22,23,6],[9,16,21,22,23,6]]
>>> c = Counter(tuple(e) for e in l)
>>> c
Counter({(1, 2, 3, 4, 5, 6): 3, (1, 5, 16, 35, 55, 22): 2, (9, 16, 21, 22, 23, 6): 2, (5, 25, 35, 45, 55, 10): 1})
>>> list(c.most_common()[-1][0])
[5, 25, 35, 45, 55, 10]