Python feature.NaturalEarthFeature方法代码示例

# 需要导入模块: from cartopy import feature [as 别名]
# 或者: from cartopy.feature import NaturalEarthFeature [as 别名]
def map_unique_events(cat, catname, mids):
    """Map unassociated events from a catalog."""
    if len(mids) == len(cat):
        return

    cat = cat[~cat['id'].isin(mids)].reset_index(drop=True)
    lllat, lllon, urlat, urlon, _, _, _, clon = qcu.get_map_bounds(cat)

    plt.figure(figsize=(12, 7))
    mplmap = plt.axes(projection=ccrs.PlateCarree(central_longitude=clon))
    mplmap.coastlines('50m')
    mplmap.scatter(cat['longitude'].tolist(), cat['latitude'].tolist(),
                   color='r', s=2, zorder=4, transform=ccrs.PlateCarree())
    mplmap.gridlines(crs=ccrs.PlateCarree(), draw_labels=True,
                     linewidth=1, color='gray', alpha=0.5, linestyle='--')
    mplmap.add_feature(cfeature.NaturalEarthFeature('cultural',
        'admin_1_states_provinces_lines', '50m', facecolor='none',
        edgecolor='k', zorder=9))
    mplmap.add_feature(cfeature.BORDERS)
    plt.title('%s unassociated events' % catname, fontsize=20, y=1.08)    
    #print(catname)
    plt.savefig('%s_uniquedetecs.png' % catname, dpi=300)
    plt.close() 

# 需要导入模块: from cartopy import feature [as 别名]
# 或者: from cartopy.feature import NaturalEarthFeature [as 别名]
def countries(**kwargs):
    params = {
        "category": "cultural",
        "name": "admin_0_countries",
        "scale": "10m",
        "edgecolor": "#524c50",
        "facecolor": "none",
        "alpha": 0.5,
        **kwargs,
    }
    return NaturalEarthFeature(**params) 

# 需要导入模块: from cartopy import feature [as 别名]
# 或者: from cartopy.feature import NaturalEarthFeature [as 别名]
def rivers(**kwargs):
    params = {
        "category": "physical",
        "name": "rivers_lake_centerlines",
        "scale": "10m",
        "edgecolor": "#226666",
        "facecolor": "none",
        "alpha": 0.2,
        **kwargs,
    }
    return NaturalEarthFeature(**params) 

# 需要导入模块: from cartopy import feature [as 别名]
# 或者: from cartopy.feature import NaturalEarthFeature [as 别名]
def lakes(**kwargs):
    params = {
        "category": "physical",
        "name": "lakes",
        "scale": "10m",
        "edgecolor": "#226666",
        "facecolor": "#226666",
        "alpha": 0.2,
        **kwargs,
    }
    return NaturalEarthFeature(**params) 

# 需要导入模块: from cartopy import feature [as 别名]
# 或者: from cartopy.feature import NaturalEarthFeature [as 别名]
def ocean(**kwargs):
    params = {
        "category": "physical",
        "name": "ocean",
        "scale": "10m",
        "edgecolor": "#226666",
        "facecolor": "#226666",
        "alpha": 0.2,
        **kwargs,
    }
    return NaturalEarthFeature(**params) 

# 需要导入模块: from cartopy import feature [as 别名]
# 或者: from cartopy.feature import NaturalEarthFeature [as 别名]
def map_events(cat1, cat1name, cat2, cat2name, cat1mids, cat2mids, dirname):
    """Map matching events between catalogs."""
    if len(cat1mids) == 0:
        return

    lllat, lllon, urlat, urlon, _, _, _, clon = qcu.get_map_bounds(cat1, cat2)

    cat1lons, cat1lats, cat2lons, cat2lats = [], [], [], []
    for i, mid in enumerate(cat1mids):
        cat1lons.append(cat1[cat1['id'] == mid]['longitude'].get_values()[0])
        cat1lats.append(cat1[cat1['id'] == mid]['latitude'].get_values()[0])
        cat2lons.append(cat2[cat2['id'] == cat2mids[i]]['longitude'
                            ].get_values()[0])
        cat2lats.append(cat2[cat2['id'] == cat2mids[i]]['latitude'
                            ].get_values()[0])

    plt.figure(figsize=(12, 7))
    mplmap = plt.axes(projection=ccrs.PlateCarree(central_longitude=clon))
    mplmap.set_extent([lllon, urlon, lllat, urlat], ccrs.PlateCarree())
    mplmap.coastlines('50m')
    mplmap.gridlines(crs=ccrs.PlateCarree(), draw_labels=True,
                     linewidth=1, color='gray', alpha=0.5, linestyle='--')

    for i, lat in enumerate(cat1lats):
        mplmap.plot([cat1lons[i], cat2lons[i]], [lat, cat2lats[i]],
                    color='k', transform=ccrs.PlateCarree())

    mplmap.scatter(cat1lons, cat1lats, color='b', s=2, zorder=4,
                   transform=ccrs.PlateCarree(), label=cat1name)
    mplmap.scatter(cat2lons, cat2lats, color='r', s=2, zorder=4,
                   transform=ccrs.PlateCarree(), label=cat2name)
    mplmap.add_feature(cfeature.NaturalEarthFeature('cultural',
        'admin_1_states_provinces_lines', '50m', facecolor='none',
        edgecolor='k', zorder=9))
    mplmap.add_feature(cfeature.BORDERS)
    plt.legend()

    plt.savefig('%s_mapmatcheddetecs.png' % dirname, dpi=300)
    plt.close() 

# 需要导入模块: from cartopy import feature [as 别名]
# 或者: from cartopy.feature import NaturalEarthFeature [as 别名]
def plot_lonlat_map(ax, lon, lat, data, transform, extend=None, cmap="CN_ref", bounds=np.arange(-5,76,5),
                    cbar=True, orientation="vertical",cbar_ticks=None, cbar_ticklabels=None, **kwargs):
    """
    :param ax:cartopy.mpl.geoaxes.GeoAxesSubplot, it should get from cartopy, eg:plt.axes(projection=ccrs.PlateCarree())
    :param lon: lon mesh grid for data units: degree
    :param lat: lat mesh grid for data units: degree
    :param data: radar data ,dims like lat, lon
    :param transform: The transform argument to plotting functions tells Cartopy what coordinate system your data are defined in.
    :param extend: (min_lon, max_lon, min_lat, max_lat), Latitude and longitude range, units:degrees
    :param cmap: str or Colormap, optional, A Colormap instance or registered colormap name. to see cm.py!
    :param min_max: The colorbar range(vmin, vmax). If None, suitable min/max values are automatically chosen by min max of data!
    :param cmap_bins:bins of cmaps, int
    :param cbar: bool, if True, plot with colorbar,
    :param orientation: vertical or horizontal, it is vaild when cbar is True
    :param kwargs: kwargs: other arguments for pcolormesh!
    :return:  pcolor result
    """
    assert isinstance(ax, cartopy.mpl.geoaxes.GeoAxesSubplot), "axes is not cartopy axes!"
    if extend is None:
        min_lon = np.min(lon)
        max_lon = np.max(lon)
        min_lat = np.min(lat)
        max_lat = np.max(lat)
    else:
        min_lon, max_lon, min_lat, max_lat = extend

    ax.set_aspect("equal")
    cmaps = plt.get_cmap(cmap)
    norm = BoundaryNorm(bounds, ncolors=cmaps.N, clip=True)
    pm = ax.pcolormesh(lon, lat, data, transform=transform, cmap=cmap, norm=norm, zorder=4, **kwargs)
    ax.add_feature(cfeature.OCEAN.with_scale('50m'), zorder=0)
    ax.add_feature(cfeature.NaturalEarthFeature('physical', 'land', '50m', \
                                                edgecolor='none', facecolor="white"), zorder=1)
    ax.add_feature(cfeature.LAKES.with_scale('50m'), zorder=2)
    ax.add_feature(cfeature.RIVERS.with_scale('50m'), zorder=3)

    ax.add_feature(cfeature.ShapelyFeature(CN_shp_info.geometries(), transform, \
                                           edgecolor='k', facecolor='none'), linewidth=0.5, \
                   linestyle='-', zorder=5, alpha=0.8)
    parallels = np.arange(int(min_lat), np.ceil(max_lat) + 1, 1)
    meridians = np.arange(int(min_lon), np.ceil(max_lon) + 1, 1)
    ax.set_xticks(meridians, crs=transform)
    ax.set_yticks(parallels, crs=transform)
    lon_formatter = LongitudeFormatter()
    lat_formatter = LatitudeFormatter()
    ax.xaxis.set_major_formatter(lon_formatter)
    ax.yaxis.set_major_formatter(lat_formatter)
    if cbar:
        cb = plt.colorbar(mappable=pm, ax=ax, orientation=orientation)
        if cbar_ticks is None:
            ticks = bounds
        else:
            ticks = cbar_ticks
        cb.set_ticks(ticks)

    if cbar_ticklabels is not None:
        if orientation == "vertical":
            cb.ax.set_yticklabels(cbar_ticklabels)
        else:
            cb.ax.set_xticklabels(cbar_ticklabels)
    return pm