Merge branch 'master' of https://github.com/geopandas/contextily

Dockerfile

@@ -1,7 +1,7 @@
 FROM darribas/gds_py:4.1
 
 # Install contextily master
-RUN pip install -U git+https://github.com/geopandas/contextily.git@master
+RUN pip install -U earthengine-api git+https://github.com/geopandas/contextily.git@master
 # Add notebooks
 RUN rm -R work/
 COPY ./README.md ${HOME}/README.md

contextily/__init__.py

@@ -8,4 +8,4 @@
 from .tile import *
 from .plotting import add_basemap, add_attribution
 
-__version__ = "1.0.0"
+__version__ = "1.0.1"

contextily/place.py

@@ -2,12 +2,17 @@
 import geopy as gp
 import numpy as np
 import matplotlib.pyplot as plt
-from warnings import warn
+import warnings
+
 from .tile import howmany, bounds2raster, bounds2img, _sm2ll, _calculate_zoom
 from .plotting import INTERPOLATION, ZOOM, add_attribution
 from . import providers
 from ._providers import TileProvider
 
+# Set user ID for Nominatim
+_val = np.random.randint(1000000)
+_default_user_agent = f"contextily_user_{_val}"
+
 
 class Place(object):
     """Geocode a place by name and get its map.
@@ -45,6 +50,8 @@ class Place(object):
         Source url for web tiles, or path to local file. If
         local, the file is read with `rasterio` and all
         bands are loaded into the basemap.
+    geocoder : geopy.geocoders
+        [Optional. Default: geopy.geocoders.Nominatim()] Geocoder method to process `search`
 
     Attributes
     ----------
@@ -69,7 +76,14 @@ class Place(object):
     """
 
     def __init__(
-        self, search, zoom=None, path=None, zoom_adjust=None, source=None, url=None
+        self,
+        search,
+        zoom=None,
+        path=None,
+        zoom_adjust=None,
+        source=None,
+        url=None,
+        geocoder=gp.geocoders.Nominatim(user_agent=_default_user_agent),
     ):
         self.path = path
         if url is not None and source is None:
@@ -93,7 +107,7 @@ def __init__(
         self.zoom_adjust = zoom_adjust
 
         # Get geocoded values
-        resp = gp.geocoders.Nominatim().geocode(search)
+        resp = geocoder.geocode(search)
         bbox = np.array([float(ii) for ii in resp.raw["boundingbox"]])
 
         if "display_name" in resp.raw.keys():
@@ -240,7 +254,7 @@ def plot_map(
     ax : instance of matplotlib Axes object or None
         The axis on the map is plotted.
     """
-    warn(
+    warnings.warn(
         (
             "The method `plot_map` is deprecated and will be removed from the"
             " library in future versions. Please use either `add_basemap` or"

contextily/plotting.py

@@ -146,6 +146,10 @@ def add_basemap(
         # Warping
         if crs is not None:
             image, extent = warp_tiles(image, extent, t_crs=crs, resampling=resampling)
+        # Check if overlay
+        if _is_overlay(source) and 'zorder' not in extra_imshow_args:
+            # If zorder was not set then make it 9 otherwise leave it
+            extra_imshow_args['zorder'] = 9
     # If local source
     else:
         import rasterio as rio
@@ -177,18 +181,21 @@ def add_basemap(
                     }
                 ]
                 image, img_transform = riomask(raster, window, crop=True)
+                extent = left, right, bottom, top
             else:
                 # Read full
                 image = np.array([band for band in raster.read()])
                 img_transform = raster.transform
+                bb = raster.bounds
+                extent = bb.left, bb.right, bb.bottom, bb.top 
             # Warp
             if (crs is not None) and (raster.crs != crs):
-                image, raster = _warper(
+                image, bounds, _ = _warper(
                     image, img_transform, raster.crs, crs, resampling
                 )
+                extent = bounds.left, bounds.right, bounds.bottom, bounds.top
             image = image.transpose(1, 2, 0)
-            bb = raster.bounds
-            extent = bb.left, bb.right, bb.bottom, bb.top
+
     # Plotting
     if image.shape[2] == 1:
         image = image[:, :, 0]
@@ -222,6 +229,44 @@ def _reproj_bb(left, right, bottom, top, s_crs, t_crs):
     n_l, n_b, n_r, n_t = transform_bounds(s_crs, t_crs, left, bottom, right, top)
     return n_l, n_r, n_b, n_t
 
+def _is_overlay(source):
+    """
+    Check if the identified source is an overlay (partially transparent) layer.
+
+    Parameters
+    ----------
+    source : dict
+        The tile source: web tile provider.  Must be preprocessed as
+        into a dictionary, not just a string.
+
+    Returns
+    -------
+    bool
+
+    Notes
+    -----
+    This function is based on a very similar javascript version found in leaflet:
+    https://github.com/leaflet-extras/leaflet-providers/blob/9eb968f8442ea492626c9c8f0dac8ede484e6905/preview/preview.js#L56-L70
+    """
+    if not isinstance(source, dict):
+        return False
+    if source.get('opacity', 1.0) < 1.0:
+        return True
+    overlayPatterns = [
+        '^(OpenWeatherMap|OpenSeaMap)',
+        'OpenMapSurfer.(Hybrid|AdminBounds|ContourLines|Hillshade|ElementsAtRisk)',
+        'Stamen.Toner(Hybrid|Lines|Labels)',
+        'CartoDB.(Positron|DarkMatter|Voyager)OnlyLabels',
+        'Hydda.RoadsAndLabels',
+        '^JusticeMap',
+        'OpenPtMap',
+        'OpenRailwayMap',
+        'OpenFireMap',
+        'SafeCast'
+    ]
+    import re
+    return bool(re.match('(' + '|'.join(overlayPatterns) + ')', source.get('name', '')))
+
 
 def add_attribution(ax, text, font_size=ATTRIBUTION_SIZE, **kwargs):
     """

contextily/tile.py

@@ -302,7 +302,7 @@ def _construct_tile_url(provider, x, y, z):
 def _fetch_tile(tile_url, wait, max_retries):
     request = _retryer(tile_url, wait, max_retries)
     with io.BytesIO(request.content) as image_stream:
-        image = Image.open(image_stream).convert("RGB")
+        image = Image.open(image_stream).convert("RGBA")
         array = np.asarray(image)
         image.close()
     return array
@@ -349,11 +349,11 @@ def warp_tiles(img, extent, t_crs="EPSG:4326", resampling=Resampling.bilinear):
     resY = (y[-1] - y[0]) / h
     transform = from_origin(x[0] - resX / 2, y[-1] + resY / 2, resX, resY)
     # ---
-    w_img, vrt = _warper(
+    w_img, bounds, _ = _warper(
         img.transpose(2, 0, 1), transform, "EPSG:3857", t_crs, resampling
     )
     # ---
-    extent = vrt.bounds.left, vrt.bounds.right, vrt.bounds.bottom, vrt.bounds.top
+    extent = bounds.left, bounds.right, bounds.bottom, bounds.top
     return w_img.transpose(1, 2, 0), extent
 
 
@@ -392,13 +392,13 @@ def warp_img_transform(img, transform, s_crs, t_crs, resampling=Resampling.bilin
         Transform of the input image as expressed by `rasterio` and
         the `affine` package
     """
-    w_img, vrt = _warper(img, transform, s_crs, t_crs, resampling)
-    return w_img, vrt.transform
+    w_img, _, w_transform = _warper(img, transform, s_crs, t_crs, resampling)
+    return w_img, w_transform
 
 
 def _warper(img, transform, s_crs, t_crs, resampling):
     """
-    Warp an image returning it as a virtual file
+    Warp an image. Returns the warped image and updated bounds and transform.
     """
     b, h, w = img.shape
     with MemoryFile() as memfile:
@@ -411,12 +411,15 @@ def _warper(img, transform, s_crs, t_crs, resampling):
             crs=s_crs,
             transform=transform,
         ) as mraster:
-            for band in range(b):
-                mraster.write(img[band, :, :], band + 1)
-            # --- Virtual Warp
-            vrt = WarpedVRT(mraster, crs=t_crs, resampling=resampling)
-            img = vrt.read()
-    return img, vrt
+            mraster.write(img)
+
+        with memfile.open() as mraster:
+            with WarpedVRT(mraster, crs=t_crs, resampling=resampling) as vrt:
+                img = vrt.read()
+                bounds = vrt.bounds
+                transform = vrt.transform
+
+    return img, bounds, transform
 
 
 def _retryer(tile_url, wait, max_retries):

docs/_static/css/custom.css

@@ -1,12 +1,15 @@
 /* Override some aspects of the pydata-sphinx-theme */
 
-body {
-  padding-top: 0px;
+:root {
+  --color-active-navigation: 0, 91, 129;
+  /* Use normal text color (like h3, ..) instead of primary color */
+  --color-h1: var(--color-text-base);
+  --color-h2: var(--color-text-base);
 }
 
-h1,
-h2 {
-  color: #333;
+
+body {
+  padding-top: 0px;
 }
 
 @media (min-width: 768px) {
@@ -22,22 +25,11 @@ code {
   color: #3b444b;
 }
 
-/* Default link color for active + larger font size for sidebar*/
+/* Larger font size for sidebar*/
 .bd-sidebar .nav > li > a {
   font-size: 1em;
 }
 
-.bd-sidebar .nav>li>a:hover,
-.bd-sidebar .nav > .active:hover > a,
-.bd-sidebar .nav > .active > a {
-  color: #005b81;
-}
-.toc-entry > .nav-link.active {
-  color: #005b81;
-  border-left:2px solid #005b81;
-}
-
-
 /* New element: brand text instead of logo */
 
 /* .navbar-brand-text {

docs/conf.py

@@ -70,6 +70,9 @@
     'css/custom.css',
 ]
 
+html_sidebars = {
+   '**': ['docs-sidebar.html'],
+}
 
 # ---------------------------------------------------------------------------
 

notebooks/working_with_local_files.ipynb

@@ -213,7 +213,7 @@
    "source": [
     "### Raster from name\n",
     "\n",
-    "The other option `contextily` includes to save rasters is through its Place API, which allows you to query locations through their names (thanks to [`geopy`](https://geopy.readthedocs.io/en/stable/)). For example, we can retrieve a basemap of Sao Paulo:"
+    "The other option `contextily` includes to save rasters is through its Place API, which allows you to query locations through their names (thanks to [`geopy`](https://geopy.readthedocs.io/en/stable/)). For example, we can retrieve a basemap of Cape Town:"
    ]
   },
   {
@@ -245,8 +245,8 @@
     }
    ],
    "source": [
-    "sao_paulo = ctx.Place(\"Cape Town\", source=ctx.providers.Wikimedia)\n",
-    "sao_paulo.plot()"
+    "cape_town = ctx.Place(\"Cape Town\", source=ctx.providers.Wikimedia)\n",
+    "cape_town.plot()"
    ]
   },
   {
@@ -262,7 +262,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "sao_paulo = ctx.Place(\"Cape Town\", source=ctx.providers.Wikimedia, path=\"cape_town.tif\")"
+    "cape_town = ctx.Place(\"Cape Town\", source=ctx.providers.Wikimedia, path=\"cape_town.tif\")"
    ]
   },
   {

setup.py

@@ -10,7 +10,7 @@
 
 setup(
     name="contextily",
-    version="1.0.0",
+    version="1.0.1",
     description="Context geo-tiles in Python",
     long_description=long_description,
     long_description_content_type="text/markdown",
@@ -28,6 +28,7 @@
         "Programming Language :: Python :: 3.7",
         "Programming Language :: Python :: 3 :: Only",
         "Programming Language :: Python :: Implementation :: CPython",
+        "Framework :: Matplotlib",
     ],
     python_requires=">=3.6",
     install_requires=install_requires,