Project description

Ordinary Kriging interpolation

Ordinary Kriging interpolation is a linear estimation of regionalized variables. It assumes that the data change into a normal distribution, and considers that the expected value of regionalized variable $Z$is unknown. The interpolation process is similar to the weighted sliding average, and the weight value is determined by spatial data analysis.

ArcGIS has the implementation of this interpolation method, which is rarely used in Python environment, but this project carries out a simple implementation.

Dependencies

How to get it

pip install kriging

Project details

These details have not been verified by PyPI

Release history Release notifications | RSS feed

This version

0.0.1

Aug 21, 2020

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

kriging-0.0.1.tar.gz (813.8 kB view hashes)

Uploaded Aug 21, 2020 Source

Built Distribution

kriging-0.0.1-py3-none-any.whl (815.4 kB view hashes)

Uploaded Aug 21, 2020 Python 3

Hashes for kriging-0.0.1.tar.gz

Hashes for kriging-0.0.1.tar.gz
Algorithm	Hash digest
SHA256	`9d68a3cec6acbe63a8430f714f3acb034305c491b7d8ab59fb18e0a02d34642e`
MD5	`d9242cced8752aa2e69502993f33f420`
BLAKE2b-256	`9a45bd7e616b16d19156ef3ba6a4400d218f25cbc1fbfb53516f793c4bb44f9b`

Hashes for kriging-0.0.1-py3-none-any.whl

Hashes for kriging-0.0.1-py3-none-any.whl
Algorithm	Hash digest
SHA256	`5b3faa3b799421c0c31f2ca7280a9914f5402066674dcdc3e23a59fba884cdf1`
MD5	`e8c28388cde63c25a73e929fd8dbf1ea`
BLAKE2b-256	`0fbc4be280441047c3f061143b5be74ecb1dba8366788ed6abc01429ce23344f`