Matplotlib Integration

class GeoAxes:
    """Matplotlib axes subclass for cartographic projections."""
    def __init__(self, fig, rect, projection, **kwargs): ...
    
    # Extent and boundaries
    def set_global(self): ...
    def set_extent(self, extents, crs=None): ...
    @property
    def extent(self): ...
    
    # Geographic features
    def add_feature(self, feature, **kwargs): ...
    def coastlines(self, resolution='auto', color='black', **kwargs): ...
    def stock_img(self): ...
    
    # Gridlines and labels
    def gridlines(self, crs=None, draw_labels=False, **kwargs): ...
    
    # Coordinate transformations
    def transform_point(self, x, y, src_crs): ...
    def transform_points(self, src_crs, x, y, z=None): ...
    
    # Plotting with transformations
    def plot(self, *args, transform=None, **kwargs): ...
    def scatter(self, x, y, transform=None, **kwargs): ...
    def contour(self, x, y, z, transform=None, **kwargs): ...
    def contourf(self, x, y, z, transform=None, **kwargs): ...
    def pcolormesh(self, x, y, z, transform=None, **kwargs): ...
    def quiver(self, x, y, u, v, transform=None, **kwargs): ...
    def streamplot(self, x, y, u, v, transform=None, **kwargs): ...
    def imshow(self, img, extent=None, transform=None, **kwargs): ...
    
    # Tissot's indicatrix
    def tissot(self, rad_km, lons, lats, n_samples=80, **kwargs): ...
    
    # Web map tiles
    def add_image(self, tile_source, level, **kwargs): ...
    def add_wmts(self, wmts, layer_name, **kwargs): ...
    def add_wms(self, wms, layers, **kwargs): ...
    def add_raster(self, raster_source, **kwargs): ...
    
    # Background and stock imagery
    def background_img(self, name='ne_shaded', resolution='low', extent=None, cache=False): ...
    def stock_img(self): ...
    
    # View and coordinate utilities
    def autoscale_view(self, tight=None, scalex=True, scaley=True): ...
    def format_coord(self, x, y): ...
    def get_tightbbox(self, renderer, call_axes_locator=True, bbox_extra_artists=None): ...

class Gridliner:
    """Grid line and label management for GeoAxes."""
    def __init__(self, axes, crs, draw_labels=False, **kwargs): ...
    
    # Style properties
    xlabel_style: dict  # X-axis label styling
    ylabel_style: dict  # Y-axis label styling
    xlines: bool        # Whether to draw longitude lines
    ylines: bool        # Whether to draw latitude lines
    xlabels_top: bool   # Top longitude labels
    xlabels_bottom: bool # Bottom longitude labels  
    ylabels_left: bool  # Left latitude labels
    ylabels_right: bool # Right latitude labels
    
    # Locators and formatters
    xlocator: Any       # Longitude tick locator
    ylocator: Any       # Latitude tick locator
    xformatter: Any     # Longitude label formatter
    yformatter: Any     # Latitude label formatter

class Label:
    """Individual grid label representation."""
    def __init__(self, x, y, text, **kwargs): ...
    @property
    def x(self): ...
    @property  
    def y(self): ...
    @property
    def text(self): ...

class LatitudeFormatter:
    """Format latitude tick labels with N/S indicators."""
    def __init__(self, degree_symbol='°', number_format='g', 
                 southern_hemisphere='S', northern_hemisphere='N'): ...
    def __call__(self, value, pos=None): ...

class LongitudeFormatter:
    """Format longitude tick labels with E/W indicators."""
    def __init__(self, degree_symbol='°', number_format='g',
                 eastern_hemisphere='E', western_hemisphere='W',
                 dateline_direction_label=False, zero_direction_label=False): ...
    def __call__(self, value, pos=None): ...

class LatitudeLocator:
    """Locate latitude tick positions."""
    def __init__(self, nbins='auto'): ...
    def tick_values(self, vmin, vmax): ...

class LongitudeLocator:
    """Locate longitude tick positions."""
    def __init__(self, nbins='auto'): ...  
    def tick_values(self, vmin, vmax): ...

def shapely_to_path(shape):
    """
    Convert shapely geometry to matplotlib path.
    
    Parameters:
    - shape: shapely geometry
    
    Returns:
    matplotlib.path.Path
    """

def path_to_shapely(path):
    """
    Convert matplotlib path to shapely geometry.
    
    Parameters:
    - path: matplotlib.path.Path
    
    Returns:
    shapely geometry
    """

def geos_to_path(shape):
    """
    Convert GEOS geometry to matplotlib path.
    
    Parameters:
    - shape: GEOS geometry
    
    Returns:
    matplotlib.path.Path
    """

class FeatureArtist:
    """Artist for rendering cartopy features."""
    def __init__(self, feature, **kwargs): ...
    def draw(self, renderer): ...
    
class SlippyImageArtist:
    """Artist for rendering slippy map tiles."""
    def __init__(self, tile_source, **kwargs): ...
    def draw(self, renderer): ...

class GeoQuadMesh:
    """Geographic quadrilateral mesh for pcolormesh plots."""
    def __init__(self, x, y, **kwargs): ...

class GeoContourSet:
    """Geographic contour set with projection awareness."""
    def __init__(self, ax, *args, **kwargs): ...

import matplotlib.pyplot as plt
import cartopy.crs as ccrs
import cartopy.feature as cfeature

# Create figure with GeoAxes
fig = plt.figure(figsize=(12, 8))
ax = plt.axes(projection=ccrs.PlateCarree())

# Set up map
ax.set_global()
ax.add_feature(cfeature.LAND)
ax.add_feature(cfeature.OCEAN)
ax.coastlines()

# Add gridlines with labels
gl = ax.gridlines(draw_labels=True, dms=True, x_inline=False, y_inline=False)
gl.xlabel_style = {'size': 12, 'color': 'blue'}
gl.ylabel_style = {'size': 12, 'color': 'red'}

plt.title('World Map with Custom Gridlines')
plt.show()

import numpy as np
import matplotlib.pyplot as plt
import cartopy.crs as ccrs

# Sample data
lons = np.linspace(-180, 180, 360)
lats = np.linspace(-90, 90, 180)
lon_grid, lat_grid = np.meshgrid(lons, lats)
data = np.sin(np.radians(lat_grid)) * np.cos(np.radians(lon_grid))

# Plot with different projection
fig = plt.figure(figsize=(15, 10))

# PlateCarree data projection
ax1 = plt.subplot(2, 2, 1, projection=ccrs.PlateCarree())
ax1.contourf(lon_grid, lat_grid, data, transform=ccrs.PlateCarree())
ax1.coastlines()
ax1.set_title('PlateCarree Projection')

# Orthographic projection
ax2 = plt.subplot(2, 2, 2, projection=ccrs.Orthographic(-90, 45))
ax2.contourf(lon_grid, lat_grid, data, transform=ccrs.PlateCarree())
ax2.coastlines()
ax2.set_global()
ax2.set_title('Orthographic Projection')

plt.tight_layout()
plt.show()

import matplotlib.pyplot as plt
import cartopy.crs as ccrs
from cartopy.mpl.ticker import LongitudeFormatter, LatitudeFormatter

fig = plt.figure(figsize=(12, 8))
ax = plt.axes(projection=ccrs.PlateCarree())

# Add features
ax.coastlines()
ax.set_global()

# Custom gridlines with formatters
gl = ax.gridlines(draw_labels=True)
gl.xformatter = LongitudeFormatter(zero_direction_label=True)
gl.yformatter = LatitudeFormatter()
gl.xlabel_style = {'size': 10, 'rotation': 45}
gl.ylabel_style = {'size': 10}

plt.show()

import numpy as np
import matplotlib.pyplot as plt
import cartopy.crs as ccrs

# Create vector field data
lons = np.arange(-120, -60, 5)
lats = np.arange(25, 65, 5)
lon_grid, lat_grid = np.meshgrid(lons, lats)

# Sample wind field
u = 10 * np.sin(np.radians(lat_grid))
v = 5 * np.cos(np.radians(lon_grid))

fig = plt.figure(figsize=(12, 8))
ax = plt.axes(projection=ccrs.PlateCarree())

# Plot vector field
ax.quiver(lon_grid, lat_grid, u, v, transform=ccrs.PlateCarree(),
          regrid_shape=20, alpha=0.7)

# Add map features
ax.coastlines()
ax.add_feature(cfeature.BORDERS)
ax.set_extent([-125, -55, 20, 70])
ax.gridlines(draw_labels=True)

plt.title('Wind Vector Field')
plt.show()

import matplotlib.pyplot as plt
import cartopy.crs as ccrs
from cartopy.io import img_tiles

# Create map with OpenStreetMap tiles
fig = plt.figure(figsize=(12, 8))

# Use the same CRS as the tile source
osm_tiles = img_tiles.OSM()
ax = plt.axes(projection=osm_tiles.crs)

# Add tiles at zoom level 10
ax.add_image(osm_tiles, 10)

# Set extent for London
ax.set_extent([-0.2, 0.1, 51.4, 51.6])

# Add some data points
lons = [-0.1, 0.0, 0.05]
lats = [51.5, 51.52, 51.48]
ax.scatter(lons, lats, color='red', s=100, transform=ccrs.PlateCarree())

plt.title('London with OpenStreetMap Background')
plt.show()

import matplotlib.pyplot as plt
import cartopy.crs as ccrs

# Show projection distortion with Tissot's indicatrix
fig, axes = plt.subplots(1, 2, figsize=(15, 6),
                        subplot_kw={'projection': ccrs.PlateCarree()})

projections = [ccrs.PlateCarree(), ccrs.Mercator()]
titles = ['PlateCarree', 'Mercator']

for ax, proj, title in zip(axes, projections, titles):
    ax = plt.axes(projection=proj)
    ax.coastlines()
    ax.set_global()
    
    # Add Tissot's indicatrix circles
    ax.tissot(rad_km=1000, lons=range(-180, 181, 30), 
              lats=range(-90, 91, 30), alpha=0.5)
    
    ax.set_title(f'{title} - Tissot Indicatrix')

plt.tight_layout()
plt.show()

def merge(*style_dicts):
    """
    Merge matplotlib style dictionaries.
    
    Parameters:
    - *style_dicts: variable number of style dictionaries
    
    Returns:
    Merged style dictionary
    """

def finalize(style):
    """
    Finalize style dictionary for matplotlib use.
    
    Parameters:
    - style: dict, style parameters
    
    Returns:
    Finalized style dictionary
    """