snuggs | Snuggs are s-expressions for Numpy | Machine Learning library

by mapbox Python Version: 1.4.7 License: MIT

X-Ray Key Features Code Snippets(2)Community Discussions(4)Vulnerabilities Install Support

kandi X-RAY | snuggs Summary

snuggs is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Numpy applications. snuggs has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install snuggs' or download it from GitHub, PyPI.

Snuggs are s-expressions for Numpy

Support

Quality

Security

License

Reuse

Support

snuggs has a low active ecosystem.

It has 15 star(s) with 5 fork(s). There are 78 watchers for this library.

It had no major release in the last 12 months.

There are 0 open issues and 18 have been closed. On average issues are closed in 76 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of snuggs is 1.4.7

Quality

snuggs has 0 bugs and 0 code smells.

Security

snuggs has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

snuggs code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

snuggs is licensed under the MIT License. This license is Permissive.

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

Reuse

snuggs releases are not available. You will need to build from source code and install.

Deployable package is available in PyPI.

Build file is available. You can build the component from source.

Top functions reviewed by kandi - BETA

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

Evaluate source
Process a line
Process argument
Process a list of arguments
Resolve a variable
Get the value of a key

Get all kandi verified functions for this library.

snuggs Key Features

No Key Features are available at this moment for snuggs.

snuggs Examples and Code Snippets

Installing cartopy from pip exits with various errors on Linux Ubuntu 18.04

Python

Lines of Code : 79

License : Strong Copyleft (CC BY-SA 4.0)

Copy

andylu@andylu-ThinkPad-Edge-E130:~/Desktop/Python/Scripts$ sudo find / -type f -iname "unixccompiler.py"
find: ‘/run/user/1000/gvfs’: Permission denied
find: ‘/tmp/.mount_pcloudgeFVGR’: Permission denied
/snap/core/9436/usr/lib/python3.5/d

How can I improve the performance of my script?

Python

Lines of Code : 76

License : Strong Copyleft (CC BY-SA 4.0)

Copy

temp_df['rel_contribution'] = 0.0
temp_df['rel_contribution'] = temp_df['overlay_area']/sum(temp_df.area)

temp_df = merged_df[merged_df['seed_index'] == row['seed_index']]

# Merge datafarme

Community Discussions

Trending Discussions on snuggs

Import rasterio failed. Reason: image not found

Installing cartopy from pip exits with various errors on Linux Ubuntu 18.04

How can I improve the performance of my script?

Why does geopandas throw an assertion error, when the conditions seems to be met?

QUESTION

Import rasterio failed. Reason: image not found

Asked 2020-Sep-22 at 05:37

I'm going to use rasterio in python. I downloaded rasterio via

...

ANSWER

Answered 2020-Sep-22 at 05:37

I've got some experience with rasterio, but I am not nearly a master with it. If I remember correctly, rasterio requires you to have installed the program GDAL(both binaries and python utilities), and some other dependencies listed on the PyPi page. I don't use conda at the moment, I like to use the regular python 3.8 installer with pip. Given what I'm seeing with your installation, I would uninstall rasterio and follow a different installation procedure.

I follow the instructions listed here: https://rasterio.readthedocs.io/en/latest/installation.html
This page also has separate instructions for those using Anaconda.

The GDAL installation is by far the most annoying but once it's done, the hard part is over. The python utilities for both rasterio and gdal can be found here:
https://www.lfd.uci.edu/~gohlke/pythonlibs/#gdal
The second link is also provided on the PyPi page but I like to keep it bookmarked because there's a lot of good resources there!

Source https://stackoverflow.com/questions/64002714

QUESTION

Installing cartopy from pip exits with various errors on Linux Ubuntu 18.04

Asked 2020-Aug-04 at 08:40

The shell command pip install cartopy led to several errors.

At first, the following error occurred:

...

ANSWER

Answered 2020-Aug-04 at 08:40

After searching solutions to the main error message c++: error: unrecognized command line option '-R', I finally found it in this discussion.

What I did was searching for the relevant files using the mighty find method:

Source https://stackoverflow.com/questions/63236626

QUESTION

How can I improve the performance of my script?

Asked 2020-Feb-27 at 18:33

I have a "seed" GeoDataFrame (GDF)(RED) which contains a 0.5 arc minutes global grid ((180*2)*(360*2) = 259200). Each cell contains an absolute population estimate. In addition, I have a "leech" GDF (GREEN) with roughly 8250 adjoining non-regular shapes of various sizes (watersheds).

I wrote a script to allocate the population estimates to the geometries in the leech GDF based on the overlapping area between grid cells (seed GDF) and the geometries in the leech GDF. The script works perfectly fine for my sample data (see below). However, once I run it on my actual data, it is very slow. I ran it overnight and the next morning only 27% of the calculations had been performed. I will have to run this script many times and waiting for two days each time, is simply not an option.

After doing a bit of literature research, I already replaced (?) for loops with for index i in df.iterrows() (or is this the same as "conventional" python for loops) but it didn't bring about the performance imporvement I had hoped for.

Any suggestion son how I can speed up my code? In twelve hours, my script only processed only ~30000 rows out of ~200000.

My expected output is the column leech_df['leeched_values'].

...

ANSWER

Answered 2020-Feb-27 at 18:33

Introduction

It might be worthy to profile your code in details to get precise insights of what is your bottleneck.

Bellow some advises to already improve your script performance:

Avoid list.append(1) to count occurrences, use collection.Counter instead;
Avoid pandas.DataFrame.iterrows, use pandas.DataFrame.itertuples instead;
Avoid extra assignation that are not needed, use pandas.DataFrame.fillna instead:

Eg. this line:

Source https://stackoverflow.com/questions/60338228

QUESTION

Why does geopandas throw an assertion error, when the conditions seems to be met?

Asked 2020-Jan-22 at 15:14

I am trying to make a WFS request and create a GeoDataFrame (from the geopandas library) with this data. However, when I run my code, an assert raises an error:

...

ANSWER

Answered 2020-Jan-22 at 15:14

You don't have a list with four elements, you have a string.

To solve this, split your string to create a list before the assert, like bb = bb.split(',').

Source https://stackoverflow.com/questions/59860075

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

Vulnerabilities

No vulnerabilities reported

Install snuggs

You can install using 'pip install snuggs' or download it from GitHub, PyPI.
You can use snuggs 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 .

Find more information at: