def getXSAtPoint(point, numpoints, width, file=None):
tpoint = f'POINT({point[1]} {point[0]})'
df = pd.DataFrame({
'pointofinterest': ['this'],
'Lat': [point[0]],
'Lon': [point[1]]
})
gpd_pt = gpd.GeoDataFrame(df, geometry=gpd.points_from_xy(df.Lon, df.Lat))
gpd_pt.set_crs(epsg=4326, inplace=True)
gpd_pt.to_crs(epsg=3857, inplace=True)
comid = getCIDFromLatLon(point)
print(f'comid = {comid}')
strm_seg = NLDI().getfeature_byid("comid", "3561878",
basin=False).to_crs('epsg:3857')
xs = XSGen(point=gpd_pt, cl_geom=strm_seg, ny=100, width=1000)
xs_line = xs.get_xs()
# get topo polygon with buffer to ensure there is enough topography to interpolate xs line
# With coarsest DEM (30m) 100. m should
bb = xs_line.total_bounds - ((100., 100., -100., -100.))
dem = py3dep.get_map("DEM",
tuple(bb),
resolution=10,
geo_crs="EPSG:3857",
crs="epsg:3857")
x, y = xs.get_xs_points()
dsi = dem.interp(x=('z', x), y=('z', y))
pdsi = dsi.to_dataframe()
# gpdsi = gpd.GeoDataFrame(pdsi, gpd.points_from_xy(pdsi.x.values, pdsi.y.values))
gpdsi = dataframe_to_geodataframe(pdsi)
gpdsi.set_crs(epsg=3857, inplace=True)
gpdsi.to_crs(epsg=4326, inplace=True)
if (file):
if not isinstance(file, str):
# with open(file, "w") as f:
file.write(gpdsi.to_json())
file.close()
return 0
else:
with open(file, "w") as f:
f.write(gpdsi.to_json())
f.close()
# gpdsi.to_file(file, driver="GeoJSON")
return 0
else:
return gpdsi
def get_streamflow(
self, station_ids: Union[List[str], str], dates: Tuple[str, str], mmd: bool = False
) -> pd.DataFrame:
"""Get daily streamflow observations from USGS.
Parameters
----------
station_ids : str, list
The gage ID(s) of the USGS station.
dates : tuple
Start and end dates as a tuple (start, end).
mmd : bool
Convert cms to mm/day based on the contributing drainage area of the stations.
Returns
-------
pandas.DataFrame
Streamflow data observations in cubic meter per second (cms)
"""
if not isinstance(station_ids, (str, list)):
raise InvalidInputType("ids", "str or list")
station_ids = station_ids if isinstance(station_ids, list) else [station_ids]
if not isinstance(dates, tuple) or len(dates) != 2:
raise InvalidInputType("dates", "tuple", "(start, end)")
start = pd.to_datetime(dates[0])
end = pd.to_datetime(dates[1])
siteinfo = self.get_info(self.query_byid(station_ids))
check_dates = siteinfo.loc[
(
(siteinfo.stat_cd == "00003")
& (start < siteinfo.begin_date)
& (end > siteinfo.end_date)
),
"site_no",
].tolist()
nas = [s for s in station_ids if s in check_dates]
if len(nas) > 0:
raise InvalidInputRange(
"Daily Mean data unavailable for the specified time "
+ "period for the following stations:\n"
+ ", ".join(nas)
)
payload = {
"format": "json",
"sites": ",".join(station_ids),
"startDT": start.strftime("%Y-%m-%d"),
"endDT": end.strftime("%Y-%m-%d"),
"parameterCd": "00060",
"statCd": "00003",
"siteStatus": "all",
}
resp = self.session.post(f"{self.url}/dv", payload)
time_series = resp.json()["value"]["timeSeries"]
r_ts = {
t["sourceInfo"]["siteCode"][0]["value"]: t["values"][0]["value"] for t in time_series
}
def to_df(col, dic):
discharge = pd.DataFrame.from_records(dic, exclude=["qualifiers"], index=["dateTime"])
discharge.index = pd.to_datetime(discharge.index)
discharge.columns = [col]
return discharge
qobs = pd.concat([to_df(f"USGS-{s}", t) for s, t in r_ts.items()], axis=1)
# Convert cfs to cms
qobs = qobs.astype("float64") * 0.028316846592
if mmd:
nldi = NLDI()
basins_dict = {
f"USGS-{s}": nldi.getfeature_byid("nwissite", f"USGS-{s}", basin=True).geometry
for s in station_ids
}
basins = gpd.GeoDataFrame.from_dict(basins_dict, orient="index")
basins.columns = ["geometry"]
basins = basins.set_crs(DEF_CRS)
eck4 = "+proj=eck4 +lon_0=0 +x_0=0 +y_0=0 +datum=WGS84 +units=m +no_defs"
area = basins.to_crs(eck4).area
ms2mmd = 1000.0 * 24.0 * 3600.0
qobs = qobs.apply(lambda x: x / area.loc[x.name] * ms2mmd)
return qobs
from shapely import geometry
import geopandas as gpd
import json
def getFeatures(gdf):
"""Function to parse features from GeoDataFrame in such a manner that rasterio wants them"""
import json
return [json.loads(gdf.to_json())['features'][0]['geometry']]
band_of_interest = 1 # DEM
with rio.open('Mads_1_COG.tif') as dataset:
elev = dataset.read(1)
basin = NLDI().getfeature_byid("comid", "13294318",
basin=True).to_crs('epsg:4269')
ax = plt.subplot(111)
show(dataset, ax=ax)
basin.plot(ax=ax, facecolor="none", edgecolor='black', lw=0.7)
plt.show()
#Subset to bounding box of basin
demdata = rio.open('Mads_1.tif')
show((demdata, 1), cmap='terrain')
print(demdata.crs, basin.crs)
# print(basin.boundary.to_json())
basin_coords = getFeatures(basin)
minx, miny, maxx, maxy = basin.total_bounds
p1 = geometry.Point(minx, miny)
p2 = geometry.Point(minx, maxy)
"""Tests for PyNHD package."""
import io
import pytest
from shapely.geometry import box
import pynhd as nhd
from pynhd import NLDI, WaterData
STA_ID = "01031500"
station_id = f"USGS-{STA_ID}"
site = "nwissite"
UM = "upstreamMain"
UT = "upstreamTributaries"
nldi = NLDI()
@pytest.mark.flaky(max_runs=3)
def test_nldi_navigate():
stm = nldi.navigate_byid(site, station_id, UM, site)
st100 = nldi.navigate_byid(site, station_id, UM, site, distance=100)
pp = nldi.navigate_byid(site, station_id, UT, "huc12pp")
wqp = nldi.navigate_byloc((-70, 44), UT, "wqp")
assert (
st100.shape[0] == 2
and stm.shape[0] == 2
and pp.shape[0] == 12
and wqp.comid.iloc[0] == "6710923"
)