def points_to_facility(netDataset,
rdv_name,
points,
facilities,
outTable,
oneway=None,
save_result_input=None):
"""
Execute Closest Facility and save the result in the points table
"""
from gasp.cpu.arcg.mng.fld import add_field
from gasp.cpu.arcg.mng.fld import calc_fld
from gasp.cpu.arcg.mng.joins import join_table
arcpy.env.overwriteOutput = True
closest_facility(netDataset,
rdv_name,
facilities,
points,
outTable,
oneway_restriction=oneway)
if save_result_input:
add_field(outTable, 'j', "SHORT", 6)
calc_fld(outTable, 'j', "[IncidentID]-1")
join_table(points, "FID", outTable, "j", "Total_Minu")
def aspect(dem, aspect, reclass=None):
"""
Return Aspect raster reclassified or not
"""
import os
outAspect = aspect if not reclass else \
os.path.join(
os.path.dirname(aspect),
'{n}_original{f}'.format(
n=os.path.splitext(os.path.basename(aspect))[0],
f=os.path.splitext(os.path.basename(aspect))[1]
)
)
arcpy.gp.Aspect_sa(dem, outAspect)
if reclass:
from gasp.cpu.arcg.lyr import raster_lyr
from gasp.cpu.arcg.spanlst.rcls import reclassify
from gasp.cpu.arcg.mng.fld import add_field
__rules = ("-1 0 1;"
"0 22,5 2;"
"22,5 67,5 3;"
"67,5 112,5 4;"
"112,5 157,5 5;"
"157,5 202,5 6;"
"202,5 247,5 7;"
"247,5 292,5 8;"
"292,5 337,5 9;"
"337,5 360 2")
reclassify(outAspect, "Value", __rules, aspect, template=outAspect)
d = {
1: 'Flat',
2: 'North',
3: 'Northeast',
4: 'East',
5: 'Southeast',
6: 'South',
7: 'Southwest',
8: 'West',
9: 'Northwest'
}
add_field(aspect, 'aspect', "TEXT", "15")
cursor = arcpy.UpdateCursor(rst_lyr(aspect))
for lnh in cursor:
__val = int(lnh.getValue("Value"))
lnh.setValue('aspect', d[__val])
cursor.updateRow(lnh)
del cursor, lnh
def WritePopLessXMin(shp, fld_pop, lst_intersected):
add_field(shp, "poxX", "SHORT", "8")
cursor = arcpy.UpdateCursor(shp)
linha = cursor.next()
while linha:
bgri = int(linha.getValue("FID"))
if bgri in lst_intersected:
p = int(linha.getValue(fld_pop))
linha.setValue("popX", p)
cursor.UpdateRow(linha)
linha = cursor.next()
return "popX"
def mean_rst_by_polygon(polygons, raster, work, resultShp):
"""
Mean of all cells intersect with the input polygon features
"""
import arcpy
import os
from gasp.cpu.arcg.lyr import feat_lyr, rst_lyr
from gasp.prop.rst import rst_stats
from gasp.cpu.arcg.mng.fld import add_field
from gasp.mng.gen import copy_feat
from gasp.cpu.arcg.anls.exct import select_by_attr
from gasp.cpu.arcg.mng.rst.proc import clip_raster
# ########### #
# Environment #
# ########### #
arcpy.env.overwriteOutput = True
arcpy.env.workspace = work
# ###### #
# Do it! #
# ###### #
# Copy the Input
poly_copy = copy_feat(polygons, resultShp, gisApi='arcpy')
# Create Layers
lyrShp = feat_lyr(poly_copy)
lyrRst = rst_lyr(raster)
# Create field for register calculated statistics
if len(os.path.basename(raster)) <= 10:
fld_name = os.path.basename(raster)
else:
fld_name = os.path.basename(raster)[:10]
add_field(lyrShp, fld_name, "DOUBLE", "20", "3")
# Calculate mean
c = arcpy.UpdateCursor(lyrShp)
l = c.next()
while l:
fid = str(l.getValue("FID"))
selection = select_by_attr(lyrShp, "FID={c}".format(c=fid),
"poly_{c}.shp".format(c=fid))
sel_rst = clip_raster(lyrRst, selection,
"clip_rst_{c}.img".format(c=fid))
mean = rst_stats(sel_rst, api='arcpy')["MEAN"]
l.setValue(fld_name, mean)
c.updateRow(l)
l = c.next()
def polygons_to_facility(netdataset,
polygons,
facilities,
outTbl,
oneway=None,
rdv=None,
junctions=None,
save_result_input=None):
"""
Execute the Closest Facility tool after calculation of polygons
centroids
"""
from gasp.cpu.arcg.lyr import feat_lyr
from gasp.cpu.arcg.mng.feat import feat_to_pnt
from gasp.cpu.arcg.mng.fld import add_field
from gasp.cpu.arcg.mng.fld import calc_fld
from gasp.cpu.arcg.mng.joins import join_table
arcpy.env.overwriteOutput = True
# Polygons to Points
polLyr = feat_lyr(polygons)
pntShp = os.path.join(
os.path.dirname(polygons),
os.path.splitext(os.path.basename(polygons))[0] + '_pnt.shp')
pntShp = feat_to_pnt(polLyr, pntShp, pnt_position='INSIDE')
closest_facility(netdataset,
facilities,
pntShp,
outTbl,
oneway_restriction=oneway,
rdv=rdv,
junc=junctions)
field_output = 'dst' + os.path.splitext(os.path.basename(facilities))[0]
add_field(outTbl, field_output[:10], "FLOAT", "10", "3")
calc_fld(outTbl, field_output[:10], "[Total_Minu]")
if save_result_input:
add_field(outTbl, 'j', "SHORT", "6")
calc_fld(outTbl, 'j', "[IncidentID]-1")
join_table(polLyr, "FID", outTbl, "j", field_output[:10])
def assign_units_to_polygons(bgri,
polygons,
id_bgri,
id_polygon,
field_bgri='pol_assigned',
workspace=None):
"""
Permite verificar a que municipio ou area de influencia uma subsecao
estatistica pertence (territorialmente).
Se uma subseccao se intersectar com mais de um poligono, a primeira fica
relacionada ao poligono que ocupa maior parte da sua area (isto pode
levantar algumas questoes, mas para ja fica assim).
A relacao entre a subsecao e o poligono que com ela intersecta ficara
escrita num novo campo da bgri
Use Arcgis to accomplish this
"""
import arcpy
import os
from gasp.cpu.arcg.lyr import feat_lyr
from gasp.cpu.arcg import get_geom_field, get_feat_area
from gasp.cpu.arcg.anls.ovlay import intersect
from gasp.cpu.arcg.mng.fld import add_field
arcpy.env.overwriteOutput = True
workspace = workspace if workspace else os.path.dirname(bgri)
# Create feature layers of the inputs
bgriLyr, polygLyr = [feat_lyr(bgri), feature_lyr(polygons)]
# Intersect
int_fc = os.path.join(workspace, 'bgri_and_polygons.shp')
int_fc = intersect([bgriLyr, polygLyr], int_fc)
# Relate bgri unit with polygon entities
intLyr = feat_lyr(int_fc)
cursor = arcpy.SearchCursor(intLyr)
bgri_polygons = {}
geomField = get_geom_field(intLyr)
for linha in cursor:
fid_bgri = linha.getValue(id_bgri)
fid_polygon = linha.getValue(id_polygon)
area = get_feat_area(linha, geomField)
if fid_bgri not in bgri_polygons.keys():
bgri_polygons[fid_bgri] = [fid_polygon, area]
else:
if area > bgri_polygons[fid_bgri][1]:
bgri_polygons[fid_bgri] = [fid_polygon, area]
else:
continue
# Write output
del cursor, linha
add_field(bgriLyr, field_bgri, "TEXT", "15")
cursor = arcpy.UpdateCursor(bgriLyr)
for linha in cursor:
fid_bgri = linha.getValue(id_bgri)
linha.setValue(field_bgri, bgri_polygons[fid_bgri][0])
cursor.updateRow(linha)
del cursor, linha, bgriLyr, polygLyr
def polygons_from_points(inputPnt,
outputPol,
prj,
POLYGON_FIELD,
ORDER_FIELD=None):
"""
Create a Polygon Table from a Point Table
A given Point Table:
FID | POLYGON_ID | ORDER_FIELD
0 | P1 | 1
1 | P1 | 2
2 | P1 | 3
3 | P1 | 4
4 | P2 | 1
5 | P2 | 2
6 | P2 | 3
7 | P2 | 4
Will be converted into a new Polygon Table:
FID | POLYGON_ID
0 | P1
1 | P2
In the Point Table, the POLYGON_ID field identifies the Polygon of that point,
the ORDER FIELD specifies the position (first point, second point, etc.)
of the point in the polygon.
If no ORDER field is specified, the points will be assigned to polygons
by reading order.
"""
import os
from gasp.cpu.arcg.lyr import feat_lyr
from gasp.cpu.arcg.mng.featcls import create_feat_class
from gasp.cpu.arcg.mng.fld import add_field
from gasp.cpu.arcg.mng.fld import type_fields
arcpy.env.overwriteOutput = True
# TODO: Check Geometry of the Inputs
# List all point
pntLyr = feat_lyr(inputPnt)
cursor = arcpy.SearchCursor(pntLyr)
line = cursor.next()
lPnt = {}
cnt = 0
while line:
# Get Point Geom
pnt = line.Shape.centroid
# Get Polygon Identification
polygon = line.getValue(POLYGON_FIELD)
# Get position in the polygon
order = line.getValue(ORDER_FIELD) if ORDER_FIELD else cnt
# Store data
if polygon not in lPnt.keys():
lPnt[polygon] = {order: (pnt.X, pnt.Y)}
else:
lPnt[polygon].update({order: (pnt.X, pnt.Y)})
line = cursor.next()
cnt += 1
del line
del cursor
# Write Output
create_feat_class(outputPol, "POLYGON", prj)
outLyr = feat_lyr(outputPol)
# Add polygon ID
fieldsPnt = type_fields(pntLyr)
POLYGON_FIELD_TYPE = "TEXT" if fieldsPnt[POLYGON_FIELD] == 'String' \
else "SHORT" if fieldsPnt[POLYGON_FIELD] == 'Integer' else \
"TEXT"
POLYGON_FIELD_PRECISION = 50 if POLYGON_FIELD_TYPE == "TEXT" else \
15
add_field(outLyr, POLYGON_FIELD, POLYGON_FIELD_TYPE,
POLYGON_FIELD_PRECISION)
cursor = arcpy.InsertCursor(outLyr)
# Add Polygons
point = arcpy.CreateObject("Point")
for polygon in lPnt:
vector = arcpy.CreateObject("Array")
pnt_order = lPnt[polygon].keys()
pnt_order.sort()
for p in pnt_order:
point.ID = p
point.X = lPnt[polygon][p][0]
point.Y = lPnt[polygon][p][1]
vector.add(point)
# Add last point
point.X = lPnt[polygon][pnt_order[0]][0]
point.Y = lPnt[polygon][pnt_order[0]][1]
vector.add(point)
new_row = cursor.newRow()
new_row.Shape = vector
new_row.setValue(POLYGON_FIELD, str(polygon))
cursor.insertRow(new_row)
vector = 0
def area_by_population(polygons,
inhabitants,
field_inhabitants,
work,
area_field='area_pop'):
"""
Feature area (polygons) by feature inhabitant (inhabitants)
"""
from gasp.cpu.arcg.lyr import feat_lyr
from gasp.cpu.arcg.mng.fld import add_field
from gasp.mng.genze import dissolve
from gasp.cpu.arcg.anls.ovlay import intersect
from gasp.cpu.arcg.anls.exct import select_by_attr
# ArcGIS environment
arcpy.env.overwriteOutput = True
arcpy.env.workspace = work
inhabitant_lyr = feat_lyr(inhabitants)
add_field(inhabitant_lyr, area_field, "FLOAT", "")
cursor = arcpy.UpdateCursor(inhabitant_lyr)
lnh = cursor.next()
while lnh:
"""TODO: Use intersection only once"""
f = int(lnh.getValue("FID"))
poly_extracted = "poly_{fid}.shp".format(fid=str(f))
select_by_attr(inhabitant_lyr, "FID = {fid}".format(fid=str(f)),
poly_extracted)
intersected = "int_{fid}.shp".format(fid=str(f))
intersect([polygons, poly_extracted], intersected)
dissolved = dissolve(intersected,
"diss_{f_}.shp".format(f_=str(f)),
"FID",
api='arcpy')
cs = arcpy.SearchCursor(dissolved)
l = cs.next()
geom = arcpy.Describe(dissolved).shapeFieldName
while l:
area = float(l.getValue(geom).area)
l = cs.next()
pop = int(lnh.getValue(field_inhabitants))
try:
indicator = area / pop
except:
indicator = 0.0 / pop
lnh.setValue(area_field)
cursor.updateRow(lnh)
lnh = cursor.next()
def count_geom_by_polygon(shp_geom,
polygons,
w,
count_geom_field='COUNT',
population_field=None):
"""
Intersect a given geometry with all polygons in a feature class and
count the number of geometries inside each polygon.
The user can also give a population field. The method will return the number
of geometries by person * 1000.
E.g. Count the number of points (health care centers, sports) by
statistical unit;
E.g. Count the number of points by inhabitants in each statistical unit.
"""
from gasp.cpu.arcg.lyr import feat_lyr
from gasp.cpu.arcg.mng.fld import add_field
from gasp.cpu.arcg.anls.ovlay import intersect
from gasp.cpu.arcg.anls.exct import select_by_attr
# ArcGIS environment
arcpy.env.workspace = w
arcpy.env.overwriteOutput = True
polygon_lyr = feat_lyr(polygons)
add_field(polygon_lyr, count_geom_field, "SHORT", "8")
if population_field:
geom_pop = count_geom_field + population_field
if len(geom_pop) >= 10:
geom_pop = geom_pop[:10]
add_field(polygon_lyr, geom_pop, "FLOAT", "")
# Update polygon layer
cursor = arcpy.UpdateCursor(polygon_lyr)
line = cursor.next()
while line:
"""TODO: Use select by attributes and not select analysis"""
fid = int(line.getValue("FID"))
poly_extracted = "poly_{f}.shp".format(f=str(fid))
select_by_attr(polygon_lyr, "FID = {f}".format(f=str(fid)),
poly_extracted)
intersected = "pnt_{f}.shp".format(f=str(fid))
intersect([shp_geom, poly_extracted], intersected)
cs = arcpy.SearchCursor(intersected)
nr_pnt = 0
for i in cs:
nr_pnt += 1
if population_field:
population = int(line.getValue(population_field))
pnt_by_pop = (nr_pnt / float(pnt_by_pop)) * 1000.0
line.setValue(geom_pop, pnt_by_pop)
line.setValue(count_geom_field, nr_pnt)
cursor.updateRow(line)
line = cursor.next()
def arcg_mean_time_WByPop(netDt,
rdv,
infraestruturas,
unidades,
conjuntos,
popf,
w,
output,
oneway=None):
"""
Tempo medio ponderado pela populacao residente a infra-estrutura mais
proxima (min)
* netDt = Path to Network Dataset
* infraestruturas = Points of destiny
* unidades = BGRI; Freg; Concelhos
* conjuntos = Freg; Concelhos; NUT - field
* popf = Field with the population of the statistic unity
* w = Workspace
* output = Path to store the final output
* rdv = Name of feature class with the streets network
"""
import arcpy
import os
from gasp.cpu.arcg.lyr import feat_lyr
from gasp.cpu.arcg.mng.feat import feat_to_pnt
from gasp.cpu.arcg.mng.fld import add_field
from gasp.cpu.arcg.mng.fld import calc_fld
from gasp.cpu.arcg.mng.joins import join_table
from gasp.mng.genze import dissolve
from gasp.mng.gen import copy_feat
from gasp.mob.arctbx.closest import closest_facility
def get_freg_denominator(shp, groups, population, fld_time="Total_Minu"):
cursor = arcpy.SearchCursor(shp)
groups_sum = {}
for lnh in cursor:
group = lnh.getValue(groups)
nrInd = float(lnh.getValue(population))
time = float(lnh.getValue(fld_time))
if group not in groups_sum.keys():
groups_sum[group] = time * nrInd
else:
groups_sum[group] += time * nrInd
del cursor, lnh
return groups_sum
arcpy.env.overwriteOutput = True
arcpy.env.workspace = w
# Start Procedure #
# Create copy of statitic unities to preserve the original data
copy_unities = copy_feat(unidades,
os.path.join(w, os.path.basename(unidades)),
gisApi='arcpy')
# Generate centroids of the statistic unities - unidades
lyr_unidades = feat_lyr(copy_unities)
pnt_unidades = feat_to_pnt(lyr_unidades, 'pnt_unidades.shp')
# Network Processing - Distance between CENTROID and Destiny points
closest_facility(netDt,
rdv,
infraestruturas,
pnt_unidades,
os.path.join(w, "cls_table.dbf"),
oneway_restriction=oneway)
add_field("cls_table.dbf", 'j', "SHORT", "6")
calc_fld("cls_table.dbf", 'j', "[IncidentID]-1")
join_table(lyr_unidades, "FID", "cls_table.dbf", "j", "Total_Minu")
# Calculo dos somatorios por freguesia (conjunto)
groups = get_freg_denominator(lyr_unidades, conjuntos, popf)
add_field(lyr_unidades, "tm", "FLOAT", "10", "3")
cs = arcpy.UpdateCursor(lyr_unidades)
linha = cs.next()
while linha:
group = linha.getValue(conjuntos)
t = float(linha.getValue("Total_Minu"))
p = int(linha.getValue(popf))
total = groups[group]
indi = ((t * p) / total) * t
linha.setValue("tm", indi)
cs.updateRow(linha)
linha = cs.next()
return dissolve(lyr_unidades,
output,
conjuntos,
statistics="tm SUM",
api="arcpy")
def mean_time_in_povoated_areas(network,
rdv_name,
stat_units,
popFld,
destinations,
output,
workspace,
ONEWAY=True,
GRID_REF_CELLSIZE=10):
"""
Receive statistical units and some destinations. Estimates the mean distance
to that destinations for each statistical unit.
The mean for each statistical will be calculated using a point grid:
-> Statistical unit to grid point;
-> Distance from grid point to destination;
-> Mean of these distances.
This method will only do the math for areas (statistic units)
with population.
"""
import os
import arcpy
from gasp.cpu.arcg.lyr import feat_lyr
from gasp.cpu.arcg.anls.exct import select_by_attr
from gasp.cpu.arcg.mng.fld import field_statistics
from gasp.cpu.arcg.mng.fld import add_field
from gasp.cpu.arcg.mng.gen import merge
from gasp.mng.gen import copy_feat
from gasp.mob.arctbx.closest import closest_facility
from gasp.to.shp.arcg import rst_to_pnt
from gasp.to.rst import shp_to_raster
if arcpy.CheckExtension("Network") == "Available":
arcpy.CheckOutExtension("Network")
else:
raise ValueError('Network analyst extension is not avaiable')
arcpy.env.overwriteOutput = True
WORK = workspace
# Add field
stat_units = copy_feat(stat_units,
os.path.join(WORK, os.path.basename(stat_units)),
gisApi='arcpy')
add_field(stat_units, "TIME", "DOUBLE", "10", precision="3")
# Split stat_units into two layers
# One with population
# One with no population
withPop = select_by_attr(stat_units, '{}>0'.format(popFld),
os.path.join(WORK, 'with_pop.shp'))
noPop = select_by_attr(stat_units, '{}=0'.format(popFld),
os.path.join(WORK, 'no_pop.shp'))
# For each statistic unit with population
withLyr = feat_lyr(withPop)
cursor = arcpy.UpdateCursor(withLyr)
FID = 0
for feature in cursor:
# Create a new file
unity = select_by_attr(
withLyr, 'FID = {}'.format(str(FID)),
os.path.join(WORK, 'unit_{}.shp'.format(str(FID))))
# Convert to raster
rst_unity = shp_to_raster(unity,
"FID",
GRID_REF_CELLSIZE,
None,
os.path.join(WORK,
'unit_{}.tif'.format(str(FID))),
api='arcpy')
# Convert to point
pnt_unity = rst_to_pnt(
rst_unity, os.path.join(WORK, 'pnt_un_{}.shp'.format(str(FID))))
# Execute closest facilitie
CLOSEST_TABLE = os.path.join(WORK, 'cls_fac_{}.dbf'.format(str(FID)))
closest_facility(network,
rdv_name,
destinations,
pnt_unity,
CLOSEST_TABLE,
oneway_restriction=ONEWAY)
# Get Mean
MEAN_TIME = field_statistics(CLOSEST_TABLE, 'Total_Minu', 'MEAN')[0]
# Record Mean
feature.setValue("TIME", MEAN_TIME)
cursor.updateRow(feature)
FID += 1
merge([withPop, noPop], output)
return output
def pop_less_dist_x(net_dataset, rdv_name, junctions_name, locations, interval,
unities, fld_groups, fld_pop, w, output):
"""
Network processing - executar service area de modo a conhecer as areas a
menos de x minutos de qualquer coisa
"""
import arcpy
import os
from gasp.cpu.arcg.lyr import feat_lyr
from gasp.mng.genze import dissolve
from gasp.cpu.arcg.anls.ovlay import intersect
from gasp.cpu.arcg.mng.fld import add_field
from gasp.mob.arctbx.svarea import service_area_polygon
def GetUnitiesIntersected(shpintersected, shpUnities):
# AND IF SHPUNITIES HAS LESS THAN 6 CHARACTERS
if len(os.path.basename(shpUnities)) > 6:
fld_tag = os.path.basename(shpUnities)[:6]
else:
fld_tag = os.path.basename(shpUnities)
c = arcpy.SearchCursor(shpintersected)
l = c.next()
u = []
while l:
fid_entity = int(l.getValue("FID_{name}".format(name=fld_tag)))
if fid_entity not in u:
u.append(fid_entity)
l = c.next()
return l
def WritePopLessXMin(shp, fld_pop, lst_intersected):
add_field(shp, "poxX", "SHORT", "8")
cursor = arcpy.UpdateCursor(shp)
linha = cursor.next()
while linha:
bgri = int(linha.getValue("FID"))
if bgri in lst_intersected:
p = int(linha.getValue(fld_pop))
linha.setValue("popX", p)
cursor.UpdateRow(linha)
linha = cursor.next()
return "popX"
arcpy.env.overwriteOutput = True
arcpy.env.workspace = w
# Procedure #
# Generate Service Area
ServiceArea = service_area_polygon(net_dataset, rdv_name, junctions_name,
interval, locations, "servarea.shp")
# Intersect unities with Service Area
lyr_unities = feat_lyr(unities)
unities_servarea = intersect([lyr_unities, ServiceArea], "unidades_mx.shp")
# Get the FID of the unities that intersects with the service area
id_unities = GetUnitiesIntersected(unities_servarea, unities)
# Update original shape with the population a menos de x minutes
fld_pop_less_x = WritePopLessXMin(lyr_unities, fld_pop, id_unities)
groups = dissolve(
lyr_unities, output, fld_groups,
"{pop} SUM;{popx} SUM".format(pop=fld_pop, popx=fld_pop_less_x))
# Estimate population percent
if len(fld_pop) > 6:
fld_pop_tag = fld_pop[:6]
else:
fld_pop_tag = fld_pop
add_field(shp, "lessX", "FLOAT", "8", "3")
cursor = arcpy.UpdateCursor(output)
linha = cursor.next()
while linha:
p = float(linha.getValue("SUM_{pop}".format(pop=fld_pop_tag)))
pt = float(linha.getValue("SUM_{p}".format(p=fld_pop_less_x)))
per = (p / pt) * 100.0
linha.setValue("lessX", per)
cursor.updateRow(linha)
linha = cursor.next()
return output
def mean_time_by_influence_area(netDt,
rdv,
infraestruturas,
fld_infraestruturas,
unidades,
id_unidade,
conjuntos,
popf,
influence_areas_unities,
w,
output,
oneway=True):
"""
Tempo medio ponderado pela populacao residente a infra-estrutura mais
proxima (min), por area de influencia
* netDt - Path to Network Dataset
* infraestruturas - Points of destiny
* fld_infraestruturas - Field on destiny points to relate with influence area
* unidades - BGRI; Freg; Concelhos
* conjuntos - Freg; Concelhos; NUT - field
* popf - Field with the population of the statistic unity
* influence_areas_unities - Field on statistic unities layer to relate
with influence area
* w = Workspace
* output = Path to store the final output
* rdv - Name of feature class with the streets network
* junctions - Name of feature class with the junctions
"""
import arcpy
import os
from gasp.cpu.arcg.lyr import feat_lyr
from gasp.cpu.arcg.mng.feat import feat_to_pnt
from gasp.cpu.arcg.mng.gen import merge
from gasp.mng.gen import copy_feat
from gasp.mng.genze import dissolve
from gasp.cpu.arcg.mng.fld import add_field
from gasp.cpu.arcg.mng.fld import calc_fld
from gasp.cpu.arcg.mng.fld import field_statistics
from gasp.cpu.arcg.mng.fld import type_fields
from gasp.cpu.arcg.mng.joins import join_table
from gasp.cpu.arcg.anls.exct import select_by_attr
from gasp.cpu.arcg.netanlst.closest import closest_facility
"""if arcpy.CheckExtension("Network") == "Available":
arcpy.CheckOutExtension("Network")
else:
raise ValueError('Network analyst extension is not avaiable')"""
def ListGroupArea(lyr, fld_ia, fld_grp):
d = {}
cs = arcpy.SearchCursor(lyr)
for lnh in cs:
id_group = lnh.getValue(fld_grp)
id_ia = lnh.getValue(fld_ia)
if id_group not in d.keys():
d[id_group] = [id_ia]
else:
if id_ia not in d[id_group]:
d[id_group].append(id_ia)
return d
arcpy.env.overwriteOutput = True
arcpy.env.workspace = w
# Procedure #
copy_unities = copy_feat(unidades,
os.path.join(w, os.path.basename(unidades)),
gisApi='arcpy')
# Generate centroids of the statistic unities - unidades
lyr_unidades = feat_lyr(copy_unities)
pnt_unidades = feat_to_pnt(lyr_unidades,
'pnt_unidades.shp',
pnt_position="INSIDE")
# List all groups of unities (conjuntos)
group_areas = ListGroupArea(lyr_unidades, influence_areas_unities,
conjuntos)
# Create Layers
lyr_pnt_unidades = feat_lyr(pnt_unidades)
lyr_pnt_facilities = feat_lyr(infraestruturas)
result_list = []
fld_type_unities = type_fields(lyr_pnt_unidades, field=conjuntos)
SELECT_UNITIES = '{fld}=\'{c}\'' if str(fld_type_unities) == 'String' \
else '{fld}={c}'
fld_type_facilities = type_fields(lyr_pnt_facilities,
field=fld_infraestruturas)
SELECT_FACILITIES = '{fld}=\'{obj}\'' if str(fld_type_facilities) == 'String' \
else '{fld}={obj}'
for group in group_areas.keys():
# Select centroids of interest
interest_centroids = select_by_attr(
lyr_pnt_unidades, SELECT_UNITIES.format(c=str(group),
fld=conjuntos),
'pnt_{c}.shp'.format(c=str(group)))
# Select facilities of interest
expression = ' OR '.join([
SELECT_FACILITIES.format(fld=fld_infraestruturas,
obj=str(group_areas[group][i]))
for i in range(len(group_areas[group]))
])
interest_facilities = select_by_attr(
lyr_pnt_facilities, expression,
'facilities_{c}.shp'.format(c=str(group)))
# Run closest facilitie - Distance between selected CENTROID and selected facilities
cls_fac_table = os.path.join(w, "clsf_{c}.dbf".format(c=str(group)))
closest_facility(netDt,
rdv,
interest_facilities,
interest_centroids,
cls_fac_table,
oneway_restriction=oneway)
add_field(cls_fac_table, 'j', "SHORT", "6")
calc_fld(cls_fac_table, 'j', "[IncidentID]-1")
join_table(interest_centroids, "FID", cls_fac_table, "j", "Total_Minu")
# Calculate sum of time x population
add_field(interest_centroids, 'sum', "DOUBLE", "10", "3")
calc_fld(interest_centroids, 'sum',
"[{pop}]*[Total_Minu]".format(pop=popf))
denominador = field_statistics(interest_centroids, 'sum', 'SUM')
add_field(interest_centroids, 'tm', "DOUBLE", "10", "3")
calc_fld(
interest_centroids, 'tm',
"([sum]/{sumatorio})*[Total_Minu]".format(
sumatorio=str(denominador)))
result_list.append(interest_centroids)
merge_shp = merge(result_list, "merge_centroids.shp")
join_table(lyr_unidades, id_unidade, "merge_centroids.shp", id_unidade,
"tm")
return dissolve(lyr_unidades,
output,
conjuntos,
statistics="tm SUM",
api='arcpy')
def dist_bet_same_points_different_featcls(pntA,
pntB,
attrA,
attrB,
distField='distance'):
"""
Calculate distance between the same points in different feature classes.
The script knows that the point is the same in pntA and pntB if the
value of attrA is equal to the value of attrB
"""
import os
from gasp.cpu.arcg.lyr import feat_lyr
from gasp.cpu.arcg.mng.fld import add_field
arcpy.env.overwriteOutput = True
# List features in pntA
lyrA = feat_lyr(pntA)
cursor = arcpy.SearchCursor(lyrA)
line = cursor.next()
dA = {}
while line:
attr = line.getValue(attrA)
geom = line.Shape.centroid
if attr not in dA:
dA[attr] = (geom.X, geom.Y)
else:
raise ValueError('AttrA and AttrB can not have duplicated values')
line = cursor.next()
del cursor
del line
# Calculate distance between points
add_field(lyrA, distField, "DOUBLE", "6", precision="4")
lyrB = feat_lyr(pntB)
cursor = arcpy.SearchCursor(lyrB)
line = cursor.next()
dist = {}
while line:
attr = line.getValue(attrB)
if attr in dA.keys():
xa, ya = dA[attr]
geom = line.Shape.centroid
xb, yb = (geom.X, geom.Y)
dist[attr] = ((xb - xa)**2 + (yb - ya)**2)**0.5
line = cursor.next()
del cursor
del line
cursor = arcpy.UpdateCursor(lyrA)
for line in cursor:
attr = line.getValue(attrA)
if attr in dist:
line.setValue(distField, dist[attr])
cursor.updateRow(line)
def geomArray_to_fc(array, output, GEOM_TYPE, EPSG, overwrite=True, fields=None):
"""
Convert a array as
array = [
{
"FID" : 0,
"OTHER_FIELDS" : value
"GEOM" : [(x1, y1), ..., (xn, yn)]
},
...,
{
"FID" : 1,
"OTHER_FIELDS" : value
"GEOM" : [(x1, y1), ..., (xn, yn)]
},
]
to a new Feature Class
If fields, it should have a value like:
{name : [type, length], name: [type, length]}
"""
from gasp.cpu.arcg.mng.featcls import create_feat_class
from gasp.cpu.arcg.lyr import feat_lyr
from gasp.cpu.arcg.mng.fld import add_field
if overwrite: arcpy.env.overwriteOutput = True
# Create a new Feature Class
output = create_feat_class(output, GEOM_TYPE, EPSG)
outLyr = feat_lyr(output)
# Create fields
if fields:
if type(fields) != dict:
raise ValueError(
'FIELDS should be a dict'
)
else:
for fld in fields:
add_field(
outLyr, fld, fields[fld][0],
fields[fld][1]
)
# Add things to the feature class
cursor = arcpy.InsertCursor(outLyr)
point = arcpy.CreateObject("Point")
for line in array:
vector = arcpy.CreateObject("Array")
c = 0
for pnt in line["GEOM"]:
point.ID = c
point.X = pnt[0]
point.Y = pnt[1]
vector.add(point)
c += 1
new_row = cursor.newRow()
new_row.Shape = vector
# Add field values
if fields:
for fld in fields:
if fld in line:
new_row.setValue(fld, line[fld])
cursor.insertRow(new_row)
vector = 0
return output
