Metadata-Version: 2.1
Name: rgd-client
Version: 0.2.6.dev3
Summary: Make web requests to a Resonant GeoData instance.
Home-page: https://github.com/ResonantGeoData/ResonantGeoData
Author: Kitware, Inc.
Author-email: rgd@kitware.com
License: Apache 2.0
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python
Requires-Python: >=3.8
Description-Content-Type: text/markdown
Requires-Dist: requests
Requires-Dist: requests-toolbelt
Requires-Dist: geomet
Requires-Dist: tqdm
Requires-Dist: validators
Provides-Extra: dev
Requires-Dist: ipython ; extra == 'dev'

[![logo](https://raw.githubusercontent.com/ResonantGeoData/ResonantGeoData/main/logos/RGD_Logo.png)](https://github.com/ResonantGeoData/ResonantGeoData/)

# rgd_client - Resonant GeoDataClient

The **rgd_client** Python package allows users to make web requests to a Resonant GeoData instance within a Python script.


# Installation
```
pip install rgd-client
```

# Usage
### Search and display results
```python
import json
import matplotlib.pyplot as plt
import numpy as np

from rgd_client import Rgdc

def plot_geojson(gjs, *args, **kwargs):
    points = np.array(gjs['coordinates'])
    if points.ndim == 3:
        points = points[0]
    if points.ndim == 1:
        points = points.reshape((1, points.size, ))
    return plt.plot(points[:,0], points[:,1], *args, **kwargs)

client = Rgdc(username='username', password='password')
bbox = {
    "type":"Polygon",
    "coordinates":[
        [
            [-105.45091240368326,39.626245373878696],
            [-105.45091240368326,39.929904289147274],
            [-104.88775649170178,39.929904289147274],
            [-104.88775649170178,39.626245373878696],
            [-105.45091240368326,39.626245373878696]
        ]
    ]
}

q = client.search(query=json.dumps(bbox), predicate='intersects')

for s in q:
    print(s['subentry_name'])

plot_geojson(bbox, 'k--', label='Search Region')

for s in q:
    plot_geojson(s['footprint'], label=s['subentry_name'])

plt.legend()
plt.title(f'Count: {len(q)}')
```

### Inspect raster

Preview thumbnails of the raster

```python
import imageio
from io import BytesIO

raster = client.get_raster(q[0])
plot_geojson(bbox, 'k--')
plot_geojson(raster['outline'], 'r')
load_image = lambda imbytes: imageio.imread(BytesIO(imbytes))

count = len(raster['parent_raster']['image_set']['images'])
for i in range(count):
    thumb_bytes = client.download_raster_thumbnail(q[0], band=i)
    thumb = load_image(thumb_bytes)
    plt.subplot(1, count, i+1)
    plt.imshow(thumb)

plt.tight_layout()
plt.show()
```

### Download Raster

Download the entire image set of the raster

```python
import rasterio
from rasterio.plot import show

paths = client.download_raster(q[0])
rasters = [rasterio.open(im) for im in paths.images]
for i, src in enumerate(rasters):
    plt.subplot(1, len(rasters), i+1)
    ax = plt.gca()
    show(src, ax=ax)
plt.tight_layout()
plt.show()
```


### Upload Processed Imagery/Raster


```python
file_url = '...'  # Some already processed file that has been upload to S3

file = client.create_file_from_url(file_url)
image = client.create_image_from_file(file)
image_set = client.create_image_set([image, ])
raster = client.create_raster_from_image_set(image_set)
raster
```


### STAC Item Support

The Python client has a search endpoint specifically for Raster data that
returns each record in the search results as a STAC Item.

```py

q = client.search_raster_stac(query=json.dumps(bbox), predicate='intersects')

print(q[0])  # view result as STAC Item

# Download using the search result
paths = client.download_raster(q[0])
print(paths)

```

We can also upload new data in the STAC Item format. Here we simply pass back
the same STAC Item JSON which will not actually do anything because RGD
recognizes that these files are already present with a Raster.

```py
client.create_raster_stac(q[0])
```

Please note that the assets in the STAC Item must already be uploaded to a
cloud storage provider with either `s3://` or `https://` URLs. Further, the
images must have the `data` tag on each asset. e.g.:

```py
{
    ... # other STAC Item fields
    'assets': {
        'image-15030': {
            'href': 'http://storage.googleapis.com/gcp-public-data-sentinel-2/tiles/17/S/MS/S2A_MSIL1C_20210302T161201_N0209_R140_T17SMS_20210302T200521.SAFE/GRANULE/L1C_T17SMS_A029738_20210302T161751/IMG_DATA/T17SMS_20210302T161201_B01.jp2',
            'title': 'GRANULE/L1C_T17SMS_A029738_20210302T161751/IMG_DATA/T17SMS_20210302T161201_B01.jp2',
            'eo:bands': [{'name': 'B1'}],
            'roles': ['data'],
        },
        'image-15041': {
            'href': 'http://storage.googleapis.com/gcp-public-data-sentinel-2/tiles/17/S/MS/S2A_MSIL1C_20210302T161201_N0209_R140_T17SMS_20210302T200521.SAFE/GRANULE/L1C_T17SMS_A029738_20210302T161751/IMG_DATA/T17SMS_20210302T161201_B02.jp2',
            'title': 'GRANULE/L1C_T17SMS_A029738_20210302T161751/IMG_DATA/T17SMS_20210302T161201_B02.jp2',
            'eo:bands': [{'name': 'B1'}],
            'roles': ['data'],
        },
        ...  # ancillary files can lack a role but we like to see `metadata` used.
        'ancillary-30687': {
            'href': 'http://storage.googleapis.com/gcp-public-data-sentinel-2/tiles/17/S/MS/S2A_MSIL1C_20210302T161201_N0209_R140_T17SMS_20210302T200521.SAFE/GRANULE/L1C_T17SMS_A029738_20210302T161751/QI_DATA/MSK_TECQUA_B03.gml',
            'title': 'GRANULE/L1C_T17SMS_A029738_20210302T161751/QI_DATA/MSK_TECQUA_B03.gml',
            'roles': ['metadata'],
        },
    }
}
```


