def create_walk_groups(zones, name, inverse=False):
"""If different walk distances must be used in the creation of
isochrones for different stops they must be generated by separate
executions of the service area analysis. This function creates
separate feature classes for those groups, the zones parameter
must be a list
"""
# Create a feature layer so that selections can be made on the data
stops_layer = 'max_stops'
MakeFeatureLayer(MAX_STOPS, stops_layer)
# Assign a variable that will determine if the output is the zones
# provide or all of the zones that are not provided
negate = 'NOT' if inverse else ''
select_type = 'NEW_SELECTION'
zones_str = ', '.join("'{}'".format(z) for z in zones)
where_clause = '"{0}" {1} IN ({2})'.format(ZONE_FIELD, negate, zones_str)
SelectLayerByAttribute(stops_layer, select_type, where_clause)
zone_stops = join(TEMP_DIR, '{}.shp'.format(name))
CopyFeatures(stops_layer, zone_stops)
return zone_stops
def _tri_tool():
"""Triangulation for tool
"""
in_fc = sys.argv[1]
tri_type = sys.argv[2]
out_fc = sys.argv[3]
xtent = sys.argv[4]
desc = Describe(in_fc)
SR = desc['spatialReference']
flds = ['SHAPE@X', 'SHAPE@Y']
allpnts = False
z = FeatureClassToNumPyArray(in_fc, flds, "", SR, allpnts)
a = np.zeros((z.shape[0], 2), dtype='<f8')
a[:, 0] = z['SHAPE@X']
a[:, 1] = z['SHAPE@Y']
#
if tri_type == 'Delaunay':
tweet("Delaunay... clip extent {}".format(xtent))
t = tri_pnts(a, True) # must be a list of list of points
polys = poly(t, SR)
if Exists(out_fc):
Delete(out_fc)
CopyFeatures(polys, "in_memory/temp")
MakeFeatureLayer("in_memory/temp", "temp")
if xtent not in ("", None):
Clip("temp", xtent, out_fc, None)
else:
CopyFeatures("temp", out_fc)
else:
tweet("Voronoi... clip extent {}".format(xtent))
c = infinity_circle(a, fac=10)
aa = np.vstack((a, c))
v = vor_pnts(aa, testing=False)
polys = poly([v], SR)
if Exists(out_fc):
Delete(out_fc)
CopyFeatures(polys, "in_memory/temp")
MakeFeatureLayer("in_memory/temp", "temp")
if xtent not in (
"",
None,
):
Clip("temp", xtent, out_fc, None)
else:
CopyFeatures("temp", out_fc)
def execute_ChannelCorrection(demras, boundary, riverbed, rivernet, breachedmnt, messages):
arcpy.env.outputCoordinateSystem = demras.spatialReference
env.snapRaster = demras
ends = CreateScratchName("loob", data_type="FeatureClass", workspace="in_memory")
CopyFeatures(boundary, ends)
AddField(ends, "dummy", "LONG", field_alias="dummy", field_is_nullable="NULLABLE")
CalculateField(ends, "dummy", "1", "PYTHON")
endsras = CreateScratchName("loras", data_type="RasterDataset", workspace=env.scratchWorkspace)
PolylineToRaster(ends, "dummy", endsras, "MAXIMUM_LENGTH", cellsize=demras)
statpts = FocalStatistics(endsras, NbrRectangle(3, 3, "CELL"), "MAXIMUM", "DATA")
env.extent = demras
rasterbed = CreateScratchName("loras", data_type="RasterDataset", workspace=env.scratchWorkspace)
PolygonToRaster(riverbed, arcpy.Describe(riverbed).OIDFieldName, rasterbed, "CELL_CENTER", cellsize=demras)
rasterline = CreateScratchName("loras", data_type="RasterDataset", workspace=env.scratchWorkspace)
PolylineToRaster(rivernet, arcpy.Describe(rivernet).OIDFieldName, rasterline, cellsize=demras)
streambed = Con(IsNull(rasterline), Con(IsNull(rasterbed) == 0, 1), 1)
bedwalls = FocalStatistics(streambed, NbrRectangle(3, 3, "CELL"), "MAXIMUM", "DATA")
env.extent = bedwalls
chanelev = Con(streambed, demras)
chanmax = chanelev.maximum
chanwalls = chanelev.minimum - 100
switchtemp = CreateScratchName("loras", data_type="RasterDataset", workspace=env.scratchWorkspace)
switchelev = -1 * (Con(IsNull(streambed), Con(bedwalls, Con(IsNull(statpts), chanwalls)), chanelev) - chanmax)
switchelev.save(switchtemp)
Delete(statpts)
Delete(chanelev)
switchfilled = Fill(switchtemp)
Delete(switchtemp)
env.extent = demras
breachedtemp = Con(IsNull(streambed), demras, (-1*switchfilled) + chanmax)
breachedtemp.save(breachedmnt)
Delete(bedwalls)
Delete(endsras)
Delete(rasterline)
Delete(rasterbed)
Delete(switchfilled)
return
def tri_poly(in_fc, gdb, name, out_kind, constrained=True):
"""Return the Delaunay triangulation of the poly* features."""
tmp = MultipartToSinglepart(in_fc, r"memory\in_fc_temp") # in_fc = tmp
g, oids, shp_kind, k, m, SR = _in_(tmp, info="triangulate")
out = g.triangulate(as_one=False, as_polygon=True)
x, y = g.LL
g0 = out.translate(dx=x, dy=y)
if constrained:
tmp_name = temp_fc(g0, "tmp", shp_kind, SR) # make temp featureclass
tmp_lyr = MakeFeatureLayer(tmp_name)
SelectLayerByLocation(tmp_lyr, "WITHIN", tmp, None, "NEW_SELECTION",
"NOT_INVERT")
out_name = gdb.replace("\\", "/") + "/" + name
CopyFeatures(tmp_lyr, out_name)
else:
_out_(g0, gdb, name, shp_kind, SR)
return
def geometry_fc(a, IFT, p_type=None, gdb=None, fname=None, sr=None):
"""Form poly features from the list of arrays created by `fc_geometry`.
Parameters
----------
a : array or list of arrays
Some can be object arrays, normally created by ``pnts_arr``
IFT : list/array
Identifies which feature each input belongs to. This enables one to
account for multipart shapes
p_type : string
Uppercase geometry type eg POLYGON.
gdb : text
Geodatabase path and name.
fname : text
Featureclass name.
sr : spatial reference
name or object
Returns
-------
Singlepart and/or multipart featureclasses.
Notes
-----
The work is done by ``array_poly``.
"""
if p_type is None:
p_type = "POLYGON"
out = array_poly(a, p_type.upper(), sr=sr, IFT=IFT) # call array_poly
name = gdb + "/" + fname
wkspace = env.workspace = 'memory' # legacy is in_memory
CreateFeatureclass(wkspace, fname, p_type, spatial_reference=sr)
AddField(fname, 'ID_arr', 'LONG')
with InsertCursor(fname, ['SHAPE@', 'ID_arr']) as cur:
for row in out:
cur.insertRow(row)
CopyFeatures(fname, name)
return
def Geo_to_fc(geo, gdb=None, name=None, kind=None, SR=None):
"""Return a FeatureClass from a Geo array."""
SR = SR
if kind in (None, 0, 1, 2):
print("\n ``kind`` must be one of Polygon, Polyline or Point.")
return None
#
# dx, dy = geo.LL
# geo = geo.shift(dx, dy)
polys = Geo_to_arc_shapes(geo, as_singlepart=True)
out_name = gdb.replace("\\", "/") + "/" + name
wkspace = env.workspace = 'memory' # legacy is in_memory
tmp_name = "{}\\{}".format(wkspace, "tmp")
if Exists(tmp_name):
Delete(tmp_name)
CreateFeatureclass(wkspace, "tmp", kind, spatial_reference=SR)
AddField("tmp", 'ID_arr', 'LONG')
with InsertCursor("tmp", ['SHAPE@', 'ID_arr']) as cur:
for row in polys:
cur.insertRow(row)
CopyFeatures("tmp", out_name)
return
def process():
class LicenseError(Exception):
pass
try:
if CheckExtension("ImageAnalyst") == "Available":
CheckOutExtension("ImageAnalyst")
else:
# raise a custom exception
raise LicenseError
# System Parameters
tile_name = "FileName"
# Begin Script
temp_fc = join("in_memory", "temp_fc")
CopyFeatures(in_fc, temp_fc)
for f in file_names:
AddField(temp_fc, f, "TEXT")
df = pd.read_excel(in_xlsx, index_col=0)
def attribute_tile(in_feature_class,
in_tile_name,
in_df,
in_name,
xlsx_row_name=xlsx_row_name):
with da.UpdateCursor(in_feature_class,
[in_tile_name, in_name]) as cursor:
for fc_r in cursor:
for df_i, df_r in in_df.iterrows():
url = df_r[xlsx_row_name]
n = Path(url).stem
t_name = fc_r[0]
t_n = Path(t_name).stem
if n.startswith(in_name) and t_n in n:
fc_r[1] = url
cursor.updateRow(fc_r)
# Attribute the LiDAR Derivatives
for n in file_names:
attribute_tile(temp_fc, tile_name, df, n)
def attribute_tile_lidar(in_feature_class,
in_tile_name,
in_df,
in_name,
xlsx_row_name=xlsx_row_name):
with da.UpdateCursor(in_feature_class,
[in_tile_name, in_name]) as cursor:
for fc_r in cursor:
for df_i, df_r in in_df.iterrows():
url = df_r[xlsx_row_name]
n = split(url)[1]
t_name = fc_r[0]
if n == t_name:
fc_r[1] = url
cursor.updateRow(fc_r)
# Attribute the LiDAR tile now
AddField(temp_fc, in_lidar_format, "TEXT")
attribute_tile_lidar(temp_fc,
tile_name,
df,
in_lidar_format,
xlsx_row_name=xlsx_row_name)
'''
# Print Fields for debugging/assessing results of above operations
file_names.append(in_lidar_format)
print(file_names)
with da.SearchCursor(temp_fc, file_names) as cursor:
for fc_r in cursor:
print(fc_r)
'''
# Delete Pandas Dataframe from Memory
del df
# Copy in_memory temporary feature class to output location
CopyFeatures(temp_fc, out_fc)
# Delete Temporary Feature Class
Delete(temp_fc)
# Check back in Image Analyst license
CheckInExtension("ImageAnalyst")
except LicenseError:
AddError("ImageAnalyst license is unavailable")
print("ImageAnalyst license is unavailable")
except ExecuteError:
AddError(GetMessages(2))
print(GetMessages(2))