interpolation.py

by EconForge Python Version: v2.2.1 License: BSD-2-Clause

X-Ray Key Features Code Snippets Community Discussions(4)Vulnerabilities Install Support

kandi X-RAY | interpolation.py Summary

interpolation.py is a Python library. interpolation.py has no vulnerabilities, it has a Permissive License and it has low support. However interpolation.py has 13 bugs and it build file is not available. You can download it from GitHub.

interpolation.py

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interpolation.py has a low active ecosystem.

It has 102 star(s) with 25 fork(s). There are 13 watchers for this library.

It had no major release in the last 12 months.

There are 14 open issues and 41 have been closed. On average issues are closed in 152 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of interpolation.py is v2.2.1

Quality

interpolation.py has 13 bugs (11 blocker, 0 critical, 2 major, 0 minor) and 516 code smells.

Security

interpolation.py has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

interpolation.py code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

interpolation.py is licensed under the BSD-2-Clause License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

interpolation.py releases are available to install and integrate.

interpolation.py has no build file. You will be need to create the build yourself to build the component from source.

interpolation.py saves you 2209 person hours of effort in developing the same functionality from scratch.

It has 4834 lines of code, 201 functions and 39 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed interpolation.py and discovered the below as its top functions. This is intended to give you an instant insight into interpolation.py implemented functionality, and help decide if they suit your requirements.

Builds a grid from a given distribution
Return a list of indices that are within a given sum
Generate a chain of n s
Generate a set of values from the nested sequence
R Hermite Interpolation
Interpolate through the Hermite quadratic model
Perform Hermite interpolation
Calculate the Hamiltonian angles
Set the coefficients
Filter coefficients in 3d
Filter coefficients
Linear interpolation function
Compute tensor reduction
Calculate the coefficients of X
Evaluate vector interpolation
Interpolate aa formula
The grid of the grid
Returns the grid
Evaluate a linear interpolation
Get a spline code from a given d
Filter coefficients according to coefficients
Computes tensor reduction
Multilinear interpolation
Evaluate a cubic cubic spline
Helper function for prefilter
Get the value of a function
Find coefficients in 3d
Compute the coefficients of the function X
Evaluate a cubic spline
Set the mvalues of the interpolation
Pairwise interpolation

Get all kandi verified functions for this library.

interpolation.py Key Features

No Key Features are available at this moment for interpolation.py.

interpolation.py Examples and Code Snippets

No Code Snippets are available at this moment for interpolation.py.

Community Discussions

Trending Discussions on interpolation.py

Error in calculating integral for 2D interpolation. Comparing numpy arrays

Django cookiecutter docker build failing: maximum recursion depth exceeded

Unable to resample then plot a Pandas Data Frame

Trying to to use Caffe classifier causes "sequence argument must have length equal to input rank "error

QUESTION

Error in calculating integral for 2D interpolation. Comparing numpy arrays

Asked 2018-Apr-30 at 09:38

My optimization task deals with calculation of the following integral and finding the best values of xl and xu:

Iterations take too long, so I decided to speed them up by calculating integral for all possible values xl and xu and then interpolate calculated values during optimization.

I wrote the following function:

...

ANSWER

Answered 2018-Apr-28 at 23:02

I can't reproduce your error unless I omit the np.vectorize decorator. Setting xl/xu values that coincide does give me a ZeroDivisionError though.

Anyway, there's nothing stopping you from checking the values of xu vs xl in your higher-level function. That way you can skip integration entirely for nonsensical data points and return np.nan early:

Source https://stackoverflow.com/questions/49557809

QUESTION

Django cookiecutter docker build failing: maximum recursion depth exceeded

Asked 2018-Apr-08 at 10:14

I've been using the cookiecutter docker setup for local development which has been working wonderfully. I'm now ready to build and deploy a production version of my application.

I've followed the instructions here and here.

It all seems pretty straight-forward, however when I run the build command:

...

ANSWER

Answered 2018-Apr-08 at 10:14

It looks like you ran into an old bug.

Does any of your auto-generated long string start with $? If that's the case, it's causing django-environ to try to interpolate the value and crashing. Try re-generating these, and it should fix it.

Source https://stackoverflow.com/questions/49710829

QUESTION

Unable to resample then plot a Pandas Data Frame

Asked 2017-Oct-28 at 16:56

I have been trying to plot a simple resampled data that is coming from a Pandas dataframe. Here is my initial code:

...

ANSWER

Answered 2017-Oct-28 at 16:48

date is not column, but index, so need:

Source https://stackoverflow.com/questions/46992158

QUESTION

Trying to to use Caffe classifier causes "sequence argument must have length equal to input rank "error

Asked 2017-Jul-22 at 17:44

I am trying to use Caffe.Classifier class and its predict() method on my Imagenet trained caffemodel.
Images were resized to 256x256 and crops of 227x227 were used to train the net.
Everything is simple and straight forward, yet I keep getting weird errors such as the following :

...

ANSWER

Answered 2017-Jul-22 at 17:44

I found the cause, I had to feed the image in the form of 3D tensor not a 4D one! so our 4d tensor:

Source https://stackoverflow.com/questions/44321679

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install interpolation.py

You can download it from GitHub.
You can use interpolation.py like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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