def calcHotspots(paths,states,segl):
import arcpy
shpath = paths["Shapefiles"]
for state in states:
input_fc = shpath + "{0}_TractsWData.shp".format(state)
tpath = shpath + "Centroids/"
if not os.path.exists(tpath):
os.makedirs(tpath)
output_fc = tpath + "{0}_Hotspot.shp".format(state)
print ("Calculating hotspot for ")
for segy in segl:
arcpy.HotSpots_stats(input_fc, segy, output_fc)
point_count = int(arcpy.GetParameterAsText(4)) boundary = arcpy.GetParameterAsText(5) workspace = arcpy.GetParameterAsText(6) buffer_l = workspace + "\\buffered.shp" buffer_erased = workspace + "\\buffer_erased.shp" HotSpots_l = workspace + "\\HotSpots.shp" HotSpots_signif = workspace + "\\HotSpots_sig.shp" HotSpots_signif_buffer = workspace + "\\HotSpots_sig_buff.shp" buffer_erased_final = workspace + "\\buffer_erased_final.shp" outFC = workspace + "\\absence_samples.shp" arcpy.Buffer_analysis(point_layer,buffer_l, "%s Meters"%buffer, "FULL", "ROUND", "NONE", "") arcpy.Erase_analysis(boundary, buffer_l, buffer_erased,'#') arcpy.HotSpots_stats(point_layer, weight_field, HotSpots_l,"FIXED_DISTANCE_BAND", "EUCLIDEAN_DISTANCE", "NONE","#", "#", "#","NO_FDR") my_addfield(HotSpots_l, "buff_dis", type="n") with arcpy.da.UpdateCursor(HotSpots_l, ["GiPValue", "GiZScore","buff_dis"]) as cursor: for row in cursor: if row[1] > 1.96 and row[0] < 0.05: row[2] = float(1) cursor.updateRow(row) try: arcpy.AddField_management(inFeatures, "temp7788", "DOUBLE",18 ,11) arcpy.DeleteField_management(inFeatures, "temp7788") except: pass arcpy.Select_analysis(HotSpots_l, HotSpots_signif, "\"buff_dis\" = 1") arcpy.Buffer_analysis(HotSpots_signif,HotSpots_signif_buffer, "%s Meters"%HotSpots_buffer, "FULL", "ROUND", "NONE", "")
arcpy.MakeFeatureLayer_management(urban_areas_2010_shp, urban_area, name_select, "", "FID FID VISIBLE NONE;Shape Shape VISIBLE NONE;UACE10 UACE10 VISIBLE NONE;AFFGEOID10 AFFGEOID10 VISIBLE NONE;GEOID10 GEOID10 VISIBLE NONE;NAME10 NAME10 VISIBLE NONE;NAMELSAD10 NAMELSAD10 VISIBLE NONE;LSAD10 LSAD10 VISIBLE NONE;UATYP10 UATYP10 VISIBLE NONE;ALAND10 ALAND10 VISIBLE NONE") print "- Area clip of Census Tracts" # Process: Clip (2) arcpy.Clip_analysis(state_tracts_clip, urban_area, ua_tracts_00, "") print "- Join DEC Data" # Process: Feature Layer arcpy.MakeFeatureLayer_management (ua_tracts_00, layer_dec) # Process: Add Join arcpy.AddJoin_management(layer_dec, "CTIDFP00", dec, "geoid2", "KEEP_COMMON") arcpy.CopyFeatures_management(layer_dec, ua_dec) print "- Income and Race Clusters - 2500 m" # Process: Hot Spot Analysis (Getis-Ord Gi*) arcpy.HotSpots_stats(ua_dec, "income_hh_", uat_inc_hspt00, "ZONE_OF_INDIFFERENCE", "EUCLIDEAN_DISTANCE", "NONE", "2500", "", "") arcpy.HotSpots_stats(ua_dec, "perc_white", uat_pw_hspt00, "ZONE_OF_INDIFFERENCE", "EUCLIDEAN_DISTANCE", "NONE", "2500", "", "") #2012 #Generate state, urban area lists (for projections, etc.) print "[2012]" st_list = [] for s in range(len(st)): st_list = st_list + [tract_12 + st[s] + "_tracts_12.shp"] print "- Merge for Multi-state Areas" # Process: Merge #arcpy.Union_analysis(st_list[:len(st)], state_tracts_union_shp, "ALL", "", "GAPS")
import arcpy
import os
from arcpy import env
from arcpy.sa import *
try:
# Get parameters
features = arcpy.GetParameter(0)
# Do outlier
out_features = arcpy.CreateUniqueName('results',
arcpy.env.scratchWorkspace)
arcpy.AddMessage('Output directory: ' + out_features)
arcpy.HotSpots_stats(Input_Feature_Class=features,
Input_Field='VALUE',
Output_Feature_Class=out_features)
arcpy.AddMessage('Outlier analysis complete')
# Write raster as result
arcpy.SetParameter(1, out_features)
except Exception as e:
arcpy.AddError(str(e))
finally:
arcpy.Delete_management('in_memory')
field_type='FLOAT')
arcpy.CalculateField_management(census_prj, 'area_true',
"float(!SHAPE.AREA!) / 1E6", "PYTHON")
#compare total population to mean NDVI normalized by population density
arcpy.AddField_management(census_prj, field_name='ageNDVI', field_type='FLOAT')
arcpy.CalculateField_management(census_prj, 'ageNDVI',
'(!MEAN! / !DP0010006!)', "PYTHON")
#compare male population to mean NDVI normalized by total population
arcpy.AddField_management(census_prj,
field_name='maleNDVI',
field_type='FLOAT')
arcpy.CalculateField_management(census_prj, 'maleNDVI',
'(!MEAN! / !DP0030002! )', "PYTHON")
#compare total hispanic ethnicity to mean NDVI normalized by total population
arcpy.AddField_management(census_prj,
field_name='his_NDVI',
field_type='FLOAT')
arcpy.CalculateField_management(census_prj, 'his_NDVI',
'(!MEAN! / !DP0180002!)', "PYTHON")
#hotspot analysis
out_ageNDVI = workspace + 'out_ageNDVI.shp'
out_maleNDVI = workspace + 'out_maleNDVI.shp'
out_hisNDVI = workspace + 'out_hisNDVI.shp'
arcpy.HotSpots_stats(census_prj, 'ageNDVI', out_ageNDVI)
arcpy.HotSpots_stats(census_prj, 'maleNDVI', out_maleNDVI)
arcpy.HotSpots_stats(census_prj, 'his_NDVI', out_hisNDVI)
raster_loc = arcpy.GetParameter(0)
# save raster cellsize
cellsize = arcpy.GetRasterProperties_management(raster_loc, 'CELLSIZEX')
# convert raster to points
arcpy.AddMessage('Converting to points: ' + str(raster_loc))
in_point_mem = 'in_memory\\raster_points'
arcpy.RasterToPoint_conversion(raster_loc, in_point_mem, "VALUE")
arcpy.AddMessage('Conversion to points complete')
# Do hot spot
out_features = 'in_memory\\out_group'
arcpy.AddMessage('Output directory: ' + out_features)
arcpy.HotSpots_stats(Input_Feature_Class=in_point_mem,
Input_Field='grid_code',
Output_Feature_Class=out_features)
arcpy.AddMessage('Hot spot analysis complete')
# add field to use for classification
arcpy.AddField_management(out_features, 'COLOR', 'SHORT')
codeblock = '''
def getColor(pval, zscore):
if pval <= 0.01 and zscore > 0:
return 1
elif pval <= 0.01 and zscore <= 0:
return -1
elif pval <= 0.05 and zscore > 0:
return 2
elif pval <= 0.05 and zscore <= 0:
return -2
years = ['1970', '1980', '1990', '2000', '2010']
no_seventy = ['75', '78', '98']
for y in years:
minc = "minc" + y
shrwht = "shrwht" + y
pop = "pop" + y
op = "[" + pop + "]/[AREA]"
uat_inc_hspt = "uat_inc_hspt_" + str(c) + "_" + y + ".shp"
uat_pw_hspt = "uat_pw_hspt_" + str(c) + "_" + y + ".shp"
print "- Compute Pop Dens " + y
# Process: Calculate Field
arcpy.CalculateField_management(ua_ncdb, "pdens", op, "VB", "")
print "- Income and Race Clusters - 1250 m [" + y + "]"
# Process: Hot Spot Analysis (Getis-Ord Gi*)
arcpy.HotSpots_stats(ua_ncdb, minc, uat_inc_hspt,
"FIXED_DISTANCE_BAND", "EUCLIDEAN_DISTANCE",
"NONE", "1250", "", "")
arcpy.HotSpots_stats(ua_ncdb, shrwht, uat_pw_hspt,
"FIXED_DISTANCE_BAND", "EUCLIDEAN_DISTANCE",
"NONE", "1250", "", "")
stop = timeit.default_timer()
print "Time:" + str((stop - start) / 60)
# Process: Add Join
arcpy.AddJoin_management(layerName, "GEOID", wac, "trct", "KEEP_COMMON")
arcpy.CopyFeatures_management(layerName, urban_area_join)
print "- Limit to Non-Truncated Tracts"
# Process: Make Feature Layer
thr = 0.01
name_select = "\"AREA\" > " + str(thr)
#print name_select
# Process: Make Feature Layer
arcpy.MakeFeatureLayer_management(
urban_area_join, valid_trcts, "\"AREA\" > 0.01", "",
"FID FID VISIBLE NONE;Shape Shape VISIBLE NONE;STATEFP STATEFP VISIBLE NONE;COUNTYFP COUNTYFP VISIBLE NONE;TRACTCE TRACTCE VISIBLE NONE;GEOID GEOID VISIBLE NONE;NAME NAME VISIBLE NONE;NAMELSAD NAMELSAD VISIBLE NONE;MTFCC MTFCC VISIBLE NONE;FUNCSTAT FUNCSTAT VISIBLE NONE;ALAND ALAND VISIBLE NONE;AWATER AWATER VISIBLE NONE;INTPTLAT INTPTLAT VISIBLE NONE;INTPTLON INTPTLON VISIBLE NONE;AREA AREA VISIBLE NONE;state state VISIBLE NONE;trct trct VISIBLE NONE;trctname trctname VISIBLE NONE;ca01 ca01 VISIBLE NONE;ca02 ca02 VISIBLE NONE;ca03 ca03 VISIBLE NONE;ce01 ce01 VISIBLE NONE;ce02 ce02 VISIBLE NONE;ce03 ce03 VISIBLE NONE;cns01 cns01 VISIBLE NONE;cns02 cns02 VISIBLE NONE;cns03 cns03 VISIBLE NONE;cns04 cns04 VISIBLE NONE;cns05 cns05 VISIBLE NONE;cns06 cns06 VISIBLE NONE;cns07 cns07 VISIBLE NONE;cns08 cns08 VISIBLE NONE;cns09 cns09 VISIBLE NONE;cns10 cns10 VISIBLE NONE;cns11 cns11 VISIBLE NONE;cns12 cns12 VISIBLE NONE;cns13 cns13 VISIBLE NONE;cns14 cns14 VISIBLE NONE;cns15 cns15 VISIBLE NONE;cns16 cns16 VISIBLE NONE;cns17 cns17 VISIBLE NONE;cns18 cns18 VISIBLE NONE;cns19 cns19 VISIBLE NONE;cns20 cns20 VISIBLE NONE;cr01 cr01 VISIBLE NONE;cr02 cr02 VISIBLE NONE;cr03 cr03 VISIBLE NONE;cr04 cr04 VISIBLE NONE;cr05 cr05 VISIBLE NONE;cr07 cr07 VISIBLE NONE;ct01 ct01 VISIBLE NONE;ct02 ct02 VISIBLE NONE;cd01 cd01 VISIBLE NONE;cd02 cd02 VISIBLE NONE;cd03 cd03 VISIBLE NONE;cd04 cd04 VISIBLE NONE;cs01 cs01 VISIBLE NONE;cs02 cs02 VISIBLE NONE;cfa01 cfa01 VISIBLE NONE;cfa02 cfa02 VISIBLE NONE;cfa03 cfa03 VISIBLE NONE;cfa04 cfa04 VISIBLE NONE;cfa05 cfa05 VISIBLE NONE;cfs01 cfs01 VISIBLE NONE;cfs02 cfs02 VISIBLE NONE;cfs03 cfs03 VISIBLE NONE;cfs04 cfs04 VISIBLE NONE;cfs05 cfs05 VISIBLE NONE;emp_dens emp_dens VISIBLE NONE"
)
print "- Add Emp Dens Field"
# Process: Add Field
arcpy.AddField_management(valid_trcts, "EMP_DENS", "DOUBLE", "", "", "",
"", "NULLABLE", "NON_REQUIRED", "")
print "- Compute Emp Dens"
# Process: Calculate Field
arcpy.CalculateField_management(valid_trcts, "emp_dens", "[ca01]/ [AREA]",
"VB", "")
print "- Employment Clusters - 500 m"
# Process: Hot Spot Analysis (Getis-Ord Gi*)
arcpy.HotSpots_stats(valid_trcts, "emp_dens", uat_emp_hspt,
"FIXED_DISTANCE_BAND", "EUCLIDEAN_DISTANCE", "NONE",
"500", "", "")
# Process: Generate Spatial Weights Matrix
arcpy.GenerateSpatialWeightsMatrix_stats(LondonWards, "ID", contig_swm,
"CONTIGUITY_EDGES_CORNERS",
"EUCLIDEAN", "1", "", "0",
"ROW_STANDARDIZATION", "", "", "", "")
# Process: Cluster and Outlier Analysis (Anselin Local Morans I)
arcpy.ClustersOutliers_stats(LondonWards, "AvgGCSE201", MoransContig,
"GET_SPATIAL_WEIGHTS_FROM_FILE",
"EUCLIDEAN_DISTANCE", "NONE", "", contig_swm,
"NO_FDR")
# Process: Hot Spot Analysis (Getis-Ord Gi*)
arcpy.HotSpots_stats(LondonWards, "AvgGCSE201", Gearys_Contig,
"GET_SPATIAL_WEIGHTS_FROM_FILE", "EUCLIDEAN_DISTANCE",
"NONE", "", "", contig_swm, "NO_FDR")
# Process: Generate Spatial Weights Matrix (3)
arcpy.GenerateSpatialWeightsMatrix_stats(LondonWards, "ID", invidist_swm,
"INVERSE_DISTANCE", "EUCLIDEAN", "1",
"", "0", "ROW_STANDARDIZATION", "",
"", "", "")
# Process: Hot Spot Analysis (Getis-Ord Gi*) (2)
arcpy.HotSpots_stats(LondonWards, "AvgGCSE201", Geary_Individist,
"GET_SPATIAL_WEIGHTS_FROM_FILE", "EUCLIDEAN_DISTANCE",
"NONE", "", "", invidist_swm, "NO_FDR")
# Process: Generate Spatial Weights Matrix (2)
arcpy.GenerateSpatialWeightsMatrix_stats(LondonWards, "ID", neighbour_swm,
#arcpy.CopyFeatures_management(layer_acs, ua_lehd_acs)
print "- Add Emp Dens Field"
# Process: Add Field
arcpy.AddField_management(ua_lehd_acs, "EMP_DENS", "DOUBLE", "", "",
"", "", "NULLABLE", "NON_REQUIRED", "")
print "- Compute Emp Dens"
# Process: Calculate Field
arcpy.CalculateField_management(ua_lehd_acs, "emp_dens",
"[ca01]/ [AREA]", "VB", "")
print "- Employment Clusters - 500 m"
# Process: Hot Spot Analysis (Getis-Ord Gi*)
arcpy.HotSpots_stats(ua_lehd_acs, "emp_dens", uat_emp_hspt,
"FIXED_DISTANCE_BAND", "EUCLIDEAN_DISTANCE",
"NONE", "500", "", "")
#print "- Income and Race Clusters - 2500 m"
# Process: Hot Spot Analysis (Getis-Ord Gi*)
#arcpy.HotSpots_stats(valid_trcts, "income_hh_", uat_inc_hspt, "ZONE_OF_INDIFFERENCE", "EUCLIDEAN_DISTANCE", "NONE", "2500", "", "")
#arcpy.HotSpots_stats(valid_trcts, "perc_white", uat_pw_hspt, "ZONE_OF_INDIFFERENCE", "EUCLIDEAN_DISTANCE", "NONE", "2500", "", "")
##MODULE 3
print "- High Density Select"
name_select = "\"GiZScore\" > 2.58"
arcpy.MakeFeatureLayer_management(uat_emp_hspt, uat_hspt_hi,
name_select)