Start rewrite true color notebooks

true-color-image/sentinel_helpers.py

@@ -1,50 +1,120 @@
-import glob
 import urllib.parse
 from pathlib import Path
 import zipfile
 
-import geopandas as gp
+import fiona
+import geopandas as gpd
+from matplotlib import pyplot as plt
+import numpy as np
 import rasterio as r
-
 from rasterio.warp import calculate_default_transform, reproject, Resampling
 
-def band_paths(p, bands, resolution=None):
-    '''
-    Given a zip file or folder at `p`, returns the paths inside p to the raster files containing
-    information for the given bands. Because some bands are available in more than one
-    resolution, this can be filtered by prodiding a third parameter (e.g. resolution='10m').
-   
-    The returned paths are formatted in the zip scheme as per Apache Commons VFS if necessary
-    and can be directly opened by rasterio.
-    '''
-    if p.endswith('.zip'):
-        with zipfile.ZipFile(p) as f:
-            files = f.namelist()
-            rasters = [f for f in files if f.endswith('.jp2')]
-    else:
-        rasters = glob.glob(Path(p) / '**/*.jp2')
-    rasters = [r for r in rasters for b in bands if b in r]
-    if resolution:
-        rasters = [r for r in rasters if resolution in r]
-
-    rasters = ['zip+file://' + p + '!/' + r for r in rasters]
-    return rasters
-
- 
-def rgb_paths(zip_file, resolution='10m'):
-    return band_paths(zip_file, ['B02', 'B03', 'B04'], resolution)
-
-
 def search_osm(place):
     '''
     Returns a GeoDataFrame with results from OpenStreetMap Nominatim for the given search string.
     This allows us to fetch detailed geometries for virtually any place on earth.
     '''
     urlescaped_place = urllib.parse.quote(place)
-    search_url = 'https://nominatim.openstreetmap.org/search/?q={}&format=geojson&polygon_geojson=1'.format(urlescaped_place)
-    return gp.read_file(search_url)
+    search_url = ('https://nominatim.openstreetmap.org/search/?q={}' +
+                  '&format=geojson&polygon_geojson=1').format(urlescaped_place)
+    return gpd.read_file(search_url)
 
 
+def nth(xs, n, default=None):
+    '''
+    Wraps list access to return `default` instead of returning an `ItemError`
+    when accessing out-of-bounds elements. `default` is `None` when not
+    explicitly given.
+    '''
+    try:
+        return xs[n]
+    except IndexError:
+        return default
+
+    
+def plot_all(items, extra_kwargs=[]):
+    '''
+    Returns a plot containing all of the geometries in `items`.
+    If an `item` does not contain a `plot` method, a GeoSeries will be
+    constructed from it.
+    
+    The parameter `extra_kwargs` can contain extra keyword arguments that are
+    passed to matplotlib for the given item.
+    '''
+    ax = None
+    for idx, item in enumerate(items):
+        if 'plot' not in dir(item):
+            item = gpd.GeoSeries(item)
+        
+        kwargs = nth(extra_kwargs, idx, {})
+        if not ax:
+            ax = item.plot(**kwargs)
+        else:
+            item.plot(ax=ax, **kwargs)
+    
+    
+def scihub_product_ids(geodataframe):
+    '''
+    Returns the product ids of items in a GeoDataFrame returned by
+    `sentinelsat.to_geodataframe` as expected by `sentinelsat.download` and
+    `sentinelsat.download_all`.
+    '''
+    return [link.split('Products(\'')[-1].split('\')/$value')[0] for link in geodataframe['link'].values]
+
+
+def scihub_band_paths(p, bands, resolution=None):
+    '''
+    Given a zip file or folder at `p`, returns the paths inside p to the raster files containing
+    information for the given bands. Because some bands are available in more than one
+    resolution, this can be filtered by prodiding a third parameter (e.g. resolution='10m').
+    
+    `p` can be a string or a pathlib.Path.
+    `bands` can be a list of bands or a single band.
+   
+    The returned paths are formatted in the zip scheme as per Apache Commons VFS if necessary
+    and can be directly opened by rasterio.
+    '''
+    if type(bands) != list:
+        # allow passing in a single band more easily
+        bands = [bands]
+    
+    p = Path(p) # make sure we're dealing with a pathlib.Path
+    if p.suffix == '.zip':
+        # when dealing with zip files we have to read the filenames from the
+        # archive first
+        with zipfile.ZipFile(p) as f:
+            files = f.namelist()
+            rasters = [f for f in files if f.endswith('.jp2')]
+    else:
+        rasters = p.glob('**/*.jp2')
+    
+    # take only the paths that contain one of the given bands
+    rasters = [raster for band in bands for raster in rasters if band in raster]
+    
+    # if a resolution is given, further discard the bands we don't need
+    if resolution:
+        rasters = [raster for raster in rasters if resolution in raster]
+
+    if p.suffix == '.zip':
+        # we have to reformat the paths to 
+        rasters = [f'zip+file://{p}!/{r}' for r in rasters]
+    
+    return rasters
+
+
+def scihub_bgr_paths(raster_path, resolution=None):
+    '''
+    A convenence function to return the paths to the blue, green and red bands
+    in the downloaded product at `raster_path`.
+    '''
+    return scihub_band_paths(raster_path, ['B02', 'B03', 'B04'], resolution)
+
+
+def scihub_normalize_range(v):
+    return np.clip(v, 0, 2000) / 2000
+
+ 
+
 def reproject_raster_image(src, dst, target_crs):
     '''
     Reprojects `src` into `dst`, given a coordinate reference system `target_crs`.