Dfsu - Export to shapefile¶
- Read selected item and timestep from dfsu
- Extract geometry
- Create GeoPandas dataframe
- Save to ESRI shapefile
In [1]:
import pandas as pd
import geopandas as gpd
import mikeio
Step 1. read the selected data¶
In [2]:
ds = mikeio.read("../tests/testdata/wind_north_sea.dfsu")
ws = ds["Wind speed"][0]
ws.plot();
Step 2. extract geometry¶
In [3]:
shp = ds.geometry.to_shapely()
type(shp)
Out[3]:
shapely.geometry.multipolygon.MultiPolygon
Geopandas does not like multipolygon, it should be a list of polygons
In [4]:
poly_list = [p for p in shp.geoms]
Step 3. Create a geopandas dataframe¶
In [5]:
df = pd.DataFrame({'wind_speed':ws.to_numpy()})
df.head()
Out[5]:
| wind_speed | |
|---|---|
| 0 | 9.530760 |
| 1 | 9.652719 |
| 2 | 9.806072 |
| 3 | 8.775489 |
| 4 | 11.013206 |
In [6]:
gdf = gpd.GeoDataFrame(df,geometry=poly_list, crs=4326)
Step 4. Save to shapefile¶
In [7]:
gdf.to_file("wind_speed.shp")
Would you prefer to have this workflow to be a method on the mikeio.Dfsu class?
Post an issue on GitHub !
Clean up¶
In [8]:
import os
files = ["wind_speed"]
exts = ["cpg","dbf","shp","shx"]
for file in files:
for ext in exts:
filename = f"{file}.{ext}"
if os.path.exists(filename):
os.remove(filename)
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