### Install Frykit

Source: https://github.com/zhajiman/frykit/blob/main/README.md

Installs the frykit package, with an option to include map data for full functionality. It also shows how to update the package.

```bash
pip install frykit

# 需要地图数据
pip install frykit[data]

# 更新
pip install -U frykit
```

--------------------------------

### Plot World Base Map

Source: https://github.com/zhajiman/frykit/blob/main/README.md

Provides examples for plotting world base maps using `frykit.plot`. It shows how to add country borders and visualize land and ocean areas with specified fill colors.

```Python
# 画所有国家
fplt.add_countries(ax)

# 画海陆
fplt.add_land(ax, fc='floralwhite')
fplt.add_ocean(ax, fc='dodgerblue')
```

--------------------------------

### Read Chinese Administrative Boundaries

Source: https://github.com/zhajiman/frykit/blob/main/README.md

Demonstrates how to read various Chinese administrative boundaries using the `frykit.shp` module. It covers reading national borders, coastlines, provinces, cities, and districts, with examples of filtering by name or administrative code.

```Python
import frykit.shp as fshp

国界 = fshp.get_cn_border()
九段线 = fshp.get_cn_line()

所有省 = fshp.get_cn_province()
安徽省 = fshp.get_cn_province('安徽省')
安徽省, 江苏省 = fshp.get_cn_province(['安徽省', '江苏省'])

所有市 = fshp.get_cn_city()
合肥市 = fshp.get_cn_city('合肥市')
合肥市, 六安市 = fshp.get_cn_city(['合肥市', '六安市'])

安徽省的所有市 = fshp.get_cn_city(province='安徽省')
安徽省和江苏省的所有市 = fshp.get_cn_city(province=['安徽省', '江苏省'])

所有区县 = fshp.get_cn_district()
蜀山区 = fshp.get_cn_district('蜀山区')
蜀山区, 包河区 = fshp.get_cn_district(['蜀山区', '包河区'])

合肥市的所有区县 = fshp.get_cn_district(city='合肥市')
安徽省的所有区县 = fshp.get_cn_district(province='安徽省')

# 通过行政区划代码查询
北京市 = fshp.get_cn_province(110000)
京津冀 = fshp.get_cn_province([110000, 120000, 130000])
```

--------------------------------

### Plot Chinese Administrative Boundaries

Source: https://github.com/zhajiman/frykit/blob/main/README.md

Demonstrates plotting Chinese administrative boundaries using the `frykit.plot` module. It includes functions for plotting national borders, coastlines, provinces, cities, and districts, along with functions for labeling them. The example shows how to color-code specific regions and use a predefined Cartopy projection.

```Python
import matplotlib.pyplot as plt
import frykit.plot as fplt

plt.figure(figsize=(8, 8))
ax = plt.axes(projection=fplt.PLATE_CARREE)
fplt.add_cn_province(ax)
fplt.add_cn_province(ax, ['北京市', '天津市', '河北省'], fc='dodgerblue')
fplt.add_cn_line(ax)
fplt.label_cn_province(ax)

plt.show()

# 画出所有省份，同时用颜色区分京津冀地区
# 其中 fplt.PLATE_CARREE 只是一个 ccrs.PlateCarree() 实例，这样就无需在脚本开头导入 cartopy.crs。

ax = plt.axes(projection=fplt.PLATE_CARREE)
fplt.add_cn_district(ax, province='北京市', fc=plt.cm.Pastel1.colors)
fplt.label_cn_district(ax, province='北京市')

plt.show()

# 画出北京所有区
```

--------------------------------

### Add Mini Map

Source: https://github.com/zhajiman/frykit/blob/main/README.md

Demonstrates how to add a small overview map (mini map) to a larger geospatial plot using Frykit's `add_mini_axes` function. This function automatically positions the mini map in a corner and uses the same projection as the main map, simplifying the setup.

```Python
mini_ax = fplt.add_mini_axes(ax)
mini_ax.set_extent((105, 120, 2, 25), crs=fplt.PLATE_CARREE)
fplt.add_cn_province(mini_ax)
fplt.add_cn_line(mini_ax)
```

--------------------------------

### Switch Data Source in Frykit

Source: https://github.com/zhajiman/frykit/blob/main/README.md

Explains how to switch between different administrative boundary data sources (Gaode Maps and Tianditu) in Frykit. It shows methods using function parameters, global configuration, and context managers.

```Python
# 通过函数参数指定
amap_cities = fshp.get_cn_city(data_source='amap')
tianditu_cities = fshp.get_cn_city(data_source='tianditu')

# 在脚本开头设置全局数据源
import frykit
frykit.set_option({'data_source': 'tianditu'})

# 用上下文管理器临时设置数据源
with frykit.option_context({'data_source': 'tianditu'}):
    cities = fshp.get_cn_city()
    some_function(cities)

# 0.7.5 开始可以直接修改 frykit.config.data_source 属性来设置数据源
# frykit.config.data_source = 'tianditu'
```

--------------------------------

### Environment Versions

Source: https://github.com/zhajiman/frykit/blob/main/README.md

Lists the specific versions of Python and key libraries (Cartopy, Frykit) used in the performance tests. These versions are crucial for reproducibility and understanding the test environment.

```Python
# Environment Versions
python==3.11.9
cartopy==0.24.0
frykit==0.7.2.post1
```

--------------------------------

### Clip Artist with Multiple Provinces

Source: https://github.com/zhajiman/frykit/blob/main/README.md

Demonstrates clipping a plot artist using a list of specific Chinese provinces. The `clip_by_cn_province` function allows for targeted clipping by providing a list of province names.

```Python
fplt.clip_by_cn_province(artist, ['北京市', '天津市', '河北省'])
```

--------------------------------

### Create Qualitative Colorbar

Source: https://github.com/zhajiman/frykit/blob/main/README.md

Provides a method to create a qualitative colorbar where each discrete color corresponds to a specific tick label. This is useful for categorical data and is achieved using Frykit's `make_qualitative_palette` and `plot_colormap` functions.

```Python
colors = [
    'orangered',
    'orange',
    'yellow',
    'limegreen',
    'royalblue',
    'darkviolet'
]
cmap, norm, ticks = fplt.make_qualitative_palette(colors)
cbar = fplt.plot_colormap(cmap, norm)
cbar.set_ticks(ticks)
cbar.set_ticklabels(colors)
```

--------------------------------

### Create Centered Boundary Colorbar

Source: https://github.com/zhajiman/frykit/blob/main/README.md

Demonstrates how to create a colorbar with a centered zero value, where the color scale is symmetric around zero (e.g., blue for negative, white for zero, orange/red for positive). This uses Frykit's `CenteredBoundaryNorm` and a specified colormap.

```Python
import cmaps

boundaries = [-10, -5, -2, -1, 1, 2, 5, 10, 20, 50, 100]
norm = fplt.CenteredBoundaryNorm(boundaries)
cbar = fplt.plot_colormap(cmaps.BlueWhiteOrangeRed, norm)
cbar.set_ticks(boundaries)
```

--------------------------------

### Clip Artist with Custom Polygon

Source: https://github.com/zhajiman/frykit/blob/main/README.md

Illustrates how to clip a plot artist using a custom polygon formed by combining multiple geographic boundaries (e.g., a province and cities). This involves using Shapely for geometric operations like union and Frykit's `clip_by_polygon` function.

```Python
import shapely

北京市 = fshp.get_cn_province('北京市')
保定市 = fshp.get_cn_city('保定市')
张家口市 = fshp.get_cn_city('张家口市')
polygon = shapely.union_all([北京市, 保定市, 张家口市])
fplt.clip_by_polygon(artist, polygon)
```

--------------------------------

### Set Map Extent and Ticks with Frykit

Source: https://github.com/zhajiman/frykit/blob/main/README.md

Simplifies the process of setting map extents and ticks for Cartopy GeoAxes. The `set_map_ticks` function automates the creation of longitude and latitude ticks with specified intervals and formatting, including directional symbols.

```Python
import numpy as np
import cartopy.crs as ccrs
from cartopy.mpl.ticker import LongitudeFormatter, LatitudeFormatter

crs = ccrs.PlateCarree()
ax.set_extent((70, 140, 0, 60), crs=crs)
ax.set_xticks(np.arange(70, 141, 10), crs=crs)
ax.set_yticks(np.arange(0, 61, 10), crs=crs)
ax.xaxis.set_major_formatter(LongitudeFormatter())
ax.yaxis.set_major_formatter(LatitudeFormatter())
```

```Python
fplt.set_map_ticks(ax, (70, 140, 0, 60), dx=10, dy=10)
```

--------------------------------

### Draw Geometries with Frykit

Source: https://github.com/zhajiman/frykit/blob/main/README.md

Demonstrates how to draw various geographic shapes like country borders, circles, shapefiles, and GeoJSON data using Frykit's `add_geometries` function. This function is similar to Cartopy's `GeoAxes.add_geometries` but works with standard Matplotlib Axes and offers optimizations for projection and filling.

```Python
fplt.add_geometries(ax, fshp.get_cn_border())
```

```Python
import shapely

circle = shapely.Point(0, 0).buffer(10)
fplt.add_geometries(ax, circle)
```

```Python
from cartopy.io.shapereader import Reader

reader = Reader('2023年_CTAmap_1.12版/2023年县级/2023年县级.shp')
geometries = list(reader.geometries())
reader.close()

fplt.add_geometries(ax, geometries, fc='none', ec='k', lw=0.25)
```

```Python
import json
import shapely.geometry as sgeom

with open('天地图_行政区划可视化/中国_省.geojson') as f:
    geometries = [
        sgeom.shape(feature["geometry"]) for feature in json.load(f)["features"]
    ]

fplt.add_geometries(ax, geometries, fc='none', ec='k', lw=0.25)
```

--------------------------------

### Add GMT Style Frame

Source: https://github.com/zhajiman/frykit/blob/main/README.md

Shows how to add a GMT-style frame (grid lines and labels) to a map using Frykit's `add_frame` function. This function is primarily for Plate Carree or Mercator projections and can also be applied to other artists like scale bars.

```Python
fplt.add_frame(ax)
```

```Python
fplt.add_frame(scale_bar)
```

--------------------------------

### Clip Artist with Country Border

Source: https://github.com/zhajiman/frykit/blob/main/README.md

Shows how to clip a Matplotlib artist, such as a contour plot, using the country border. This is achieved using Frykit's `clip_by_cn_border` function, which visually removes data outside the specified geographic boundary.

```Python
import matplotlib.pyplot as plt
import frykit.plot as fplt

ax = plt.axes(projection=fplt.PLATE_CARREE)
fplt.add_cn_province(ax)
fplt.add_cn_line(ax)

data = fplt.load_test_data()
cf = ax.contourf(
    data.lon,
    data.lat,
    data.t2m,
    levels=20,
    cmap='rainbow',
    transform=fplt.PLATE_CARREE,
)
fplt.clip_by_cn_border(cf)

plt.show()
```

--------------------------------

### Create Data Mask with Polygon

Source: https://github.com/zhajiman/frykit/blob/main/README.md

Explains how to create a data mask based on a geographic polygon using Frykit's `polygon_mask` or `polygon_mask2` functions. This mask can then be used to set data points outside the polygon to NaN (Not a Number) during data processing.

```Python
border = fshp.get_cn_border()
mask = fshp.polygon_mask(border, lon2d, lat2d)
data[~mask] = np.nan
ax.contourf(lon2d, lat2d, data)
```

```Python
mask = fplt.polygon_mask2(border, lon1d, lat1d)
data[~mask] = np.nan
```

--------------------------------

### Add Scale Bar

Source: https://github.com/zhajiman/frykit/blob/main/README.md

Illustrates adding a scale bar to a map using Frykit's `add_scale_bar` function. The scale bar's length is determined by the geographic distance corresponding to a unit length at the map's center. It can be further customized using standard Matplotlib methods.

```Python
scale_bar = fplt.add_scale_bar(ax, 0.36, 0.8, length=1000)
scale_bar.set_xticks([0, 500, 1000])
```

--------------------------------

### Add Wind Vector Legend

Source: https://github.com/zhajiman/frykit/blob/main/README.md

Demonstrates how to add a wind vector legend to a plot using Frykit's `add_quiver_legend` function. This function places a legend indicating wind speed and direction, typically in the lower right corner of the plot.

```Python
Q = ax.quiver(x, y, u, v, transform=fplt.PLATE_CARREE)
fplt.add_quiver_legend(Q, U=10, width=0.15, height=0.12)
```

--------------------------------

### Add North Arrow

Source: https://github.com/zhajiman/frykit/blob/main/README.md

Shows how to add a north arrow (compass rose) to a geospatial plot using Frykit's `add_compass` function. The position is specified using Axes coordinates, and the arrow automatically points north or can be manually oriented with the `angle` parameter.

```Python
fplt.add_compass(ax, 0.95, 0.8, size=15)
```

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