def compute_hotspots(city_id):
print 'Computing Moran index for', city_id
shpfile = os.path.join(LATLNGS_SHP_DIR, str(city_id) + '.shp')
moran_index = arcpy.SpatialAutocorrelation_stats(
shpfile, 'price', 'NO_REPORT', 'INVERSE_DISTANCE_SQUARED',
'EUCLIDEAN DISTANCE', 'NONE', '100', '#')
print 'FINISHED %s!' % city_id
return moran_index
ols = arcpy.OrdinaryLeastSquares_stats(
"C:\\MyUW\\SummerProject1\\censusjoin.shp", "OID_",
"C:\\MyUW\\SummerProject1\\olsResults.shp", "canrate", "MEAN")
# Create Spatial Weights Matrix (Can be based off input or output FC)
# Process: Generate Spatial Weights Matrix...
swm = arcpy.GenerateSpatialWeightsMatrix_stats(
"C:\\MyUW\\SummerProject1\\censusjoin.shp", "OID_",
"C:\\MyUW\\SummerProject1\\euclidean6Neighs.swm",
"K_NEAREST_NEIGHBORS", "#", "#", "#", 6)
# Calculate Moran's Index of Spatial Autocorrelation for
# OLS Residuals using a SWM File.
# Process: Spatial Autocorrelation (Morans I)...
moransI = arcpy.SpatialAutocorrelation_stats(
"C:\\MyUW\\SummerProject1\\olsResults.shp", "Residual",
"NO_REPORT", "GET_SPATIAL_WEIGHTS_FROM_FILE", "EUCLIDEAN_DISTANCE",
"NONE", "#", "C:\\MyUW\\SummerProject1\\euclidean6Neighs.swm")
except:
# If an error occurred when running the tool, print out the error message.
print(arcpy.GetMessages())
# Setup a new map document for the OLS results
mxdols = arcpy.mapping.MapDocument(r"C:\\MyUW\\SummerProject1\\olsmap.mxd")
dfols = arcpy.mapping.ListDataFrames(mxdols, "Layers")[0]
# Make the OLS output a layer and add it to the mxd
# Also give the layer the symbology of an existing layer
olsResults = arcpy.mapping.Layer(
r"C:\\MyUW\\SummerProject1\\olsResults.shp")
olsSymbology = "C:\\MyUW\\SummerProject1\\ols_symbology.lyr"
tempEnvironment42 = arcpy.env.mask
arcpy.env.mask = ""
tempEnvironment43 = arcpy.env.spatialGrid3
arcpy.env.spatialGrid3 = "0"
tempEnvironment44 = arcpy.env.maintainSpatialIndex
arcpy.env.maintainSpatialIndex = "false"
tempEnvironment45 = arcpy.env.workspace
arcpy.env.workspace = "C:\\Users\\sfrazier\\Documents\\ArcGIS\\Default.gdb"
tempEnvironment46 = arcpy.env.MResolution
arcpy.env.MResolution = ""
tempEnvironment47 = arcpy.env.derivedPrecision
arcpy.env.derivedPrecision = "HIGHEST"
tempEnvironment48 = arcpy.env.ZTolerance
arcpy.env.ZTolerance = ""
arcpy.SpatialAutocorrelation_stats(OLSResults_shp, "Residual",
"GENERATE_REPORT", "INVERSE_DISTANCE",
"EUCLIDEAN_DISTANCE", "NONE", "", "")
arcpy.env.newPrecision = tempEnvironment0
arcpy.env.autoCommit = tempEnvironment1
arcpy.env.XYResolution = tempEnvironment2
arcpy.env.processingServerUser = tempEnvironment3
arcpy.env.XYDomain = tempEnvironment4
arcpy.env.processingServerPassword = tempEnvironment5
arcpy.env.scratchWorkspace = tempEnvironment6
arcpy.env.cartographicPartitions = tempEnvironment7
arcpy.env.terrainMemoryUsage = tempEnvironment8
arcpy.env.MTolerance = tempEnvironment9
arcpy.env.compression = tempEnvironment10
arcpy.env.coincidentPoints = tempEnvironment11
arcpy.env.randomGenerator = tempEnvironment12
arcpy.env.outputCoordinateSystem = tempEnvironment13
## # Growth as a function of {log of starting income, dummy for South
## # counties, interaction term for South counties, population density}
## # Process: Ordinary Least Squares...
## ols = arcpy.OrdinaryLeastSquares_stats("USCounties.shp", "MYID",
## "olsResults.shp", "GROWTH",
## "LOGPCR69;SOUTH;LPCR_SOUTH;PopDen69",
## "olsCoefTab.dbf",
## "olsDiagTab.dbf")
##
##
## # Calculate Moran's I Index of Spatial Autocorrelation for
## # OLS Residuals using a SWM File.
## # Process: Spatial Autocorrelation (Morans I)...
moransI = arcpy.SpatialAutocorrelation_stats(r"C:\Users\sfrazier\Desktop\Geog777\Project1\olsResults1.shp",
"Residual", "GENERATE_REPORT", "INVERSE_DISTANCE",
"EUCLIDEAN_DISTANCE", "NONE", "","")
print ("at the bottom")
####except:
#### # If an error occurred when running the tool, print out the error message.
#### print(arcpy.GetMessages())
#-------------------------------------------------------------------------------------------
##refLyr = m.listLayers("Points of Interest")[0]
##m.insertLayer(refLyr, insertLyr, "BEFORE")
#aprx.saveACopy(r"C:\Projects\YosemiteNP\Yosemite_updated.aprx")
#aprx.save()
del aprx
def run(*args):
try:
#setup workspace
env.workspace = r"C:\Users\sfrazier\Desktop\GEOG777\Project1"
env.overwriteOutput = True
#Set arcGIS Pro project location - will be used throughout script.
aprx = arcpy.mp.ArcGISProject(
r"C:\Users\sfrazier\Desktop\GEOG777\Project1\Project1\Project1.aprx"
)
# Set local variables for the IDW tool
inPointFeatures = r"\well_nitrate\well_nitrate_WTM.shp"
zField = "nitr_ran"
##cellSize = 2000.0
power = float(powerEntry.get())
searchRadius = RadiusVariable(10, )
powerText = str(power)
messagebox.showinfo("Running", "The analysis has begun using "+powerText+" for the power\n lease"\
" wait for the IDW process to complete.")
# Execute IDW
outIDW = Idw(inPointFeatures, zField, '', power, searchRadius)
## Save the output IDW as a Tiff
outIDW.save(
r"C:\Users\sfrazier\Desktop\GEOG777\Project1\outputFiles\idwout.tif"
)
#Set variables for building the IDW jpeg map
idwTif = r"C:\Users\sfrazier\Desktop\GEOG777\Project1\outputFiles\idwout.tif"
# Locating the first map in the project
map1 = aprx.listMaps('IDWMap')[0]
map1.addDataFromPath(
r"C:\Users\sfrazier\Desktop\GEOG777\Project1\outputFiles\idwout.tif"
)
#define the Layers
refLay = map1.listLayers()[0]
#print("no name: " +refLay.name)
moveLay = map1.listLayers()[1]
#print(moveLay.name)
#Apply symbology to the IDW raster
sybLyr = r"C:\Users\sfrazier\Desktop\Geog777\Project1\outputFiles\idwout.lyrx"
#apply symbology for the output raster
arcpy.ApplySymbologyFromLayer_management(refLay, sybLyr)
#rearrange the layers in the map to move the tracts above the raster.
map1.moveLayer(refLay, moveLay, 'BEFORE')
#locate correct layout to export the map
lyt = aprx.listLayouts()[1]
lyt.exportToJPEG(
r"C:\Users\sfrazier\Desktop\Geog777\Project1\Images\Idw.jpg")
#message box to let user know process has completed the IDW
messagebox.showinfo(
"Completed IDW",
"Completed IDW Interpolation.\n OLS process is now running.")
#activate display IDW map button
idwDisplay.config(state=NORMAL)
# Set local variables for zonal join
idwTif = r"C:\Users\sfrazier\Desktop\GEOG777\Project1\outputFiles\idwout.tif"
inZoneData = r"cancer_tracts\cancer_tracts_WTM.shp"
zoneField = "GEOID10"
inValueRaster = idwTif
outTable = "zonalstat"
# Execute ZonalStatisticsAsTable
outZSaT = ZonalStatisticsAsTable(inZoneData, zoneField, inValueRaster,
outTable, "DATA", "MEAN")
#set the environment setting
arcpy.env.qualifiedFieldNames = False
# Set local variables for the zonal table to census tracts shapefile
inFeatures = r"\cancer_tracts\cancer_tracts_WTM.shp"
joinTable = "zonalstat"
joinField = "GEOID10"
outFeature = r"outputFiles\Tract_IDW"
# Join the feature layer to a table
canTract_joined_table = arcpy.AddJoin_management(
inFeatures, joinField, joinTable, joinField, "KEEP_COMMON")
# Copy the layer to a new permanent feature class
arcpy.CopyFeatures_management(canTract_joined_table, outFeature)
print("join")
#Location of the Tract IDW.shp
feature = r"C:\Users\sfrazier\Desktop\Geog777\Project1\outputFiles\Tract_IDW.shp"
#run the OLS tool
ols = arcpy.OrdinaryLeastSquares_stats(feature, "Rowid_",
r"outputFiles\olsResults.shp",
"canrate", "MEAN", '', '',
r"outputFiles\olsTable.pdf")
print("we got to the OLS")
#Load data into OLS Map
olsRes = r"C:\Users\sfrazier\Desktop\Geog777\Project1\outputFiles\olsResults.shp"
map2 = aprx.listMaps("OLS")[0]
map2.addDataFromPath(olsRes)
#call the ols layout and export the map
lyt1 = aprx.listLayouts("olsMap")[0]
lyt1.exportToJPEG(
r"C:\Users\sfrazier\Desktop\Geog777\Project1\Images\olsMap.jpg")
#activate the olsDisplay button and show a feedback that OLS is completed
olsDisplay.config(state=NORMAL)
messagebox.showinfo(
"Completed OLS",
"Completed OLS. \nPlease wait for process to complete")
# run morans I
moransI = arcpy.SpatialAutocorrelation_stats(
r"C:\Users\sfrazier\Desktop\Geog777\Project1\outputFiles\olsResults.shp",
"Residual", "GENERATE_REPORT", "INVERSE_DISTANCE",
"EUCLIDEAN_DISTANCE", "NONE", "", "")
#print("completed spatial Process")
# activate ols button
olsDisplay.config(state=NORMAL)
#let user know that process is complete.
messagebox.showinfo("Process Completed", "Process Completed")
except:
#an error check to let user know to enter a number.
messagebox.showwarning(
"Power Error", "Enter a number greater then 1\n for the power")
print("please enter a number value")
# Skipped OLS for now (done by hand earlier). Will revisit.
# Moran's I
# Where Moran's I evaluates whether a pattern is clustered, dispered, or
# random.
# Positive Moran's I values, a p-value less than the desired confidence level and an abs(z-score) greater than the related p-value z score suggests strong spatial autocorrelation and a rejection of the null hypothesis.
arcpy.env.workspace = workspace + r'\\MAUP.gdb'
arcpy.env.overwriteOutput = True
in_layers = ['VanDA_OLS', 'VanCT_OLS']
field = 'Residual'
out_html_list = []
os.chdir(workspace)
for layer in in_layers:
arcpy.SpatialAutocorrelation_stats(layer, field, 'GENERATE_REPORT', 'INVERSE_DISTANCE', 'EUCLIDEAN_DISTANCE', 'NONE', '#')
desc = arcpy.Describe(layer)
layer_name = desc.nameString
out_html_name = 'MoI_{}.html'.format(layer_name)
os.rename(glob.glob(workspace + r'\\MoransI*.html')[0], out_html_name)
out_html_list.append(out_html_name)
print('Completed layer {}'.format(layer_name))
for doc in out_html_list:
soup = BeautifulSoup(open(workspace + r'\\' + doc), 'html.parser')
table = soup.find('table', attrs={'id':'keytable'})
print(table.get_text())
# Layout: This is better done with ArcMap's GUI. Could potentially revisit creating this map programatically, but the script will likely be pretty extensive.
def idw():
#Determine which spatial unit the user chose
selection = unitVar.get()
#Setting up the workspace
arcpy.env.workspace = "C:\\MAMP\\htdocs\\cancerAnalysis\\files"
arcpy.env.overwriteOutput = True
arcpy.CheckOutExtension("Spatial")
#Setting up the variables for the IDW tool
inPoint = "well_nitrate.shp"
zField = "nitr_ran"
power = float(powerEntry.get())
print power
searchRadius = RadiusVariable(10, 150000)
#Run IDW
idwOutPut = Idw(inPoint, zField, "", power, searchRadius)
#Save the output raster
idwOutPut.save("C:\\MAMP\\htdocs\\cancerAnalysis\\project1\\idw.tif")
#Update the mxd to include the IDW raster
mxd = arcpy.mapping.MapDocument(r"C:\\MAMP\\htdocs\\cancerAnalysis\\idwMap.mxd")
dataFrame = arcpy.mapping.ListDataFrames(mxd, "Layers")[0]
#Change the symbology of the IDW raster
idwTiff = arcpy.mapping.Layer(r"C:\\MAMP\\htdocs\\cancerAnalysis\\project1\\idw.tif")
idwSymbology = r"C:\\MAMP\\htdocs\\cancerAnalysis\\project1\\idwSymbology.lyr"
arcpy.ApplySymbologyFromLayer_management(idwTiff, idwSymbology)
#Add newly changed IDW raster to the map
arcpy.mapping.AddLayer(dataFrame, idwTiff, "BOTTOM")
#Export the map
arcpy.mapping.ExportToPNG(mxd, "C:\\MAMP\\htdocs\\cancerAnalysis\\idwResults.png")
del mxd
#Update the county mxd to include the IDW raster
mxd2 = arcpy.mapping.MapDocument(r"C:\\MAMP\\htdocs\\cancerAnalysis\\countyIDWMap.mxd")
dataFrame2 = arcpy.mapping.ListDataFrames(mxd2, "Layers")[0]
arcpy.mapping.AddLayer(dataFrame2, idwTiff, "BOTTOM")
arcpy.mapping.ExportToPNG(mxd2, "C:\\MAMP\\htdocs\\cancerAnalysis\\countyIDWResults.png")
idwDisplay.config(state=NORMAL)
tkMessageBox.showinfo("Completed IDW", "Completed IDW interpolation...")
#Setting up the process for the two different spatial units
if selection == 1:
#Allow overwriting
arcpy.env.overwriteOutput = True
#Setting up the variables for the Zonal Statistics tool
inZone = "cancer_tracts.shp"
zone = "GEOID10"
rasterValue = idwTiff
table = "zonalStatistics.dbf"
#Run the Zonal Statistics tool
outZoneStat = ZonalStatisticsAsTable(inZone, zone, rasterValue, table, "NODATA", "MEAN")
#Join the Zonal Statistics table with the census tracts
try:
#Setting up the variables
inFeatures = "cancer_tracts.shp"
layerName = "cancer_tracts"
joinTable = "zonalStatistics.dbf"
joinField = "GEOID10"
outputFeature = r"C:\\MAMP\\htdocs\\cancerAnalysis\\files\\Result_Testing.gdb\\joinedCensus"
#Make a feature layer from the cancer tracts
arcpy.MakeFeatureLayer_management(inFeatures, layerName)
#Join the feature to the table
arcpy.AddJoin_management(layerName, joinField, joinTable, joinField, "KEEP_COMMON")
#Create a copy of the joined layer
arcpy.CopyFeatures_management(layerName, outputFeature)
tkMessageBox.showinfo("Completed Zonal Statistics", "Completed Zonal Statistics...")
except Exception, e:
import traceback, sys
tb = sys.exc_info()[2]
print "Line %i" % tb.tb_lineno
print e.message
#Run linear regression on the results
try:
#Set the environment to allow to overwrite existing data
arcpy.env.overwriteOutput = True
#Create the tool to run Ordinary Least Squares
ordLeastSq = arcpy.OrdinaryLeastSquares_stats("C:\\MAMP\\htdocs\\cancerAnalysis\\files\\Result_Testing.gdb\\joinedCensus",
"cancer_tracts_ID", "C:\\MAMP\\htdocs\\cancerAnalysis\\files\\Result_Testing.gdb\\olsResults", "cancer_tracts_canrate",
"zonalStatistics_MEAN", "", "C:\\MAMP\\htdocs\\cancerAnalysis\\project1\\olsTable.pdf")
except:
print (arcpy.GetMessages())
moransI = arcpy.SpatialAutocorrelation_stats("C:\\MAMP\\htdocs\\cancerAnalysis\\files\\Result_Testing.gdb\\olsResults",
"Residual", "NO_REPORT", "INVERSE_DISTANCE", "EUCLIDEAN_DISTANCE", "NONE", "", "")
#Get the mxd
olsMXD = arcpy.mapping.MapDocument("C:\\MAMP\\htdocs\\cancerAnalysis\\OLSmap.mxd")
olsDF = arcpy.mapping.ListDataFrames(olsMXD, "Layers")[0]
#Add the OLS output to an mxd and apply symbology
olsResults = arcpy.mapping.Layer(r"C:\\MAMP\\htdocs\\cancerAnalysis\\files\\Result_Testing.gdb\\olsResults")
olsSymbology = r"C:\\MAMP\\htdocs\\cancerAnalysis\\project1\\olsSymbology.lyr"
arcpy.ApplySymbologyFromLayer_management(olsResults, olsSymbology)
arcpy.mapping.AddLayer(olsDF, olsResults, "AUTO_ARRANGE")
#Add the legend to the map
olsLegend = arcpy.mapping.ListLayoutElements(olsMXD, "LEGEND_ELEMENT", "Legend")[0]
olsLegend.autoAdd = True
#Export the mxd
arcpy.mapping.ExportToPNG(olsMXD, "C:\\MAMP\\htdocs\\cancerAnalysis\\olsResults.png")
tkMessageBox.showinfo("Completed OLS", "Completed Ordinary Least Squares..." + "\n\nYou can now view and download the maps")
olsDisplay.config(state=NORMAL)
downloadButton.config(state=NORMAL)
image3 = ImageTk.PhotoImage(file="C:\\MAMP\\htdocs\\cancerAnalysis\\olsResults.png")
mapDisplay.configure(image=image3)
mapDisplay.image = image3
Image.ANTIALIAS
print "Line %i" % tb.tb_lineno
print e.message
#Run linear regression on the results
try:
#Set the environment to allow to overwrite existing data
arcpy.env.overwriteOutput = True
#Create the tool to run Ordinary Least Squares
ordLeastSq = arcpy.OrdinaryLeastSquares_stats("C:\\MAMP\\htdocs\\cancerAnalysis\\files\\Result_Testing.gdb\\joinedCounty",
"zonalStatistics_ZONE_CODE", "C:\\MAMP\\htdocs\\cancerAnalysis\\files\\Result_Testing.gdb\\countyOLSResults", "cancer_county_canrate",
"zonalStatistics_MEAN", "", "C:\\MAMP\\htdocs\\cancerAnalysis\\project1\\countyOLSTable.pdf")
except:
print (arcpy.GetMessages())
moransII = arcpy.SpatialAutocorrelation_stats("C:\\MAMP\\htdocs\\cancerAnalysis\\files\\Result_Testing.gdb\\countyOLSResults",
"Residual", "NO_REPORT", "INVERSE_DISTANCE", "EUCLIDEAN_DISTANCE", "NONE", "", "")
#Get the mxd
olsMXD = arcpy.mapping.MapDocument("C:\\MAMP\\htdocs\\cancerAnalysis\\OLSmap.mxd")
olsDF = arcpy.mapping.ListDataFrames(olsMXD, "Layers")[0]
#Add the OLS output to an mxd and apply symbology
olsResults = arcpy.mapping.Layer(r"C:\\MAMP\\htdocs\\cancerAnalysis\\files\\Result_Testing.gdb\\countyOLSResults")
olsSymbology = r"C:\\MAMP\\htdocs\\cancerAnalysis\\project1\\olsSymbology.lyr"
arcpy.ApplySymbologyFromLayer_management(olsResults, olsSymbology)
arcpy.mapping.AddLayer(olsDF, olsResults, "AUTO_ARRANGE")
#Add the legend to the map
olsLegend = arcpy.mapping.ListLayoutElements(olsMXD, "LEGEND_ELEMENT", "Legend")[0]
olsLegend.autoAdd = True