spatialanalytics | 0 Workshop Code : Spatial Analysis

by datawrangling Python Version: Current License: No License

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

kandi X-RAY | spatialanalytics Summary

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

Where 2.0 Workshop Code: Spatial Analysis of Tweets using Hadoop, Pig, Python & Mechanical Turk. Slides here: http://www.slideshare.net/kevinweil/spatial-analytics-where-20-2010

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spatialanalytics has a low active ecosystem.

It has 134 star(s) with 13 fork(s). There are 10 watchers for this library.

It had no major release in the last 6 months.

spatialanalytics has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of spatialanalytics is current.

Quality

spatialanalytics has 0 bugs and 0 code smells.

Security

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

spatialanalytics code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

spatialanalytics does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

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

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

spatialanalytics saves you 145 person hours of effort in developing the same functionality from scratch.

It has 363 lines of code, 15 functions and 7 files.

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

Top functions reviewed by kandi - BETA

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

Read tweets from stdin .
Generate a heatmap .
Emits a list of ngrams .
Load intensities from a CSV file .
Clean a string .
Return datetime from a given timestamp .
Get the hour from the given timestamp .
Find n - grams in sequence .
Tokenize a text string .
Initialize the message .

Get all kandi verified functions for this library.

spatialanalytics Key Features

No Key Features are available at this moment for spatialanalytics.

spatialanalytics Examples and Code Snippets

No Code Snippets are available at this moment for spatialanalytics.

Community Discussions

Trending Discussions on spatialanalytics

Intersecting big spatial datasets in R SF

Parallelize st_union from R's sf package

QUESTION

Intersecting big spatial datasets in R SF

Asked 2019-Nov-19 at 10:33

I have two spatial datasets. One dataset contains lots polygons (more than 150k in total) specifying different features, like rivers, vegetation. The other dataset contains much less polygons (500) specifying different areas. I need to intersect those two datasets to get the features in the different areas. I can subset the first dataset by the different features. If I use a subset from a small feature (2,500 polygons) the intersection with the areas is quite fast (5min). But if I want to interest a bigger feature subset (20,000 polygons) the computation runs really long (I terminated it after two hours). And this is not even the biggest feature (50,000 polygons) I need to intersect.

This is the code snipped I run:

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ANSWER

Answered 2019-Nov-19 at 10:33

As there probably won´t come a real answer to this vague question I will answer it on my own.

Thanks @Chris and @TimSalabim for the help. I ended up with a combination of both ideas.

I ended up using PostGIS which is from my experience a pretty intuitive way to work with spatial data. The three things which speeded up the calculations of intersection for me are:

In my chase the spatial data was stored in MULTIPOLYGONS when loading from shapefile. I expanded those into POLYGONS using ST_DUMP: https://postgis.net/docs/ST_Dump.html
I created a Spatial Index on the POLYGONS: https://postgis.net/workshops/postgis-intro/indexing.html
I used a combination of ST_Intersection and ST_Intersects to only call the costly ST_Intersection when realy needed (As @TimSalabim suggested, this approach could also speed up things in R....But I currently have no time to test this approach): https://postgis.net/2014/03/14/tip_intersection_faster/

Source https://stackoverflow.com/questions/58825990

QUESTION

Parallelize st_union from R's sf package

Asked 2018-Feb-15 at 13:40

I have some large shapefiles with multiple millions of polygons that I need to dissolve. Depending upon the shapefile I need to either dissolve by group or just use st_union for all. I have been using the st_par function and it has been working great for most sf applications. Though when I use this function on st_union it returns a list and I cannot figure out how to parallize the sf dissolve function st_union.

Any suggestions would be most helpful! Here is a small code snippet to illustrate my point.

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ANSWER

Answered 2018-Feb-15 at 10:04

I think you can solve your specific problem with a small modification of the original st_par function.
However this is just a quick and bold fix and this might broke the code for other uses of the function.
The author of the function could certainly provide a better fix...

Source https://stackoverflow.com/questions/48800375

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

Vulnerabilities

No vulnerabilities reported

Install spatialanalytics

You can download it from GitHub.
You can use spatialanalytics 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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