def get_nogrowthmaps(urllist):
"""getNoGrowthLayers - downloads 0 or more shapefiles, convert
them to raster and merge into the noGrowth layers
To use grass GIS to import vector file requires a new folder
to be created, and such folder name exist(error and fail otherwise).
v.in.org
Thus, each time during import, a tmp folder name is given.
# To run this, a Temp directory should be created.
"""
runlog.p("--import nogrowth layers......")
# importNoGrowth -- overlay multiple nogrowth maps into a initial blank one
script = './bin/importNoGrowth'
logname = './Log/' + os.path.basename(script) + '.log'
createdirectorynotexist('./Temp/')
shplist = []
for url in urllist:
layername = get_shapefile(url, flag=1)
import_vectormap(layername, layer='nogrowth')
vec2rast('nogrowth')
layername = os.path.basename(layername)
shplist.append('"%s"' % layername)
check_call('%s %s > %s 2>&1' % (script, ' '.join(shplist), logname),
shell=True)
def frequencyanalysis_cost(cost_res_arr, cost_arr, cost_arr_x, RESCOM, COSTFREQ,
COSTMAX, COSTBASE, CST=CST):
xlen = len(cost_arr_x)
cost_res_arr_nb = cost_res_arr[(cost_res_arr < COSTMAX)&(cost_res_arr > COSTBASE)]
print "NUM COST " + RESCOM + " CELLS CONSIDERED: ", len(cost_res_arr_nb)
cost_res_arr_nbsort = np.sort(cost_res_arr_nb)
cost_res_basketsize_last = len(cost_res_arr[cost_res_arr == COSTMAX])
cost_res_freq = []
cost_arr_freq = []
cur1 = cost_arr_x[0]
for i in xrange(1, xlen): #i is for cur2. in total ATTRBASKETNUM baskets.
cur2 = cost_arr_x[i]
mask = (cost_res_arr >= cur1) & (cost_res_arr < cur2)
cost_res_freq.append(len(cost_res_arr[mask]))
mask = (cost_arr >= cur1) & (cost_arr < cur2)
cost_arr_freq.append(len(cost_arr[mask]))
cur1 = cur2
cost_res_freq.append(len(cost_res_arr[cost_res_arr >= cur1]))
cost_arr_freq.append(len(cost_arr[cost_arr >= cur1]))
print "---------------------cost_"+RESCOM.lower()+"_freq----------------\n",[int(i) for i in cost_res_freq]
print "---------------------cost_arr_freq----------------\n",[int(i) for i in cost_arr_freq]
cost_res_y = np.divide(cost_res_freq, cost_arr_freq, dtype=np.float)
cost_res_y = np.nan_to_num(cost_res_y)
cost_res_y[cost_res_y > 100] = 100
print "---------------------cost_"+RESCOM.lower()+"_y----------------\n",cost_res_y
outgraphfname = COSTFREQ[:-4]+"-"+str(sys.argv[2])+".png"
outdatafname = COSTFREQ[:-4]+"-"+str(sys.argv[2])+".csv"
createdirectorynotexist(outgraphfname)
plotgraph(cost_arr_x, cost_res_y, xlen, outgraphfname, RESCOM, CST)
print outdatafname
outdata_arr = np.asarray([cost_arr_x, cost_res_freq, cost_arr_freq, cost_res_y])
outdata_arr = np.transpose(outdata_arr)
np.savetxt(outdatafname, outdata_arr, fmt='%5.5f',delimiter=',',
header="x,res/com,original,y", comments='')
def frequencyanalysis_attr(attr_res_arr, attr_arr, attr_arr_x, attrbasketsize_1st, RESCOM, ATTRFREQ,
ATT=ATT, ATTRBASKETNUM=ATTRBASKETNUM, ATTRBASE=ATTRBASE):
attr_res_arr_nobase = attr_res_arr[attr_res_arr > ATTRBASE]
print "NUM RES CELLS CONSIDERED: ", len(attr_res_arr_nobase)
attr_res_arr_nbsort = np.sort(attr_res_arr_nobase)
attr_res_basketsize_1st = len(attr_res_arr[attr_res_arr == ATTRBASE])
attr_res_freq = [attr_res_basketsize_1st]
attr_arr_freq = [attrbasketsize_1st]
cur1 = attr_arr_x[1]
for i in xrange(2, ATTRBASKETNUM+1): #i is for cur2. in total ATTRBASKETNUM baskets.
cur2 = attr_arr_x[i]
mask = (attr_res_arr >= cur1) & (attr_res_arr < cur2)
attr_res_freq = np.append(attr_res_freq, len(attr_res_arr[mask]))
mask = (attr_arr >= cur1) & (attr_arr < cur2)
attr_arr_freq = np.append(attr_arr_freq, len(attr_arr[mask]))
cur1 = cur2
attr_res_freq = np.append(attr_res_freq, len(attr_res_arr[attr_res_arr >= cur1]))
attr_arr_freq = np.append(attr_arr_freq, len(attr_arr[attr_arr >= cur1]))
print "---------------------attr_com_freq----------------\n",attr_res_freq.astype(np.int)
print "---------------------attr_arr_freq----------------\n",attr_arr_freq.astype(np.int)
attr_res_y = np.divide(attr_res_freq*1.0, attr_arr_freq)
attr_res_y = np.nan_to_num(attr_res_y)
print "---------------------attr_com_y----------------\n",attr_res_y
outgraphfname = ATTRFREQ[:-4]+"-"+str(ATTRBASKETNUM)+".png"
outdatafname = ATTRFREQ[:-4]+"-"+str(ATTRBASKETNUM)+".csv"
createdirectorynotexist(outgraphfname)
plotgraph(attr_arr_x, attr_res_y, ATTRBASKETNUM, outgraphfname, RESCOM, ATT)
outdata_arr = np.asarray([attr_arr_x, attr_res_freq, attr_arr_freq, attr_res_y])
outdata_arr = np.transpose(outdata_arr)
np.savetxt(outdatafname, outdata_arr,fmt='%5.5f',delimiter=',',
header="x,res/com,original,y", comments='')
def frequencyanalysis_attr(attr_res_arr, attr_arr, attr_arr_x, RESCOM, ATTRFREQ,
ATTRBASE, ATT=ATT):
xlen = len(attr_arr_x)
attr_res_arr_nb = attr_res_arr[attr_res_arr > ATTRBASE]
print "NUM ATTR " + RESCOM + " CELLS CONSIDERED: ", len(attr_res_arr_nb)
attr_res_arr_nbsort = np.sort(attr_res_arr_nb)
attr_res_basketsize_1st = len(attr_res_arr[attr_res_arr == ATTRBASE])
attr_basketsize_1st = len(attr_arr [attr_arr == ATTRBASE])
attr_res_freq = [attr_res_basketsize_1st]
attr_arr_freq = [attr_basketsize_1st]
cur1 = attr_arr_x[1]
for i in xrange(2, xlen): #i is for cur2. in total ATTRBASKETNUM baskets.
cur2 = attr_arr_x[i]
mask = (attr_res_arr > cur1) & (attr_res_arr <= cur2)
attr_res_freq.append(len(attr_res_arr[mask]))
mask = (attr_arr > cur1) & (attr_arr <= cur2)
attr_arr_freq.append(len(attr_arr[mask]))
cur1 = cur2
attr_res_freq.append(len(attr_res_arr[attr_res_arr > cur1]))
attr_arr_freq.append(len(attr_arr[attr_arr > cur1]))
print "---------------------attr_"+RESCOM.lower()+"_freq----------------\n",[int(i) for i in attr_res_freq]
print "---------------------attr_arr_freq----------------\n",[int(i) for i in attr_arr_freq]
attr_res_y = np.divide(attr_res_freq, attr_arr_freq, dtype=np.float)
attr_res_y = np.nan_to_num(attr_res_y)
print "---------------------attr_"+RESCOM.lower()+"_y----------------\n",attr_res_y
outgraphfname = ATTRFREQ[:-4]+"-"+str(sys.argv[1])+".png"
outdatafname = ATTRFREQ[:-4]+"-"+str(sys.argv[1])+".csv"
createdirectorynotexist(outgraphfname)
plotgraph(attr_arr_x, attr_res_y, xlen, outgraphfname, RESCOM, ATT)
outdata_arr = np.asarray([attr_arr_x, attr_res_freq, attr_arr_freq, attr_res_y])
outdata_arr = np.transpose(outdata_arr)
np.savetxt(outdatafname, outdata_arr,fmt='%5.5f',delimiter=',',
header="x,res/com,original,y", comments='')
def frequencyanalysis_cost(cost_res_arr,
cost_arr,
cost_arr_x,
RESCOM,
COSTFREQ,
CST=CST,
COSTBASKETNUM=COSTBASKETNUM,
COSTMAX=COSTMAX,
COSTBASE=COSTBASE):
cost_res_arr_nobase = cost_res_arr[(cost_res_arr < COSTMAX)
& (cost_res_arr > COSTBASE)]
print "NUM RES CELLS CONSIDERED: ", len(cost_res_arr_nobase)
cost_res_arr_nbsort = np.sort(cost_res_arr_nobase)
cost_res_basketsize_last = len(cost_res_arr[cost_res_arr == COSTMAX])
cost_res_freq = []
cost_arr_freq = []
cur1 = cost_arr_x[0]
xlen = len(cost_arr_x)
for i in xrange(1, xlen): #i is for cur2. in total ATTRBASKETNUM baskets.
cur2 = cost_arr_x[i]
mask = (cost_res_arr >= cur1) & (cost_res_arr < cur2)
cost_res_freq = np.append(cost_res_freq, len(cost_res_arr[mask]))
mask = (cost_arr >= cur1) & (cost_arr < cur2)
cost_arr_freq = np.append(cost_arr_freq, len(cost_arr[mask]))
cur1 = cur2
mask = (cost_res_arr >= cur1) & (cost_res_arr < COSTMAX)
cost_res_freq = np.append(cost_res_freq, len(cost_res_arr[mask]))
mask = (cost_arr >= cur1) & (cost_arr < COSTMAX)
cost_arr_freq = np.append(cost_arr_freq, len(cost_arr[mask]))
#cost_res_freq = np.append(cost_res_freq, cost_res_basketsize_last)
#cost_arr_freq = np.append(cost_arr_freq, costbasketsize_last)
print "---------------------cost_res_freq----------------\n", cost_res_freq.astype(
np.int)
print "---------------------cost_arr_freq----------------\n", cost_arr_freq.astype(
np.int)
cost_res_y = np.divide(cost_res_freq, cost_arr_freq)
cost_res_y = np.nan_to_num(cost_res_y)
cost_res_y[cost_res_y > 100] = 100
print "---------------------cost_res_y----------------\n", cost_res_y
outgraphfname = COSTFREQ[:-4] + "-" + str(COSTBASKETNUM) + ".png"
outdatafname = COSTFREQ[:-4] + "-" + str(COSTBASKETNUM) + ".csv"
createdirectorynotexist(outgraphfname)
plotgraph(cost_arr_x, cost_res_y, COSTBASKETNUM, outgraphfname, RESCOM,
CST)
print outdatafname
outdata_arr = np.asarray(
[cost_arr_x, cost_res_freq, cost_arr_freq, cost_res_y])
outdata_arr = np.transpose(outdata_arr)
np.savetxt(outdatafname,
outdata_arr,
fmt='%5.5f',
delimiter=',',
header="x,res/com,original,y",
comments='')
def _init_logger(self, name, level=logging.DEBUG, fname='./Log/run.log'):
logger = logging.getLogger(name)
logger.setLevel(level)
createdirectorynotexist(fname)
handler = logging.FileHandler(fname, mode='w')
handler.setLevel(level)
formatter = logging.Formatter('%(asctime)s - %(levelname)s - %(message)s')
handler.setFormatter(formatter)
logger.addHandler(handler)
return logger
def _init_logger(self, name, level=logging.DEBUG, fname='./Log/run.log'):
logger = logging.getLogger(name)
logger.setLevel(level)
createdirectorynotexist(fname)
handler = logging.FileHandler(fname, mode='w')
handler.setLevel(level)
formatter = logging.Formatter(
'%(asctime)s - %(levelname)s - %(message)s')
handler.setFormatter(formatter)
logger.addHandler(handler)
return logger
def writeDemand(yearincrpoplist, yearincremplist, title, filename=DEMANDGRAPH):
# concatenate the year, population to string to demand.graph file.
outstrlist = ['# %s\n\nPopulation\n' % title]
for yr, pop in yearincrpoplist:
outstrlist.append('%s, %s\n' % (str(yr), str(pop)))
outstrlist.append('\n\nEmployment\n')
for yr, emp in yearincremplist:
outstrlist.append('%s, %s\n' % (str(yr), str(emp)))
createdirectorynotexist(filename)
with open(filename, 'w') as f:
f.write(''.join(outstrlist))
def writeDemand(yearincrpoplist, yearincremplist, title,
filename=DEMANDGRAPH):
# concatenate the year, population to string to demand.graph file.
outstrlist = ['# %s\n\nPopulation\n'%title]
for yr, pop in yearincrpoplist:
outstrlist.append('%s, %s\n' % (str(yr), str(pop)))
outstrlist.append('\n\nEmployment\n')
for yr, emp in yearincremplist:
outstrlist.append('%s, %s\n' % (str(yr), str(emp)))
createdirectorynotexist(filename)
with open(filename, 'w') as f:
f.write(''.join(outstrlist))
def get_shapefile(url, downloaddir='./Inputs', flag = 0):
"""Download zipped shape file from the url to downloaddir
@output: name of the shapefile with downloaddir and unzipped folder
"""
# Note: we currently read the entire uncompressed content of
# a file into a string and then write it to file. Python 2.6
# provides a mechanssm for reading files piecemeal.
try:
if url.startswith('file://'):
z = ZipFile(url.replace('file://',''))
else:
z = ZipFile(site.getURL(url))
except BadZipfile:
raise RuntimeError('%s is not zip file' % url)
# processes each file in the zipfile because embedded
# directories are also part of the namelist we exclude
# any filename ending with a trailing slash
shapefile = None
for zname in z.namelist():
if zname.endswith('/'):
continue
else:
fname = os.path.basename(zname)
#shapefolder = fname.split('.')[0]
#print "test shapefolder" + shapefolder
if flag == 0:
shapefolder = fname.split('.')[0]
print "test shapefolder" + shapefolder
else:
shapefolder = "nogrowth"
print "test shapefolder" + shapefolder
fname = '%s/%s/%s' %(downloaddir, shapefolder, fname)
if fname.endswith('.shp'):
shapefile = fname
createdirectorynotexist(fname)
with open(fname, 'wb') as f:
content = z.read(zname)
f.write(content)
if not shapefile:
raise RuntimeError('%s did not contain a shapefile' % url)
# print shapefile name
print "sharefolder is " + shapefolder
print "fname is " + fname
print "shapefile is" + shapefile
return shapefile
def get_shapefile(url, downloaddir='./Inputs', flag=0):
"""Download zipped shape file from the url to downloaddir
@output: name of the shapefile with downloaddir and unzipped folder
"""
# Note: we currently read the entire uncompressed content of
# a file into a string and then write it to file. Python 2.6
# provides a mechanssm for reading files piecemeal.
try:
if url.startswith('file://'):
z = ZipFile(url.replace('file://', ''))
else:
z = ZipFile(site.getURL(url))
except BadZipfile:
raise RuntimeError('%s is not zip file' % url)
# processes each file in the zipfile because embedded
# directories are also part of the namelist we exclude
# any filename ending with a trailing slash
shapefile = None
for zname in z.namelist():
if zname.endswith('/'):
continue
else:
fname = os.path.basename(zname)
#shapefolder = fname.split('.')[0]
#print "test shapefolder" + shapefolder
if flag == 0:
shapefolder = fname.split('.')[0]
print "test shapefolder" + shapefolder
else:
shapefolder = "nogrowth"
print "test shapefolder" + shapefolder
fname = '%s/%s/%s' % (downloaddir, shapefolder, fname)
if fname.endswith('.shp'):
shapefile = fname
createdirectorynotexist(fname)
with open(fname, 'wb') as f:
content = z.read(zname)
f.write(content)
if not shapefile:
raise RuntimeError('%s did not contain a shapefile' % url)
# print shapefile name
print "sharefolder is " + shapefolder
print "fname is " + fname
print "shapefile is" + shapefile
return shapefile
def frequencyanalysis_attr(attr_res_arr,
attr_arr,
attr_arr_x,
attrbasketsize_1st,
RESCOM,
ATTRFREQ,
ATT=ATT,
ATTRBASKETNUM=ATTRBASKETNUM,
ATTRBASE=ATTRBASE):
attr_res_arr_nobase = attr_res_arr[attr_res_arr > ATTRBASE]
print "NUM RES CELLS CONSIDERED: ", len(attr_res_arr_nobase)
attr_res_arr_nbsort = np.sort(attr_res_arr_nobase)
attr_res_basketsize_1st = len(attr_res_arr[attr_res_arr == ATTRBASE])
attr_res_freq = [attr_res_basketsize_1st]
attr_arr_freq = [attrbasketsize_1st]
cur1 = attr_arr_x[1]
for i in xrange(2, ATTRBASKETNUM +
1): #i is for cur2. in total ATTRBASKETNUM baskets.
cur2 = attr_arr_x[i]
mask = (attr_res_arr >= cur1) & (attr_res_arr < cur2)
attr_res_freq = np.append(attr_res_freq, len(attr_res_arr[mask]))
mask = (attr_arr >= cur1) & (attr_arr < cur2)
attr_arr_freq = np.append(attr_arr_freq, len(attr_arr[mask]))
cur1 = cur2
attr_res_freq = np.append(attr_res_freq,
len(attr_res_arr[attr_res_arr >= cur1]))
attr_arr_freq = np.append(attr_arr_freq, len(attr_arr[attr_arr >= cur1]))
print "---------------------attr_com_freq----------------\n", attr_res_freq.astype(
np.int)
print "---------------------attr_arr_freq----------------\n", attr_arr_freq.astype(
np.int)
attr_res_y = np.divide(attr_res_freq * 1.0, attr_arr_freq)
attr_res_y = np.nan_to_num(attr_res_y)
print "---------------------attr_com_y----------------\n", attr_res_y
outgraphfname = ATTRFREQ[:-4] + "-" + str(ATTRBASKETNUM) + ".png"
outdatafname = ATTRFREQ[:-4] + "-" + str(ATTRBASKETNUM) + ".csv"
createdirectorynotexist(outgraphfname)
plotgraph(attr_arr_x, attr_res_y, ATTRBASKETNUM, outgraphfname, RESCOM,
ATT)
outdata_arr = np.asarray(
[attr_arr_x, attr_res_freq, attr_arr_freq, attr_res_y])
outdata_arr = np.transpose(outdata_arr)
np.savetxt(outdatafname,
outdata_arr,
fmt='%5.5f',
delimiter=',',
header="x,res/com,original,y",
comments='')
def main(argv):
start = time.time()
cellnum = int(sys.argv[1])
if cellnum >= 100:
print "Error: the cellnum choice should be less than 100"
exit(0)
# read only one popcenter specified by cellnum from popcenterlist
with open(CENTERLIST, 'r') as p:
popcenterlist = p.readlines()
(disW, disN, weight) = popcenterlist[cellnum].strip('\n').split(',')
print disW, disN, weight
# redirect stdout to log file
logname = TRAVELCOSTPATH + "/cell_" + disW + "_" + disN + "/log.txt"
createdirectorynotexist(logname)
sys.stdout = open(logname, 'w')
RandomWalk(int(disW), int(disN)) #distW, distN
end = time.time()
print(end - start)
def main(argv):
start = time.time()
cellnum = int(sys.argv[1])
if cellnum >= 100:
print "Error: the cellnum choice should be less than 100"
exit(0)
# read only one popcenter specified by cellnum from popcenterlist
with open(CENTERLIST, 'r') as p:
popcenterlist = p.readlines()
(disW, disN, weight) = popcenterlist[cellnum].strip('\n').split(',')
print disW, disN, weight
# redirect stdout to log file
logname = TRAVELCOSTPATH+"/cell_" + disW + "_" + disN + "/log.txt"
createdirectorynotexist(logname)
sys.stdout = open(logname, 'w')
RandomWalk(int(disW),int(disN)) #distW, distN
end = time.time()
print (end-start)
def frequencyanalysis_cost(cost_res_arr, cost_arr, cost_arr_x, RESCOM, COSTFREQ,
CST=CST, COSTBASKETNUM=COSTBASKETNUM, COSTMAX=COSTMAX, COSTBASE=COSTBASE):
cost_res_arr_nobase = cost_res_arr[(cost_res_arr < COSTMAX)&(cost_res_arr > COSTBASE)]
print "NUM RES CELLS CONSIDERED: ", len(cost_res_arr_nobase)
cost_res_arr_nbsort = np.sort(cost_res_arr_nobase)
cost_res_basketsize_last = len(cost_res_arr[cost_res_arr == COSTMAX])
cost_res_freq = []
cost_arr_freq = []
cur1 = cost_arr_x[0]
xlen = len(cost_arr_x)
for i in xrange(1, xlen): #i is for cur2. in total ATTRBASKETNUM baskets.
cur2 = cost_arr_x[i]
mask = (cost_res_arr >= cur1) & (cost_res_arr < cur2)
cost_res_freq = np.append(cost_res_freq, len(cost_res_arr[mask]))
mask = (cost_arr >= cur1) & (cost_arr < cur2)
cost_arr_freq = np.append(cost_arr_freq, len(cost_arr[mask]))
cur1 = cur2
mask = (cost_res_arr >= cur1) & (cost_res_arr < COSTMAX)
cost_res_freq = np.append(cost_res_freq, len(cost_res_arr[mask]))
mask = (cost_arr >= cur1) & (cost_arr < COSTMAX)
cost_arr_freq = np.append(cost_arr_freq, len(cost_arr[mask]))
#cost_res_freq = np.append(cost_res_freq, cost_res_basketsize_last)
#cost_arr_freq = np.append(cost_arr_freq, costbasketsize_last)
print "---------------------cost_res_freq----------------\n",cost_res_freq.astype(np.int)
print "---------------------cost_arr_freq----------------\n",cost_arr_freq.astype(np.int)
cost_res_y = np.divide(cost_res_freq, cost_arr_freq)
cost_res_y = np.nan_to_num(cost_res_y)
cost_res_y[cost_res_y > 100] = 100
print "---------------------cost_res_y----------------\n",cost_res_y
outgraphfname = COSTFREQ[:-4]+"-"+str(COSTBASKETNUM)+".png"
outdatafname = COSTFREQ[:-4]+"-"+str(COSTBASKETNUM)+".csv"
createdirectorynotexist(outgraphfname)
plotgraph(cost_arr_x, cost_res_y, COSTBASKETNUM, outgraphfname, RESCOM, CST)
print outdatafname
outdata_arr = np.asarray([cost_arr_x, cost_res_freq, cost_arr_freq, cost_res_y])
outdata_arr = np.transpose(outdata_arr)
np.savetxt(outdatafname, outdata_arr, fmt='%5.5f',delimiter=',',
header="x,res/com,original,y", comments='')
def get_nogrowthmaps(urllist):
"""getNoGrowthLayers - downloads 0 or more shapefiles, convert
them to raster and merge into the noGrowth layers
To use grass GIS to import vector file requires a new folder
to be created, and such folder name exist(error and fail otherwise).
v.in.org
Thus, each time during import, a tmp folder name is given.
# To run this, a Temp directory should be created.
"""
runlog.p("--import nogrowth layers......")
script = './bin/importNoGrowth'
logname = './Log/'+ os.path.basename(script)+'.log'
createdirectorynotexist('./Temp/')
shplist = []
for url in urllist:
layername = get_shapefile(url, flag=1)
layername = os.path.basename(layername)
shplist.append('"%s"' % layername)
check_call('%s %s > %s 2>&1' % (script, ' '.join(shplist), logname),
shell=True)
