def dem(suffix=''):
# This DEM covers a larger area, but doesn't have the extra processing
# around the junction
base_fn = os.path.join(here, "junction-composite-dem.tif")
if suffix == '':
jct_fn = os.path.join(here, 'junction-composite-20190117-no_adcp.tif')
elif suffix == 'smooth':
jct_fn = os.path.join(here, 'junction-composite-20200603-w_smooth.tif')
elif suffix == 'smoothadcp':
jct_fn = os.path.join(here, 'junction-composite-20200604-w_smooth.tif')
elif suffix == 'smoothadcp2':
# this includes adcp-derived bathy above the junction, while
# the above uses dwr multibeam above the junction
jct_fn = os.path.join(here, 'junction-composite-20200605-w_smooth.tif')
elif suffix == 'adcp':
jct_fn = None
else:
raise Exception("Unknown bathy suffix/version: %s" % suffix)
if jct_fn is not None:
# Specify priority to be sure jct fn wins out
f = field.MultiRasterField([(jct_fn, 10), (base_fn, 0)])
else:
f = field.GdalGrid(base_fn)
return f
def factory(attrs):
geo_bounds = attrs['geom'].bounds
if attrs['src_name'].startswith('py:'):
expr = attrs['src_name'][3:]
# something like 'ConstantField(-1.0)'
# a little sneaky... make it look like it's running
# after a "from stompy.spatial.field import *"
# and also it gets fields of the shapefile
field_hash = dict(field.__dict__)
# convert the attrs into a dict suitable for passing to eval
attrs_dict = {}
for name in attrs.dtype.names:
attrs_dict[name] = attrs[name]
return eval(expr, field_hash, attrs_dict)
# Otherwise assume src_name is a file name or file pattern.
for p in paths:
full_path = os.path.join(p, attrs['src_name'])
files = glob.glob(full_path)
if len(files) > 1:
mrf = field.MultiRasterField(files)
return mrf
elif len(files) == 1:
gg = field.GdalGrid(files[0], geo_bounds=geo_bounds)
gg.default_interpolation = 'linear'
return gg
log.warning("Source %s was not found -- ignoring" % attrs['src_name'])
return None
def dem():
srcs = [
os.path.join(
data_root,
"bathy_interp/master2017/tiles_2m_20171024/merged_2m.tif"),
os.path.join(data_root, "bathy_dwr/gtiff/dem_bay_delta*.tif"),
os.path.join(data_root,
"ncei/coastal_relief-farallones_clip-utm-merge.tif")
]
mrf = field.MultiRasterField(srcs)
return mrf
def factory(attrs):
geo_bounds = attrs['geom'].bounds
if attrs['src_name'] == 'dwr_2m_dems':
mrf = field.MultiRasterField([os.path.join(dwr_dem_path, "*_2m*tif")])
return mrf
elif attrs['src_name'] == 'dwr_10m_dems':
#mrf=field.MultiRasterField([os.path.join(dwr_dem_path,"dem_bay_delta_10m_v3_20121109_*.tif")])
# In this case there is only one that matters -- tile 4.
gg = field.GdalGrid(os.path.join(
dwr_dem_path, "dem_bay_delta_10m_v3_20121109_4.tif"),
geo_bounds=geo_bounds)
gg.default_interpolation = 'linear'
return gg
elif attrs['src_name'].endswith('.tif'):
for p in tif_paths:
fn = opj(p, attrs['src_name'])
if os.path.exists(fn):
gg = field.GdalGrid(fn, geo_bounds=geo_bounds)
gg.default_interpolation = 'linear'
return gg
raise Exception("Could not find tif %s" % attrs['src_name'])
elif attrs['src_name'].startswith('py:'):
expr = attrs['src_name'][3:]
# something like 'ConstantField(-1.0)'
# a little sneaky... make it look like it's running
# after a "from stompy.spatial.field import *"
# and also it gets fields of the shapefile
field_hash = dict(field.__dict__)
# convert the attrs into a dict suitable for passing to eval
attrs_dict = {}
for name in attrs.dtype.names:
attrs_dict[name] = attrs[name]
return eval(expr, field_hash, attrs_dict)
assert False
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib import cm, collections
import numpy as np
from shapely import ops
##
upper_ll = [-120.930408, 37.309940]
lower_ll = [-121.271098, 37.691794]
release_xy = proj_utils.mapper('WGS84', 'EPSG:26910')([upper_ll, lower_ll])
##
dem_mrg = field.MultiRasterField([
"../../../bathy/junction-composite-20200605-w_smooth.tif",
"/home/rusty/data/bathy_dwr/gtiff/dem_bay_delta_10m_v3_20121109_2.tif"
])
clip = (646390., 648336., 4184677., 4187210.)
dem = dem_mrg.extract_tile(clip)
##
aerial = field.GdalGrid(
"../../../gis/aerial/m_3712114_sw_10_h_20160621_20161004-UTM.tif")
aerial.F = aerial.F[:, :, :3] # drop alpha - seems mis-scaled
##
#grid=unstructured_grid.UnstructuredGrid.read_ugrid("../../../model/grid/snubby_junction/snubby-06.nc")
grid = unstructured_grid.UnstructuredGrid.read_ugrid(
"../../../model/suntans/snubby-08-edit60-with_bathysmooth.nc")
@memoize.memoize()
def lidar_mask():
mask = np.isfinite(levee_burn().F)
mask_open = ndimage.binary_dilation(mask, iterations=5)
lidar_mask = field.SimpleGrid(extents=levee_burn().extents, F=mask_open)
return lidar_mask
#plt.figure(1).clf() ; lidar_mask.plot()
##
lidar_src = field.MultiRasterField(["../bathy/lidar/tiles/*.tif"])
@memoize.memoize()
def lidar_resamp():
lidar_resamp_fn = 'lidar-levees.tif'
if not os.path.exists(lidar_resamp_fn):
# Will compile the lidar data here:
lidar_levees = field.SimpleGrid(extents=lidar_mask().extents,
F=np.zeros(lidar_mask().F.shape,
np.float32))
lidar_levees.F[:, :] = np.nan
lidar_resamp = lidar_src.to_grid(bounds=lidar_mask().extents,
dx=lidar_mask().dx,
from stompy.spatial import field
from stompy.grid import unstructured_grid
g = unstructured_grid.UnTRIM08Grid('junction_29_w_depth_2007.grd')
g.delete_cell_field('subgrid')
g.delete_edge_field('subgrid')
##
# There is too much weird stuff in the depth data on that grid.
# Start over from DEMs
mrf = field.MultiRasterField(["/Users/rusty/data/bathy_dwr/gtiff/*.tif"])
##
edge_xy = g.edges_center()
g.add_edge_field('depth', mrf(edge_xy))
##
g.add_node_field('depth', mrf(g.nodes['x']))
##
from stompy.grid import depth_connectivity
six.moves.reload_module(depth_connectivity)