from_int = A_node,
to_int = B_node)
except ObjectDoesNotExist:
mainline_count_location = MainlineCountLocation(on_street = on_street,
on_dir = on_dir,
from_street = from_street,
from_int = A_node,
to_street = to_street,
to_int = B_node)
mainline_count_location.save()
for colname in ['EA_OBS', 'AM_OBS', 'MD_OBS', 'PM_OBS', 'EV_OBS', 'TOT_OBS']:
count = decimal.Decimal(datasheet.cell_value(row, colname_to_colnum[colname]))
if count == 0: continue # zeros are not real
mainline_count = MainlineCount(location = mainline_count_location,
count = count,
count_year = count_year,
start_time = OBS_COL_TO_STARTTIME[colname],
period_minutes = OBS_COL_TO_MINUTES[colname],
vehicle_type = 0,
sourcefile = MTC_COUNTS_FILE_FULLNAME,
project = "mtc",
reference_position = -1,
upload_user = user)
mainline_count.save()
saved_rows += 1
logger.info("Processed %d out of %d rows" % (saved_rows, total_rows))
def readCensusCounts(mapping, census_dirname, user):
"""
Reads the census station count workbooks and inputs those counts into the Count Dracula database.
"""
filenames = sorted(os.listdir(census_dirname))
for filename in filenames:
if filename[-4:] != ".xls":
logger.debug("Skipping non-xls file %s" % filename)
continue
logger.info("Processing PeMS Census file %s" % filename)
filename_parts = filename[:-4].split("_")
pems_id = filename_parts[0]
pems_dir = pems_id[-2:].upper()
pems_id = pems_id.replace("nb", "N")
pems_id = pems_id.replace("sb", "S")
pems_key = ("Census", pems_id)
if pems_key not in mapping:
logger.debug(
"Couldn't find %s in mapping; don't care about this VDS. Skipping."
% str(pems_key))
continue
try:
intersection = getIntersectionStreetnamesForPemsKey(
mapping, pems_key)
logger.debug("%20s -> %s" % (str(pems_key), str(intersection)))
except Exception, e:
logger.error(e)
continue
# look for the mainline count location in countdracula
try:
mainline_count_location = MainlineCountLocation.objects.get(
from_int=intersection[2],
to_int=intersection[4],
on_street=intersection[0],
on_dir=pems_dir)
except ObjectDoesNotExist:
mainline_count_location = MainlineCountLocation(
on_street=intersection[0],
on_dir=pems_dir,
from_street=intersection[1],
from_int=intersection[2],
to_street=intersection[3],
to_int=intersection[4])
mainline_count_location.save()
workbook_filename = os.path.join(census_dirname, filename)
book = xlrd.open_workbook(workbook_filename)
# open the workbook
assert ("Report Data"
in book.sheet_names()) # standard PeMS sheetnames
datasheet = book.sheet_by_name("Report Data")
counts_saved = 0
# for each day
for col in range(1, len(datasheet.row(0))):
pems_date = xlrd.xldate_as_tuple(datasheet.cell_value(0, col),
book.datemode)
# for each time
for row in range(1, len(datasheet.col(0))):
pems_time = xlrd.xldate_as_tuple(datasheet.cell_value(row, 0),
book.datemode)
count_date = datetime.date(year=int(pems_date[0]),
month=int(pems_date[1]),
day=int(pems_date[2]))
starttime = datetime.time(hour=int(pems_time[3]),
minute=int(pems_time[4]),
second=0)
# tzinfo=TIMEZONE)
count = datasheet.cell_value(row, col)
if count == "": continue # skip blanks
if count == 0.0:
continue # skip zeros, they aren't real zero counts
project_str = "PeMS Census %s - %s" % (pems_id,
mapping[pems_key][3])
# read the counts
mainline_count = MainlineCount(
location=mainline_count_location,
count=count,
count_date=count_date,
start_time=starttime,
period_minutes=60,
vehicle_type=0, # ALL
reference_position=-1,
sourcefile=workbook_filename,
project=project_str,
upload_user=user)
mainline_count.clean()
mainline_count.save()
counts_saved += 1
del book
logger.info("Saved %3d census counts from %s into countdracula" %
(counts_saved, workbook_filename))
def readAndInsertMainlineCounts(self,
file,
primary_street,
cross_street1,
cross_street2,
user,
logger,
tzinfo=None):
"""
Parses the given excel file representing mainline counts and inserts those counts into the countdracula database.
* *file* is the Excel workbook file name
* *primary_street* is the street on which the counts were taken
* *cross_street1* and *cross_street2* are the bounding cross streets
* *user* is the django User to associate with the count
* *logger* is a logging instance
On success, returns number of successful counts inserted.
On failure, removes all counts from this workbook so it can be fixed and inserted again, and returns -1.
"""
# logger.info("primary_street=[%s], cross_street1=[%s] cross_street2=[%s]" % (primary_street, cross_street1, cross_street2))
mainline_counts = MainlineCount.objects.filter(sourcefile=file)
if len(mainline_counts) > 0:
logger.error(" readAndInsertMainlineCounts() called on %s, but %d mainline counts already "\
"exist with that sourcefile. Skipping." % (file, len(mainline_counts)))
return -1
try:
primary_street_list = StreetName.getPossibleStreetNames(
primary_street)
if len(primary_street_list) == 0:
raise CountsWorkbookParserException(
"readMainlineCounts: primary street %s not found." %
primary_street)
cross_street1_list = StreetName.getPossibleStreetNames(
cross_street1)
if len(cross_street1_list) == 0:
raise CountsWorkbookParserException(
"readMainlineCounts: cross street 1 %s not found." %
cross_street1)
cross_street2_list = StreetName.getPossibleStreetNames(
cross_street2)
if len(cross_street2_list) == 0:
raise CountsWorkbookParserException(
"readMainlineCounts: cross street 2 %s not found." %
cross_street2)
# looking for a primary street that intersects with both one of cross_street1 cross_Street2
# collect this info in two dictionaries:
# { primary_street_name (StreetName instance) -> { cross_street1_name (StreetName instance) -> QuerySet of Node instances }}
# { primary_street_name (StreetName instance) -> { cross_street2_name (StreetName instance) -> QuerySet of Node instances }}
intersections1 = {}
intersections2 = {}
for primary_street_name in primary_street_list:
intersections1[primary_street_name] = {}
intersections2[primary_street_name] = {}
for cross_street1_name in cross_street1_list:
intersections1[primary_street_name][cross_street1_name] = Node.objects.filter(street_to_node__street_name=primary_street_name) \
.filter(street_to_node__street_name=cross_street1_name)
# don't bother if it's an empty set
if len(intersections1[primary_street_name]
[cross_street1_name]) == 0:
del intersections1[primary_street_name][
cross_street1_name]
for cross_street2_name in cross_street2_list:
intersections2[primary_street_name][cross_street2_name] = Node.objects.filter(street_to_node__street_name=primary_street_name) \
.filter(street_to_node__street_name=cross_street2_name)
# don't bother if it's an empty set
if len(intersections2[primary_street_name]
[cross_street2_name]) == 0:
del intersections2[primary_street_name][
cross_street2_name]
# ideally, there will be exactly one primary street with a cross street 1 candidate and a cross street 2 candidate
primary_street_name_final = None
for primary_street_name in primary_street_list:
if len(intersections1[primary_street_name]) == 0: continue
if len(intersections2[primary_street_name]) == 0: continue
if len(intersections1[primary_street_name]) > 1:
raise CountsWorkbookParserException(
"readMainlineCounts: Street %s and cross street 1 %s have multiple intersections: %s"
% (primary_street_name, cross_street1,
str(intersections1[primary_street_name])))
if len(intersections2[primary_street_name]) > 1:
raise CountsWorkbookParserException(
"readMainlineCounts: Street %s and cross street 2 %s have multiple intersections: %s"
% (primary_street_name, cross_street2,
str(intersections2[primary_street_name])))
# already found one?
if primary_street_name_final:
raise CountsWorkbookParserException(
"readMainlineCounts: Multiple primary streets (%s,%s) intersect with %s/%s"
% (primary_street_name, primary_street_name_final,
cross_street1, cross_street2))
primary_street_name_final = primary_street_name
if not primary_street_name_final:
raise CountsWorkbookParserException(
"readMainlineCounts: Street %s and cross streets %s,%s have no intersections: %s %s"
% (primary_street, str(cross_street1_list),
str(cross_street2_list), str(intersections1),
str(intersections2)))
# finalize the cross street names and intersection ids
cross_street1_name_final = intersections1[
primary_street_name_final].keys()[0]
cross_street2_name_final = intersections2[
primary_street_name_final].keys()[0]
# go through the sheets and read the data
book = xlrd.open_workbook(file)
sheetnames = book.sheet_names()
counts_saved = 0
for sheet_idx in range(len(sheetnames)):
if sheetnames[sheet_idx].lower() == "source": continue
activesheet = book.sheet_by_name(sheetnames[sheet_idx])
# Create date from sheetname in date format
tmp_date = sheetnames[sheet_idx].split('.')
date_yyyy_mm_dd = date(int(tmp_date[0]), int(tmp_date[1]),
int(tmp_date[2]))
project = ""
sections = self.findSectionStarts(activesheet, logger)
# loop through the different sections in the workbook
for section in sections:
# project section?
if activesheet.cell_value(section[0],
0).upper() == "PROJECT":
project = activesheet.cell_value(section[0] + 1, 0)
continue
# figure out the vehicle type and row with the column labels
assert (activesheet.cell_value(section[0] + 1,
0).upper() == "MAINLINE")
label_row = section[0] + 1
# figure out the vehicle type code
vehicle = activesheet.cell_value(section[0], 0)
if type(vehicle) in [types.FloatType, types.IntType
] and vehicle in range(16):
vtype = vehicle
elif type(vehicle) in [
types.StringType, types.UnicodeType
]:
vtype = self.vehicleTypeForString(vehicle)
else:
vtype = 0 #TODO: fix
logger.info(" Worksheet %20s Vehicle=%2d %s" %
(sheetnames[sheet_idx], vtype, vehicle))
for column in range(
1, self.numNonBlankColumns(activesheet,
label_row)):
# Read the label header
ml_ondir_temp = activesheet.cell_value(
label_row, column)
ml_ondir = ml_ondir_temp[:2]
direction = ml_ondir[0]
# The convention is that cross street 1 is always north or west of cross street 2
# so use this cue to determine the origin/destination of the movement
if (direction == 'S' or direction == 'E'):
ml_fromstreet = cross_street1_name_final
ml_fromint = intersections1[
primary_street_name_final][ml_fromstreet][0]
ml_tostreet = cross_street2_name_final
ml_toint = intersections2[
primary_street_name_final][ml_tostreet][0]
else:
ml_fromstreet = cross_street2_name_final
ml_fromint = intersections2[
primary_street_name_final][ml_fromstreet][0]
ml_tostreet = cross_street1_name_final
ml_toint = intersections1[
primary_street_name_final][ml_tostreet][0]
# look for the mainline count location in countdracula
try:
mainline_count_location = MainlineCountLocation.objects.get(
from_int=ml_fromint,
to_int=ml_toint,
on_street=primary_street_name_final,
on_dir=ml_ondir)
except ObjectDoesNotExist:
mainline_count_location = MainlineCountLocation(
on_street=primary_street_name_final,
on_dir=ml_ondir,
from_street=ml_fromstreet,
from_int=ml_fromint,
to_street=ml_tostreet,
to_int=ml_toint)
mainline_count_location.save()
# process the rows
for row in range(section[0] + 2, section[1] + 1):
count = activesheet.cell_value(row, column)
if count == "": continue
(starttime, period) = self.createtimestamp(
activesheet.cell_value(row, 0), tzinfo=tzinfo)
mainline_count = MainlineCount(
location=mainline_count_location,
count=count,
count_date=date_yyyy_mm_dd,
start_time=starttime,
period_minutes=period,
vehicle_type=vtype,
reference_position=
-1, # reference position unknown, it's not in the workbook
sourcefile=file,
project=project,
upload_user=user)
mainline_count.clean()
mainline_count.save()
counts_saved += 1
logger.info(" Processed %s into countdracula" % file)
logger.info(" Successfully saved %4d mainline counts" %
counts_saved)
return counts_saved
except Exception as e:
logger.error(" Failed to process %s" % file)
logger.error(" " + str(e))
logger.error(" " + traceback.format_exc())
# remove the rest of the counts for this sourcefile so it can be retried
mainline_counts = MainlineCount.objects.filter(sourcefile=file)
if len(mainline_counts) > 0:
logger.debug(
" Removing %d counts from countdracula so sourcefile %s can be reprocessed"
% (len(mainline_counts), file))
mainline_counts.delete()
else:
logger.debug(
" No counts to remove for sourcefile %s; sourcefile can be reprocessed"
% file)
return -1
pems_time_fields = pems_time.split(r":")
count_date = datetime.date(year=int(pems_date_fields[2]),
month=int(pems_date_fields[0]),
day=int(pems_date_fields[1]))
starttime = datetime.time(hour=int(pems_time_fields[0]),
minute=int(pems_time_fields[1]),
second=int(pems_time_fields[2]))
# tzinfo=TIMEZONE)
project_str = "PeMS VDS %s - %s" % (pems_id, mapping[pems_key][3])
mainline_count = MainlineCount(
location=mainline_count_location,
count=pems_flow,
count_date=count_date,
start_time=starttime,
period_minutes=60,
vehicle_type=
0, # ALL
reference_position=-1,
sourcefile=vds_datfilename_abspath,
project=project_str,
upload_user=user)
mainline_count.clean()
mainline_count.save()
counts_saved += 1
logger.info("Saved %d PeMS VDS counts into countdracula" % counts_saved)
vds_datfile.close()
def readCensusCounts(mapping, census_dirname, user):
"""
def readAndInsertMainlineCounts(self, file, primary_street, cross_street1, cross_street2, user, logger, tzinfo=None):
"""
Parses the given excel file representing mainline counts and inserts those counts into the countdracula database.
* *file* is the Excel workbook file name
* *primary_street* is the street on which the counts were taken
* *cross_street1* and *cross_street2* are the bounding cross streets
* *user* is the django User to associate with the count
* *logger* is a logging instance
On success, returns number of successful counts inserted.
On failure, removes all counts from this workbook so it can be fixed and inserted again, and returns -1.
"""
# logger.info("primary_street=[%s], cross_street1=[%s] cross_street2=[%s]" % (primary_street, cross_street1, cross_street2))
mainline_counts = MainlineCount.objects.filter(sourcefile=file)
if len(mainline_counts) > 0:
logger.error(" readAndInsertMainlineCounts() called on %s, but %d mainline counts already "\
"exist with that sourcefile. Skipping." % (file, len(mainline_counts)))
return -1
try:
primary_street_list = StreetName.getPossibleStreetNames(primary_street)
if len(primary_street_list) == 0:
raise CountsWorkbookParserException("readMainlineCounts: primary street %s not found." % primary_street)
cross_street1_list = StreetName.getPossibleStreetNames(cross_street1)
if len(cross_street1_list) == 0:
raise CountsWorkbookParserException("readMainlineCounts: cross street 1 %s not found." % cross_street1)
cross_street2_list = StreetName.getPossibleStreetNames(cross_street2)
if len(cross_street2_list) == 0:
raise CountsWorkbookParserException("readMainlineCounts: cross street 2 %s not found." % cross_street2)
# looking for a primary street that intersects with both one of cross_street1 cross_Street2
# collect this info in two dictionaries:
# { primary_street_name (StreetName instance) -> { cross_street1_name (StreetName instance) -> QuerySet of Node instances }}
# { primary_street_name (StreetName instance) -> { cross_street2_name (StreetName instance) -> QuerySet of Node instances }}
intersections1 = {}
intersections2 = {}
for primary_street_name in primary_street_list:
intersections1[primary_street_name] = {}
intersections2[primary_street_name] = {}
for cross_street1_name in cross_street1_list:
intersections1[primary_street_name][cross_street1_name] = Node.objects.filter(street_to_node__street_name=primary_street_name) \
.filter(street_to_node__street_name=cross_street1_name)
# don't bother if it's an empty set
if len(intersections1[primary_street_name][cross_street1_name]) == 0:
del intersections1[primary_street_name][cross_street1_name]
for cross_street2_name in cross_street2_list:
intersections2[primary_street_name][cross_street2_name] = Node.objects.filter(street_to_node__street_name=primary_street_name) \
.filter(street_to_node__street_name=cross_street2_name)
# don't bother if it's an empty set
if len(intersections2[primary_street_name][cross_street2_name]) == 0:
del intersections2[primary_street_name][cross_street2_name]
# ideally, there will be exactly one primary street with a cross street 1 candidate and a cross street 2 candidate
primary_street_name_final = None
for primary_street_name in primary_street_list:
if len(intersections1[primary_street_name]) == 0: continue
if len(intersections2[primary_street_name]) == 0: continue
if len(intersections1[primary_street_name]) > 1:
raise CountsWorkbookParserException("readMainlineCounts: Street %s and cross street 1 %s have multiple intersections: %s" %
(primary_street_name, cross_street1, str(intersections1[primary_street_name])))
if len(intersections2[primary_street_name]) > 1:
raise CountsWorkbookParserException("readMainlineCounts: Street %s and cross street 2 %s have multiple intersections: %s" %
(primary_street_name, cross_street2, str(intersections2[primary_street_name])))
# already found one?
if primary_street_name_final:
raise CountsWorkbookParserException("readMainlineCounts: Multiple primary streets (%s,%s) intersect with %s/%s" %
(primary_street_name, primary_street_name_final,
cross_street1, cross_street2))
primary_street_name_final = primary_street_name
if not primary_street_name_final:
raise CountsWorkbookParserException("readMainlineCounts: Street %s and cross streets %s,%s have no intersections: %s %s" %
(primary_street, str(cross_street1_list), str(cross_street2_list),
str(intersections1), str(intersections2)))
# finalize the cross street names and intersection ids
cross_street1_name_final = intersections1[primary_street_name_final].keys()[0]
cross_street2_name_final = intersections2[primary_street_name_final].keys()[0]
# go through the sheets and read the data
book = xlrd.open_workbook(file)
sheetnames = book.sheet_names()
counts_saved = 0
for sheet_idx in range(len(sheetnames)) :
if sheetnames[sheet_idx].lower()=="source": continue
activesheet = book.sheet_by_name(sheetnames[sheet_idx])
# Create date from sheetname in date format
tmp_date = sheetnames[sheet_idx].split('.')
date_yyyy_mm_dd = date(int(tmp_date[0]),int(tmp_date[1]),int(tmp_date[2]) )
project = ""
sections = self.findSectionStarts(activesheet, logger)
# loop through the different sections in the workbook
for section in sections:
# project section?
if activesheet.cell_value(section[0],0).upper() == "PROJECT":
project = activesheet.cell_value(section[0]+1,0)
continue
# figure out the vehicle type and row with the column labels
assert(activesheet.cell_value(section[0]+1,0).upper() == "MAINLINE")
label_row = section[0]+1
# figure out the vehicle type code
vehicle = activesheet.cell_value(section[0], 0)
if type(vehicle) in [types.FloatType, types.IntType] and vehicle in range(16):
vtype = vehicle
elif type(vehicle) in [types.StringType, types.UnicodeType]:
vtype = self.vehicleTypeForString(vehicle)
else:
vtype = 0 #TODO: fix
logger.info(" Worksheet %20s Vehicle=%2d %s" % (sheetnames[sheet_idx], vtype, vehicle))
for column in range(1,self.numNonBlankColumns(activesheet, label_row)):
# Read the label header
ml_ondir_temp = activesheet.cell_value(label_row,column)
ml_ondir = ml_ondir_temp[:2]
direction = ml_ondir[0]
# The convention is that cross street 1 is always north or west of cross street 2
# so use this cue to determine the origin/destination of the movement
if (direction == 'S' or direction == 'E'):
ml_fromstreet = cross_street1_name_final
ml_fromint = intersections1[primary_street_name_final][ml_fromstreet][0]
ml_tostreet = cross_street2_name_final
ml_toint = intersections2[primary_street_name_final][ml_tostreet][0]
else:
ml_fromstreet = cross_street2_name_final
ml_fromint = intersections2[primary_street_name_final][ml_fromstreet][0]
ml_tostreet = cross_street1_name_final
ml_toint = intersections1[primary_street_name_final][ml_tostreet][0]
# look for the mainline count location in countdracula
try:
mainline_count_location = MainlineCountLocation.objects.get(from_int = ml_fromint,
to_int = ml_toint,
on_street = primary_street_name_final,
on_dir = ml_ondir)
except ObjectDoesNotExist:
mainline_count_location = MainlineCountLocation(on_street = primary_street_name_final,
on_dir = ml_ondir,
from_street = ml_fromstreet,
from_int = ml_fromint,
to_street = ml_tostreet,
to_int = ml_toint)
mainline_count_location.save()
# process the rows
for row in range(section[0]+2, section[1]+1):
count = activesheet.cell_value(row,column)
if count == "" : continue
(starttime, period) = self.createtimestamp(activesheet.cell_value(row,0), tzinfo=tzinfo)
mainline_count = MainlineCount(location = mainline_count_location,
count = count,
count_date = date_yyyy_mm_dd,
start_time = starttime,
period_minutes = period,
vehicle_type = vtype,
reference_position = -1, # reference position unknown, it's not in the workbook
sourcefile = file,
project = project,
upload_user = user)
mainline_count.clean()
mainline_count.save()
counts_saved += 1
logger.info(" Processed %s into countdracula" % file)
logger.info(" Successfully saved %4d mainline counts" % counts_saved)
return counts_saved
except Exception as e:
logger.error(" Failed to process %s" % file)
logger.error(" " + str(e))
logger.error(" " + traceback.format_exc())
# remove the rest of the counts for this sourcefile so it can be retried
mainline_counts = MainlineCount.objects.filter(sourcefile=file)
if len(mainline_counts) > 0:
logger.debug(" Removing %d counts from countdracula so sourcefile %s can be reprocessed" %
(len(mainline_counts), file))
mainline_counts.delete()
else:
logger.debug(" No counts to remove for sourcefile %s; sourcefile can be reprocessed" % file)
return -1
on_dir=on_dir,
from_street=from_street,
from_int=A_node,
to_street=to_street,
to_int=B_node)
mainline_count_location.save()
for colname in [
'EA_OBS', 'AM_OBS', 'MD_OBS', 'PM_OBS', 'EV_OBS', 'TOT_OBS'
]:
count = decimal.Decimal(
datasheet.cell_value(row, colname_to_colnum[colname]))
if count == 0: continue # zeros are not real
mainline_count = MainlineCount(
location=mainline_count_location,
count=count,
count_year=count_year,
start_time=OBS_COL_TO_STARTTIME[colname],
period_minutes=OBS_COL_TO_MINUTES[colname],
vehicle_type=0,
sourcefile=MTC_COUNTS_FILE_FULLNAME,
project="mtc",
reference_position=-1,
upload_user=user)
mainline_count.save()
saved_rows += 1
logger.info("Processed %d out of %d rows" % (saved_rows, total_rows))
def readCensusCounts(mapping, census_dirname, user):
"""
Reads the census station count workbooks and inputs those counts into the Count Dracula database.
"""
filenames = sorted(os.listdir(census_dirname))
for filename in filenames:
if filename[-4:] != ".xls":
logger.debug("Skipping non-xls file %s" % filename)
continue
logger.info("Processing PeMS Census file %s" % filename)
filename_parts = filename[:-4].split("_")
pems_id = filename_parts[0]
pems_dir = pems_id[-2:].upper()
pems_id = pems_id.replace("nb", "N")
pems_id = pems_id.replace("sb", "S")
pems_key = ("Census", pems_id)
if pems_key not in mapping:
logger.debug("Couldn't find %s in mapping; don't care about this VDS. Skipping." % str(pems_key))
continue
try:
intersection = getIntersectionStreetnamesForPemsKey(mapping, pems_key)
logger.debug("%20s -> %s" % (str(pems_key), str(intersection)))
except Exception, e:
logger.error(e)
continue
# look for the mainline count location in countdracula
try:
mainline_count_location = MainlineCountLocation.objects.get(from_int = intersection[2],
to_int = intersection[4],
on_street = intersection[0],
on_dir = pems_dir)
except ObjectDoesNotExist:
mainline_count_location = MainlineCountLocation(on_street = intersection[0],
on_dir = pems_dir,
from_street = intersection[1],
from_int = intersection[2],
to_street = intersection[3],
to_int = intersection[4])
mainline_count_location.save()
workbook_filename = os.path.join(census_dirname, filename)
book = xlrd.open_workbook(workbook_filename)
# open the workbook
assert("Report Data" in book.sheet_names()) # standard PeMS sheetnames
datasheet = book.sheet_by_name("Report Data")
counts_saved = 0
# for each day
for col in range(1, len(datasheet.row(0))):
pems_date = xlrd.xldate_as_tuple(datasheet.cell_value(0, col), book.datemode)
# for each time
for row in range(1, len(datasheet.col(0))):
pems_time = xlrd.xldate_as_tuple(datasheet.cell_value(row, 0), book.datemode)
count_date = datetime.date(year = int(pems_date[0]),
month = int(pems_date[1]),
day = int(pems_date[2]))
starttime = datetime.time( hour = int(pems_time[3]),
minute= int(pems_time[4]),
second= 0)
# tzinfo=TIMEZONE)
count = datasheet.cell_value(row,col)
if count == "": continue # skip blanks
if count == 0.0: continue # skip zeros, they aren't real zero counts
project_str = "PeMS Census %s - %s" % (pems_id, mapping[pems_key][3])
# read the counts
mainline_count = MainlineCount(location = mainline_count_location,
count = count,
count_date = count_date,
start_time = starttime,
period_minutes = 60,
vehicle_type = 0, # ALL
reference_position = -1,
sourcefile = workbook_filename,
project = project_str,
upload_user = user)
mainline_count.clean()
mainline_count.save()
counts_saved += 1
del book
logger.info("Saved %3d census counts from %s into countdracula" % (counts_saved, workbook_filename))
count_date = datetime.date(year=int(pems_date_fields[2]),
month=int(pems_date_fields[0]),
day=int(pems_date_fields[1]))
starttime = datetime.time( hour=int(pems_time_fields[0]),
minute=int(pems_time_fields[1]),
second=int(pems_time_fields[2]))
# tzinfo=TIMEZONE)
project_str = "PeMS VDS %s - %s" % (pems_id, mapping[pems_key][3])
mainline_count = MainlineCount(location = mainline_count_location,
count = pems_flow,
count_date = count_date,
start_time = starttime,
period_minutes = 60,
vehicle_type = 0, # ALL
reference_position = -1,
sourcefile = vds_datfilename_abspath,
project = project_str,
upload_user = user)
mainline_count.clean()
mainline_count.save()
counts_saved += 1
logger.info("Saved %d PeMS VDS counts into countdracula" % counts_saved)
vds_datfile.close()
def readCensusCounts(mapping, census_dirname, user):
"""
Reads the census station count workbooks and inputs those counts into the Count Dracula database.
"""
