Custom names for links, nodes, subareas¶

This is a sample notebook demonstrating how to use the ShapefileToSwiftConverter class from the geosdhydro package to convert a shapefile with custom names for links, nodes, and subareas into a JSON format compatible with the swift2 hydrological modeling framework.

In [1]:

from pathlib import Path

import geopandas as gpd
from shapely.geometry import LineString

from geosdhydro import ShapefileToSwiftConverter

from pathlib import Path import geopandas as gpd from shapely.geometry import LineString from geosdhydro import ShapefileToSwiftConverter

Create synthetic test data¶

Side note that even if string columns for IDS are preferable, the converter will convert them to string if they are not, as will be the case for ToNodeID below.

We use the default column names for the required fields:

In [2]:

data = {
    "LinkID": ["1", "2", "3", "4", "5"],  # As strings
    "FromNodeID": ["2", "3", "4", "5", "6"],  # As strings
    "ToNodeID": [1, 2, 2, 2, 5],
    "SPathLen": [1000.0, 1500.0, 2000.0, 800.0, 1200.0],
    "DArea2": [3000000.0, 4000000.0, 2500000.0, -1.0, 3500000.0],  # Link 4 has negative area
    "geometry": [
        LineString([(2.1, 2.2), (1.1, 1.2)]),  # Link 1: node 2 -> node 1
        LineString([(3.1, 3.2), (2.1, 2.2)]),  # Link 2: node 3 -> node 2
        LineString([(4.1, 4.2), (2.1, 2.2)]),  # Link 3: node 4 -> node 2
        LineString([(5.1, 5.2), (2.1, 2.2)]),  # Link 4: node 5 -> node 2
        LineString([(6.1, 6.2), (5.1, 5.2)]),  # Link 5: node 6 -> node 5
    ],
}

data = { "LinkID": ["1", "2", "3", "4", "5"], # As strings "FromNodeID": ["2", "3", "4", "5", "6"], # As strings "ToNodeID": [1, 2, 2, 2, 5], "SPathLen": [1000.0, 1500.0, 2000.0, 800.0, 1200.0], "DArea2": [3000000.0, 4000000.0, 2500000.0, -1.0, 3500000.0], # Link 4 has negative area "geometry": [ LineString([(2.1, 2.2), (1.1, 1.2)]), # Link 1: node 2 -> node 1 LineString([(3.1, 3.2), (2.1, 2.2)]), # Link 2: node 3 -> node 2 LineString([(4.1, 4.2), (2.1, 2.2)]), # Link 3: node 4 -> node 2 LineString([(5.1, 5.2), (2.1, 2.2)]), # Link 4: node 5 -> node 2 LineString([(6.1, 6.2), (5.1, 5.2)]), # Link 5: node 6 -> node 5 ], }

That was the minimally required columns. We can add a few more to illustrate custom names:

In [3]:

custom_linkname_fieldname = "LinkName"
data[custom_linkname_fieldname] = [f"CustomLinkName_{i}" for i in range(5)]

# Custom names for subareas
custom_subarea_name_fieldname = "SubAreaName"
data[custom_subarea_name_fieldname] = [f"CustomSubAreaName_{i}" for i in range(5)]
gdf = gpd.GeoDataFrame(data)

gdf

custom_linkname_fieldname = "LinkName" data[custom_linkname_fieldname] = [f"CustomLinkName_{i}" for i in range(5)] # Custom names for subareas custom_subarea_name_fieldname = "SubAreaName" data[custom_subarea_name_fieldname] = [f"CustomSubAreaName_{i}" for i in range(5)] gdf = gpd.GeoDataFrame(data) gdf

Out[3]:

	LinkID	FromNodeID	ToNodeID	SPathLen	DArea2	geometry	LinkName	SubAreaName
0	1	2	1	1000.0	3000000.0	LINESTRING (2.1 2.2, 1.1 1.2)	CustomLinkName_0	CustomSubAreaName_0
1	2	3	2	1500.0	4000000.0	LINESTRING (3.1 3.2, 2.1 2.2)	CustomLinkName_1	CustomSubAreaName_1
2	3	4	2	2000.0	2500000.0	LINESTRING (4.1 4.2, 2.1 2.2)	CustomLinkName_2	CustomSubAreaName_2
3	4	5	2	800.0	-1.0	LINESTRING (5.1 5.2, 2.1 2.2)	CustomLinkName_3	CustomSubAreaName_3
4	5	6	5	1200.0	3500000.0	LINESTRING (6.1 6.2, 5.1 5.2)	CustomLinkName_4	CustomSubAreaName_4

In [4]:

# Custom node names
custom_nodenames = {str(i): f"CustomNodeName_{i}" for i in range(1, 7)}

# Custom node names custom_nodenames = {str(i): f"CustomNodeName_{i}" for i in range(1, 7)}

In [5]:

converter = ShapefileToSwiftConverter(
    gdf,
    linkname_field=custom_linkname_fieldname,
    subarea_name_field=custom_subarea_name_fieldname,
    node_names=custom_nodenames,
)
result = converter.convert()

converter = ShapefileToSwiftConverter( gdf, linkname_field=custom_linkname_fieldname, subarea_name_field=custom_subarea_name_fieldname, node_names=custom_nodenames, ) result = converter.convert()

In [6]:

result.keys()

result.keys()

Out[6]:

dict_keys(['Links', 'Nodes', 'SubAreas'])

In [7]:

result["Nodes"][0]

result["Nodes"][0]

Out[7]:

{'ErrorCorrection': {'ErrorCorrectionType': 'NoErrorCorrection'},
 'ID': '1',
 'Name': 'CustomNodeName_1',
 'Reservoir': {'ReservoirType': 'NoReservoir'}}

In [8]:

result["Links"][0]

result["Links"][0]

Out[8]:

{'ChannelRouting': {'ChannelRoutingType': 'NoRouting'},
 'DownstreamNodeID': '1',
 'ID': '1',
 'Length': 1000.0,
 'ManningsN': 1.0,
 'Name': 'CustomLinkName_0',
 'Slope': 1.0,
 'UpstreamNodeID': '2',
 'f': 1.0}

We check that one of the subarea is not present (area negative), even if a mapped name was specified:

In [9]:

[s['Name'] for s in  result["SubAreas"]]

[s['Name'] for s in result["SubAreas"]]

Out[9]:

['CustomSubAreaName_0',
 'CustomSubAreaName_1',
 'CustomSubAreaName_2',
 'CustomSubAreaName_4']

In [ ]:

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