spatialpixel | Computational design toolkit from Spatial Pixel

by awmartin Python Version: v0.4.0 License: MIT

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

kandi X-RAY | spatialpixel Summary

spatialpixel is a Python library typically used in Internet of Things (IoT), Deep Learning applications. spatialpixel has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However spatialpixel build file is not available. You can download it from GitHub.

Computational design toolkit from Spatial Pixel.

Support

Quality

Security

License

Reuse

Support

spatialpixel has a low active ecosystem.

It has 12 star(s) with 10 fork(s). There are no watchers for this library.

It had no major release in the last 12 months.

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

It has a neutral sentiment in the developer community.

The latest version of spatialpixel is v0.4.0

Quality

spatialpixel has 0 bugs and 0 code smells.

Security

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

spatialpixel code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

spatialpixel 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

spatialpixel releases are available to install and integrate.

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

Installation instructions are not available. Examples and code snippets are available.

spatialpixel saves you 705 person hours of effort in developing the same functionality from scratch.

It has 1629 lines of code, 262 functions and 38 files.

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

Top functions reviewed by kandi - BETA

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

Render the map
Clear the map
Gets the url for a tile
Make a GET request
Extract locations from Google Maps
Close the button
Add a marker to the map
Make a request to the Overpass API
Parses the document
Draws the button
Set fill color
Draw the button
Parse features
Parse the xml element
Default styling
Draw the map
Draws the label
Parse the entrypoint
Request the next image
Returns bounding box
Close the widget
Parse the geometries
Parses the coordinates
Parses the xml
Parses a file
Parse the coordinates element
Parses the geometries

Get all kandi verified functions for this library.

spatialpixel Key Features

No Key Features are available at this moment for spatialpixel.

spatialpixel Examples and Code Snippets

No Code Snippets are available at this moment for spatialpixel.

Community Discussions

Trending Discussions on spatialpixel

Polygons shifted north of raster even with same CRS

Kriging using the gstat and automap packages - problems when copying a tutorial

ggplot gridded SpatialPolygonsDataFrame producing odd triangles and subsetting data based on point data

Exporting Kriged Values from R

QUESTION

Polygons shifted north of raster even with same CRS

Asked 2021-Dec-02 at 11:04

I am having trouble. I am unable to identify the issue when plotting a SpatialPixelDataframe and a SpatialPolygonDataframe with the same CRS in tmaps.

The spatialpixels object can be found here saved as RDS, and the polygons shapefile here, zipped.

Here is my attempt with base functions:

...

ANSWER

Answered 2021-Dec-02 at 11:04

As @krenz mentioned you're using different classes here together, however, I'm not fully sure what causes the problem.

Here's a workaround in which your data is first converted to a sf object which is then rasterized using st_rasterize. The result only differs slightly from what you showed. Maybe you have to play around a little bit with the resolution parameters:

Source https://stackoverflow.com/questions/70080641

QUESTION

Kriging using the gstat and automap packages - problems when copying a tutorial

Asked 2021-Nov-24 at 19:49

For several locations in my study site i have water depth (m) data, and i'm trying to use kriging to interpolate depth to locations for which i do not have data. I found a useful blog post written by Dr. Wilke here, and tried to apply his code to my data set. However, when i run all the code and plot the results, the plots all come back empty (grey boxes; the depths samples comes back with grey dots instead of colours that reflect depth on continuous scale). Could anyone please tell me what i'm doing wrong? Below is the code that i tried. I suspect the issue lies with step 2, as the code output starts to deviate here from the blog code output.

Setup ...

ANSWER

Answered 2021-Nov-24 at 19:49

It looks like the culprit is in the ggplot sections of the code. When using scale_color_viridis(), you need to change the limits to fit your data. Since the depths in your data are 0 to 28, then you should change the limits from c(50, 100) to something like c(0, 30).

Source https://stackoverflow.com/questions/70101647

QUESTION

ggplot gridded SpatialPolygonsDataFrame producing odd triangles and subsetting data based on point data

Asked 2021-Jan-19 at 10:08

Using the code below I can plot the following: This code is adapted from here

As you can see there are few issues with the plot. I am struggling to

Remove weird lines in plot
Only plot cells (grids) where there are data
Plot ID (see gridSpatialPolygons$values) on top of the grid cell

I realise there are a few points to this question but I hope one solution solves all.

...

ANSWER

Answered 2021-Jan-19 at 10:08

When it comes to spatial objects, ggplot2 (and tidyverse in general) seems to play nicer with sf than sp. The advice below is taken from one of the help files in the associated broom package:

Note that the sf package now defines tidy spatial objects and is the recommended approach to spatial data. sp tidiers are likely to be deprecated in the near future in favor of sf::st_as_sf(). Development of sp tidiers has halted in broom.

Things should be fairly straightforward after conversion to sf.

Source https://stackoverflow.com/questions/65777087

QUESTION

Exporting Kriged Values from R

Asked 2020-Apr-10 at 19:40

Does anyone have any suggestions on how to export the values from your kriged data in R. I have them exported as a raster, but I need the actual cell values. The data that I'm working with are fish densities. I'm kriging the data and then converting to densities to abundance. BUT in order to convert to abundances I need the kriged values in .csv format.

Below is the code that I'm using:

...

ANSWER

Answered 2020-Apr-10 at 19:40

Your example is neither minimal nor reproducible. You could have taken an example from gstat It looks like you are interested in object fsite.ok. Presumably a Spatial*DataFrame.

Example code

Source https://stackoverflow.com/questions/61129847

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

Vulnerabilities

No vulnerabilities reported

Install spatialpixel

You can download it from GitHub.
You can use spatialpixel 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

If you'd like to contribute, please fork the repo, create a new branch, and send a pull request with a descriptive message. Screenshots are very helpful. :).

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