Merge pull request #61 from chrieke/enable_simpler_landcover_customiz…

…ation

Enable simpler landcover customization

README.md

@@ -51,6 +51,8 @@ pip install prettymapp
 
 **Define the area, download and plot the OSM data:**
 
+You can select from 4 [predefined styles](prettymapp/settings.py#L35): `Peach`, `Auburn`, `Citrus` and `Flannel`.
+
 ```python
 from prettymapp.geo import get_aoi
 from prettymapp.osm import get_osm_geometries
@@ -63,7 +65,7 @@ df = get_osm_geometries(aoi=aoi)
 fig = Plot(
     df=df,
     aoi_bounds=aoi.bounds,
-    draw_settings=STYLES["Peach"]
+    draw_settings=STYLES["Peach"],
 ).plot_all()
 
 fig.savefig("map.jpg")
@@ -79,6 +81,38 @@ aoi_bounds = df.total_bounds
 ...
 ```
 
-To customize the map appearance, use the additional arguments of the [`Plot`](plotting.py#L36) class (e.g. `shape`, 
-`contour_width` etc.). Check the preconfigured [styles](prettymapp/settings.py#L35) and 
-webapp [examples](streamlit-prettymapp/examples.json) for inspiration.
+**Customize styles & layers**
+
+Edit the `draw_settings` input to create your own custom styles! The map layout can be further customized with the additional arguments of the [`Plot`](plotting.py#L36) class (e.g. `shape`, `contour_width` etc.). Check the webapp [examples](streamlit-prettymapp/examples.json) for inspiration.
+
+```
+from prettymapp.settings import STYLES
+
+custom_style = STYLES["Peach"].copy()
+custom_style["urban"] = {
+    "cmap": ["#3452eb"],
+    "ec": "#E9724C",
+    "lw": 0.2,
+    "zorder": 4,
+}
+
+fig = Plot(
+    df=df,
+    aoi_bounds=aoi.bounds,
+    draw_settings=custom_style,
+    shape="circle",
+    contour_width=0,
+).plot_all()
+
+```
+
+You can also customize the selection of OSM landcover classes that should be displayed.
+
+```
+from prettymapp.settings import LANDCOVER_CLASSES
+
+custom_lc_classes = LANDCOVER_CLASSES.copy()
+custom_lc_classes["urban"]["building"] = False
+
+df = get_osm_geometries(aoi=aoi, landcover_classes=custom_lc_classes)
+```

prettymapp/geo.py

@@ -54,8 +54,7 @@ def get_aoi(
     df = GeoDataFrame(
         DataFrame([0], columns=["id"]), crs="EPSG:4326", geometry=[Point(lon, lat)]
     )
-    utm_crs = df.estimate_utm_crs()
-    df = df.to_crs(utm_crs)
+    df = df.to_crs(df.estimate_utm_crs())
     df.geometry = df.geometry.buffer(radius)
     df = df.to_crs(crs=4326)
     poly = df.iloc[0].geometry

prettymapp/osm.py

@@ -7,18 +7,21 @@
 from shapely.geometry import Polygon
 
 from prettymapp.geo import explode_multigeometries
-from prettymapp.settings import LC_SETTINGS
+from prettymapp.settings import LANDCOVER_CLASSES
 
 settings.use_cache = True
 settings.log_console = False
 
 
-def get_osm_tags():
+def get_osm_tags(landcover_classes: dict = LANDCOVER_CLASSES):
     """
     Get relevant OSM tags for use with prettymapp
+    
+    Args:
+        landcover_classes: Landcover selection settings, defaults to prettymapp.settings.LANDCOVER_CLASSES
     """
     tags: dict = {}
-    for d in LC_SETTINGS.values():  # type: ignore
+    for d in landcover_classes.values():  # type: ignore
         for k, v in d.items():  # type: ignore
             try:
                 tags.setdefault(k, []).extend(v)
@@ -27,9 +30,16 @@ def get_osm_tags():
     return tags
 
 
-def cleanup_osm_df(df: GeoDataFrame, aoi: Union[Polygon, None] = None) -> GeoDataFrame:
+def cleanup_osm_df(
+    df: GeoDataFrame, aoi: Union[Polygon, None] = None, landcover_classes: dict = LANDCOVER_CLASSES
+) -> GeoDataFrame:
     """
     Cleanup of queried osm geometries to relevant level for use with prettymapp
+    
+    Args:
+        df: GeoDataFrame with queried OSM geometries
+        aoi: Optional geographic boundary to filter elements
+        landcover_classes: Landcover selection settings, defaults to prettymapp.settings.LANDCOVER_CLASSES
     """
     df = df.droplevel(level=0)
     df = df[~df.geometry.geom_type.isin(["Point", "MultiPoint"])]
@@ -38,7 +48,7 @@ def cleanup_osm_df(df: GeoDataFrame, aoi: Union[Polygon, None] = None) -> GeoDat
     df = explode_multigeometries(df)
 
     df["landcover_class"] = None
-    for lc_class, osm_tags in LC_SETTINGS.items():
+    for lc_class, osm_tags in landcover_classes.items():
         tags_in_columns = list(set(osm_tags.keys()).intersection(list(df.columns)))  # type: ignore
         mask_lc_class = df[tags_in_columns].notna().sum(axis=1) != 0
         # Remove mask elements that belong to other subtag
@@ -60,30 +70,34 @@ def cleanup_osm_df(df: GeoDataFrame, aoi: Union[Polygon, None] = None) -> GeoDat
     return df
 
 
-def get_osm_geometries(aoi: Polygon) -> GeoDataFrame:
+def get_osm_geometries(
+    aoi: Polygon, landcover_classes: dict = LANDCOVER_CLASSES
+) -> GeoDataFrame:
     """
     Query OSM features within a polygon geometry.
 
     Args:
         aoi: Polygon geometry query boundary.
+        landcover_classes: Landcover selection settings, defaults to prettymapp.settings.LANDCOVER_CLASSES
     """
-    tags = get_osm_tags()
+    tags = get_osm_tags(landcover_classes=landcover_classes)
     df = features_from_polygon(polygon=aoi, tags=tags)
     df = cleanup_osm_df(df, aoi)
     return df
 
 
 def get_osm_geometries_from_xml(
-    filepath: Union[str, Path], aoi: Union[Polygon, None] = None
+    filepath: Union[str, Path], aoi: Union[Polygon, None] = None, landcover_classes: dict = LANDCOVER_CLASSES
 ) -> GeoDataFrame:
     """
     Query OSM features in an OSM-formatted XML file.
 
     Args:
         filepath: path to file containing OSM XML data
         aoi: Optional geographic boundary to filter elements
+        landcover_classes: Landcover selection settings, defaults to prettymapp.settings.LANDCOVER_CLASSES
     """
-    tags = get_osm_tags()
+    tags = get_osm_tags(landcover_classes=landcover_classes)
     df = features_from_xml(filepath, polygon=aoi, tags=tags)
     df = cleanup_osm_df(df, aoi)
     return df

prettymapp/plotting.py

@@ -3,6 +3,7 @@
 from typing import Tuple, List
 from dataclasses import dataclass
 
+from dataclasses import field
 from geopandas.plotting import _plot_polygon_collection, _plot_linestring_collection
 from geopandas import GeoDataFrame
 import numpy as np
@@ -12,7 +13,7 @@
 from matplotlib.patches import Ellipse
 import matplotlib.patheffects as PathEffects
 
-from prettymapp.settings import STREETS_WIDTH
+from prettymapp.settings import STREETS_WIDTH, STYLES
 
 
 def adjust_lightness(color: str, amount: float = 0.5) -> Tuple[float, float, float]:
@@ -34,21 +35,27 @@ def adjust_lightness(color: str, amount: float = 0.5) -> Tuple[float, float, flo
 
 @dataclass
 class Plot:
+    """
+    Main plotting class for prettymapp.
+    """
     df: GeoDataFrame
     aoi_bounds: List[
         float
     ]  # Not df bounds as could lead to weird plot shapes with unequal geometry distribution.
-    draw_settings: dict
+    draw_settings: dict = field(default_factory=lambda: STYLES["Peach"])
+    # Map layout settings
     shape: str = "circle"
     contour_width: int = 0
     contour_color: str = "#2F3537"
+    # Optional map text settings e.g. to display location name
     name_on: bool = False
     name: str = "some name"
     font_size: int = 25
     font_color: str = "#2F3737"
     text_x: int = 0
     text_y: int = 0
     text_rotation: int = 0
+    # Map background settings
     bg_shape: str = "rectangle"
     bg_buffer: int = 2
     bg_color: str = "#F2F4CB"

prettymapp/settings.py

@@ -1,4 +1,4 @@
-LC_SETTINGS = {
+LANDCOVER_CLASSES = {
     "urban": {"building": True, "landuse": ["construction", "commercial"]},
     "water": {
         "natural": ["water", "bay"],
@@ -30,10 +30,9 @@
     "other": {"amenity": ["parking"], "man_made": ["pier"], "highway": ["pedestrian"]},
 }
 
-# Macau peach
-# Barcelona auburn
+# Contains drawing settings
 STYLES = {
-    "Peach": {
+    "Peach": { # e.g. Macau
         "urban": {
             "cmap": ["#FFC857", "#E9724C", "#C5283D"],
             "ec": "#2F3737",
@@ -53,7 +52,7 @@
         "streets": {"fc": "#2F3737", "zorder": 3},
         "other": {"fc": "#F2F4CB", "ec": "#2F3737", "lw": 1, "zorder": 3},
     },
-    "Auburn": {
+    "Auburn": { # e.g. Barcelona
         "urban": {
             "cmap": ["#433633", "#FF5E5B", "#FF5E5B"],
             "ec": "#2F3737",
@@ -80,7 +79,7 @@
         "streets": {"fc": "#2F3737", "zorder": 4},
         "other": {"fc": "#F2F4CB", "ec": "#2F3737", "lw": 1, "zorder": 3},
     },
-    "Citrus": {
+    "Citrus": { # e.g. Würzburg
         "urban": {
             "cmap": ["#FFFF3F", "#F4D58D", "#F5CB5C"],
             "ec": "#2F3737",
@@ -105,7 +104,7 @@
         "streets": {"fc": "#FFFFFF", "zorder": 4},
         "other": {"fc": "#EAE2B7", "ec": "#2F3737", "lw": 1, "zorder": 3},
     },
-    "Flannel": {
+    "Flannel": { # e.g. Heerhugowaard
         "urban": {
             "cmap": ["#433633", "#FF5E5B", "#FF5E5B"],
             "ec": "#2F3737",