topography :earth_americas:

Contains different approaches to modeling terrain and topographic-style maps in python

Requirements

• numpy
• matplotlib

see the requirements.txt

Features

Inverse Distance Weighting (IDW)

A given point P(x, y) is determined by the values of its neighbors, inversely to the distance of each neighbor.

P is more heavily influenced by nearer points via a weighting function w(x, y).

Steps

The value of P(x, y) is determined only by the closest raw data point.

This approach works best to get a "feel" for larger datasets. With few input points, the resulting map has little detail.

In the case of multiple equidistant points being closest, point values are stored, and averaged.

Nearest Neighbor (NN) [in progress :construction_worker: :hammer_and_wrench:]

Install

pip install topography

Example

from topography.Map import Map
from topography.utils.io import getPointValuesFromCsv

# take in csv/xlsx
rawData = getPointValuesFromCsv("tests/data/20x20.csv")

# make map from rawData
M = Map(rawData)

# Display the inputted raw data values
M.showRawPointValues()

# interpolate using inverse distance weighting
M.idw(showWhenDone=True)

# Display the interpolated data values
M.showFilledPointValues()

# Save the data to a .csv file
M.writeLastToCsv("idw_20x20", writeAsMatrix=True)

Development with twine

python setup.py sdist bdist_wheel
twine upload -r pypi dist/* -u <username> -p <password>