Metadata-Version: 2.1
Name: geosardine
Version: 0.13.0
Summary: Spatial operations extend fiona and rasterio
Home-page: https://github.com/sahitono/geosardine
License: BSD-3-Clause
Author: Sahit Tuntas Sadono
Author-email: 26474008+sahitono@users.noreply.github.com
Requires-Python: >=3.7,<4.0
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Scientific/Engineering :: GIS
Classifier: Typing :: Typed
Requires-Dist: affine (>=2.3.0,<3.0.0)
Requires-Dist: click (>=7.1.2,<8.0.0)
Requires-Dist: fiona (>=1.8.13,<2.0.0)
Requires-Dist: gdal (>=3.0.4,<4.0.0)
Requires-Dist: numba (>=0.51.2,<0.52.0)
Requires-Dist: numpy (>=1.18,<1.19.4)
Requires-Dist: opencv-python (>=4.4.0,<5.0.0)
Requires-Dist: rasterio (>=1.1.2,<2.0.0)
Requires-Dist: shapely (>=1.6.4,<2.0.0)
Requires-Dist: tqdm (>=4.48.2,<5.0.0)
Project-URL: Repository, https://github.com/sahitono/geosardine
Description-Content-Type: text/markdown

# Geo-Sardine :fish:
![python package](https://github.com/sahitono/geosardine/workflows/python%20package/badge.svg)
[![codecov](https://codecov.io/gh/sahitono/geosardine/branch/master/graph/badge.svg)](https://codecov.io/gh/sahitono/geosardine)
[![Maintainability](https://api.codeclimate.com/v1/badges/e7ec3c08fe42ef4b5e19/maintainability)](https://codeclimate.com/github/sahitono/geosardine/maintainability)

![PyPI - Python Version](https://img.shields.io/pypi/pyversions/geosardine)
![PyPI](https://img.shields.io/pypi/v/geosardine)
![Conda](https://img.shields.io/conda/v/sahitono/geosardine)

Spatial operations extend fiona and rasterio.
Collection of spatial operation which i occasionally use written in python:
 - Interpolation with IDW (Inverse Distance Weighting) Shepard
 - Drape vector to raster
 - Spatial join between two vector
 - Raster wrapper, for better experience. ie: math operation between two raster, resize and resample

:blue_book: documentation: https://sahitono.github.io/geosardine
## Setup
install with pip
```pip install geosardine```

or anaconda
```conda install -c sahitono geosardine```

## How to use it

#### Drape and spatial join
```python
import geosardine as dine
import rasterio
import fiona

with rasterio.open("/home/user/data.tif") as raster, fiona.open("/home/user/data.shp") as vector:
    draped = dine.drape_geojson(vector, raster)
    joined = dine.spatial_join(vector, raster) 
```
#### IDW Interpolation
```python
import numpy as np
import geosardine as dine
xy = np.array([
        [106.8358,  -6.585 ],
        [106.6039,  -6.7226],
        [106.7589,  -6.4053],
        [106.9674,  -6.7092],
        [106.7956,  -6.5988]
])
values = np.array([132., 127.,  37.,  90., 182.])

"""
if epsg not provided, it will assume that coordinate is in wgs84 geographic
Find your epsg here https://epsg.io/
"""
interpolated = dine.interpolate.idw(xy, values, spatial_res=(0.01,0.01), epsg=4326)

# Save interpolation result to tiff
interpolated.save('idw.tif')

# shapefile or geojson can be used too
interp_file = dine.interpolate.idw("points.shp", spatial_res=(0.01,0.01), column_name="value")
interp_file.save("idw.tif")

# The result array can be accessed like this
print(interpolated.array)
"""
[[ 88.63769859  86.24219616  83.60463194 ... 101.98185127 103.37001289
  104.54621272]
 [ 90.12053232  87.79279317  85.22030848 ... 103.77118852 105.01425289
  106.05302554]
 [ 91.82987695  89.60855271  87.14722258 ... 105.70090081 106.76928067
  107.64635337]
 ...
 [127.21214817 127.33208302 127.53878268 ...  97.80436475  94.96247196
   93.12113458]
 [127.11315081 127.18465002 127.33444124 ...  95.86455668  93.19212577
   91.51135399]
 [127.0435062  127.0827023  127.19214624 ...  94.80175756  92.30685734
   90.75707134]]
"""


```


## Raster Wrapper
Geosardine include wrapper for raster data. The benefit are:
1. math operation (addition, subtraction, division, multiplication) between rasters of different size, resolution and reference system.
   The data type result is equal to the first raster data type

   for example:
   ```
   raster1 = float32 and raster2 = int32
   raster3 = raster1 - raster2
   raster3 will be float32
   ```
   

2. resample with opencv
3. resize with opencv
4. split into tiled
   

```python
from geosardine import Raster


"""
minimum parameter needed to create raster are 
1. 2D numpy array, example: np.ones(18, dtype=np.float32).reshape(3, 3, 2)
2. spatial resolution, example:  0.4 or ( 0.4,  0.4)
3. left coordinate / x minimum
4. bottom coordinate / y minimum
"""
raster1 = Raster(np.ones(18, dtype=np.float32).reshape(3, 3, 2), resolution=0.4, x_min=120, y_max=0.7)

## resample
resampled = raster.resample((0.2,0.2))
## resize
resized = raster.resize(height=16, width=16)

## math operation between raster
raster_2 = raster + resampled
raster_2 = raster - resampled
raster_2 = raster * resampled
raster_2 = raster / resampled

## math operation raster to number
raster_3 = raster + 2
raster_3 = raster - 2
raster_3 = raster * 2
raster_3 = raster / 2

### plot it using raster.array
import matplotlib.pyplot as plt
plt.imshow(raster_3)
plt.show()

```



## Geosardine CLI
You can use it through terminal or command prompt by calling **dine**

```
$ dine --help
Usage: dine [OPTIONS] COMMAND [ARGS]...

  GeoSardine CLI

Options:
  --help  Show this message and exit.

Commands:
  drape         Drape vector to raster to obtain height value
  info          Get supported format
  join-spatial  Join attribute by location
  idw           Create raster with Inverse Distance Weighting interpolation
```

### License
[![License](https://img.shields.io/badge/License-BSD%203--Clause-blue.svg)](https://opensource.org/licenses/BSD-3-Clause)

