sylvester | Vector , matrix and geometry math JavaScript | Math library
kandi X-RAY | sylvester Summary
kandi X-RAY | sylvester Summary
Vector and Matrix math for JavaScript. See the website for documentation.
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- Returns the surface integral of the surface .
sylvester Key Features
sylvester Examples and Code Snippets
def sylvester(number: int) -> int:
"""
:param number: nth number to calculate in the sequence
:return: the nth number in Sylvester's sequence
>>> sylvester(8)
113423713055421844361000443
>>> sylvester(-1
Community Discussions
Trending Discussions on sylvester
QUESTION
I have a use case where I need to run the same command multiple times inside a rule. However, the command arguments need to change based on the return value of another command. I found that one can do $(call foo_exec)
to invoke a macro from within a rule, which is great. However, consider the following simplified code:
ANSWER
Answered 2021-Nov-13 at 00:27The following works
QUESTION
I have a multi-column Combobox, and tried to search for a codes for awhile now, but to no avail.
Here's my combobox looks like:
...ANSWER
Answered 2021-Oct-28 at 06:15You need to use ListIndex
:
QUESTION
I have a python script where I compute the value of a normal log-likelihood function for a sample of bivariate data using scipy's multivariate_normal.log_pdf
. I am assuming the values of the sample means and variances, leaving only the sample correlation between the variables as the unknown,
ANSWER
Answered 2021-Sep-22 at 13:44You are on the right track. Note that your definiteness constraint reduces to a simple bound on the optimization variable, i.e. -∞ <= x[0] <= VAR_X*VAR_Y
. Variable bounds are better handled internally than the more general constraints, so I'd recommend something like this:
QUESTION
I'm creating a non-linear response to a series of random values from {-1, +1} using a simple Volterra kernel:
With a zero mean for a(k)
values I would expect r(k)
to have a zero mean as well for arbitrary w
values. However, I get r(k)
with an always positive mean value, while a mean for a(k)
behaves as expected: is close to zero and changes sign from run to run.
Why don't I get a similar behavior for r(k)
? Is it because a(k)
are pseudo-random and two different values from a
are not actually independent?
Here is a code that I use:
...ANSWER
Answered 2021-Mar-21 at 13:17I'm not certain if this is the case for Volterra kernels, but many kernels are positive definite, and some kernels, such as covariance functions, do not admit values less than zero (e.g. Squared Exponential/RBF, Rational Quadratic, Matern kernels).
If these are not the cases for the Volterra kernel, you can also try changing the random seed to seed the RNG differently to check if this is still the case. Here is a looped version of your code that iterates over different random seeds:
QUESTION
In the university I had a quiz today. The quiz is over but I can't understand some of its questions are their correct answers.
Note: I am not asking this to solve my quiz. Quiz is over I am just confused in some questions.
Question 1:Consider the following variable declarations:
...ANSWER
Answered 2021-Jan-06 at 09:123 errors in question 2:
- missing ( ) around the if condition
- in the second part of the if condition there must be double ==
- { } are missing
To be a valid code it must be set like this:
QUESTION
I have a dataframe made by many rows which includes tweets. I would like to classify them using a machine learning technique (supervised or unsupervised). Since the dataset is unlabelled, I thought to select a few rows (50%) to label manually (+1 pos, -1 neg, 0 neutral), then using machine learning to assign labels to the other rows. In order to do this, I did as follows:
Original Dataset
...ANSWER
Answered 2020-Jul-26 at 00:24IIUC, you have a percentage of the data labelled and require labelling the remaining data. I would recommend reading about Semi-Supervised machine learning.
Semi-supervised learning is an approach to machine learning that combines a small amount of labeled data with a large amount of unlabeled data during training. Semi-supervised learning falls between unsupervised learning (with no labeled training data) and supervised learning (with only labeled training data)
Sklearn provides quite an extensive variety of algorithms that can assist with this. Do check this out.
If you need more insight into this topic I would highly recommend checking this article out as well.
Here is an example with the iris data set -
QUESTION
To initialize a List
you have to use individual type initializer for each element - something like this:
ANSWER
Answered 2020-Jun-25 at 15:19Collection initializers for List
and Dicitionary
use internally Add
method, for List
it is public void Add (T item);
and for dictionary it is public void Add (TKey key, TValue value);
, so Dictionary
collection initializer does not actually construct KeyValuePair
to pass it to the Add
method and this code:
QUESTION
Lets say I have a dictionary,
...ANSWER
Answered 2020-Apr-06 at 14:16The dictionary comprehension only has separate expressions for key and value. k : v
by itself isn't a valid expression, so it can't be nested inside an if-then-else expression either. You'd need to wrap key and value each in a separate if-then-else expression for it to work.
Luckily, as the key is the same in both cases, you just need to make an expression for the value.
QUESTION
Let's say I have a spreadsheet that looks something like this:
...ANSWER
Answered 2020-Mar-25 at 19:07try:
QUESTION
I have a XML source similar to this:
...ANSWER
Answered 2020-Feb-24 at 19:13Why not simply:
XSLT 2.0
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