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np Examples and Code Snippets
Lines of Code : 29
License : No License
Copypublic static int dpApproach(int n, int r) {
if(r > n) return -1;
if(n == r) return 1;
if(r == 0) return n;
int[][] dp = new int[n + 1][r + 1];
for (int i = 1; i <= n; i++) {
for (int j = 0; j <= r; j++) {
if (i & Community Discussions
Trending Discussions on np
QUESTION
I'd like to construct an object that works like a random number generator, but generates numbers in a specified sequence.
...ANSWER
Answered 2022-Mar-29 at 00:47You can call next() with a generator or iterator as an argument to withdraw exactly one element from it. Saving the generator to a variable beforehand allows you to do this multiple times.
QUESTION
I saw a video about speed of loops in python, where it was explained that doing sum(range(N)) is much faster than manually looping through range and adding the variables together, since the former runs in C due to built-in functions being used, while in the latter the summation is done in (slow) python. I was curious what happens when adding numpy to the mix. As I expected np.sum(np.arange(N)) is the fastest, but sum(np.arange(N)) and np.sum(range(N)) are even slower than doing the naive for loop.
Why is this?
Here's the script I used to test, some comments about the supposed cause of slowing done where I know (taken mostly from the video) and the results I got on my machine (python 3.10.0, numpy 1.21.2):
updated script:
...ANSWER
Answered 2021-Oct-16 at 17:42From the cpython source code for sum sum initially seems to attempt a fast path that assumes all inputs are the same type. If that fails it will just iterate:
QUESTION
Say I have this array:
...ANSWER
Answered 2022-Jan-09 at 16:18You'd have to use np.repeat twice here.
QUESTION
I am trying to do a regular import in Google Colab.
This import worked up until now.
If I try:
ANSWER
Answered 2021-Oct-15 at 21:11Found the problem.
I was installing pandas_profiling, and this package updated pyyaml to version 6.0 which is not compatible with the current way Google Colab imports packages.
So just reverting back to pyyaml version 5.4.1 solved the problem.
For more information check versions of pyyaml here.
See this issue and formal answers in GitHub
##################################################################
For reverting back to pyyaml version 5.4.1 in your code, add the next line at the end of your packages installations:
QUESTION
I was using pyspark on AWS EMR (4 r5.xlarge as 4 workers, each has one executor and 4 cores), and I got AttributeError: Can't get attribute 'new_block' on . Below is a snippet of the code that threw this error:
...ANSWER
Answered 2021-Aug-26 at 14:53I had the same error using pandas 1.3.2 in the server while 1.2 in my client. Downgrading pandas to 1.2 solved the problem.
QUESTION
I used a function in Python/Numpy to solve a problem in combinatorial game theory.
...ANSWER
Answered 2022-Jan-19 at 09:34The original code can be re-written in the following way:
QUESTION
I am trying to efficiently compute a summation of a summation in Python:
WolframAlpha is able to compute it too a high n value: sum of sum.
I have two approaches: a for loop method and an np.sum method. I thought the np.sum approach would be faster. However, they are the same until a large n, after which the np.sum has overflow errors and gives the wrong result.
I am trying to find the fastest way to compute this sum.
...ANSWER
Answered 2022-Jan-16 at 12:49(fastest methods, 3 and 4, are at the end)
In a fast NumPy method you need to specify dtype=np.object so that NumPy does not convert Python int to its own dtypes (np.int64 or others). It will now give you correct results (checked it up to N=100000).
QUESTION
Assuming I want to write a function that accepts any type of number in Python, I can annotate it as follows:
...ANSWER
Answered 2021-Sep-29 at 20:20There is no general way to do this. Numbers are not strictly related to begin with and their types are even less.
While numbers.Number might seem like "the type of numbers" it is not universal. For example, decimal.Decimal is explicitly not a numbers.Number as either subclass, subtype or virtual subclass. Specifically for typing, numbers.Number is not endorsed by PEP 484 -- Type Hints.
In order to meaningfully type hint "numbers", one has to explicitly define what numbers are in that context. This might be a pre-existing numeric type set such as int <: float <: complex, a typing.Union/TypeVar of numeric types, a typing.Protocol to define operations and algebraic structure, or similar.
QUESTION
I have run the sklearn.manifold.TSNE example code from the sklearn documentation, but I got the error described in the questions' title.
I have already tried updating my sklearn version to the latest one (by !pip install -U scikit-learn) (scikit-learn=1.0.1). However, the problem is still there.
Does anyone know how to fix it?
- python = 3.7.12
- sklearn= 1.0.1
Example code:
...ANSWER
Answered 2021-Nov-03 at 12:01Delete learning_rate='auto' solved my problem.
Thanks @FlaviaGiammarino comment!!
QUESTION
Suppose you have either two arrays:
...ANSWER
Answered 2021-Oct-26 at 17:39Try broadcasting:
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