def test_01_testPasswordMatch(self):
my = DataFile("bundesliga","mourinho","win1win2","chelsea")
my.setPassword("samplePassword123")
fileOperation = FileOperations()
fileOperation.SaveFileInfo(my,"sample.p")
my = fileOperation.LoadFileInfo("sample.p","samplePassword123")
self.failIf(my.getPassword() != "samplePassword123","Fail")
def loadDims(filename):
""" Load the dimensions from a netcdf file, then close the file.
Validator initializer also does this.
Keyword Arguments:
filename:*string*
Netcdf file name
Returns:
dict of ni,nj,nk,nt
"""
conc = DataFile(filename, mode='r', open=True)
dims={'ni': conc.dimensions['COL'], \
'nj': conc.dimensions['ROW'], \
'nk': conc.dimensions['LAY']}
# TSTEP is unlimited, so python has problems reading it
# So instead we'll examine the shape of a variable
# Let's assume TFLAG exists
shape = conc.variables['TFLAG'].shape
# This first element is TSTEP
dims['nt'] = shape[0]
conc.close()
return dims
class ProcessSentence:
"""This class to process the user sentence"""
def __init__(self):
self.username = USERNAME
self.botname = BOTNAME
self.db = DataFile()
def get_user_name(self):
return self.username
def get_bot_name(self):
return self.botname
def set_user_name(self, name):
self.username = name
def set_bot_name(self, name):
self.botname = name
def check_for_greeting(self, sentence):
"""Check for greeting setence and respond"""
words = sentence.split()
for word in words:
greeting = self.db.check_for_greeting(word.lower())
if greeting is not None:
return self.db.get_greeting_response()
def process_sentence(self, sentence):
"""Process the user sentence"""
def maskSpace(self, maskf, variable, value=1): """ Set a grid mask Keyword arguments: maskf:*string* NetCDF file containing the masking field variable:*string* Variable in the NetCDF file that is the mask value:*int* The masking value of the mask """ c = bc() if maskf is not None: try: f=DataFile(maskf, mode='r', open=True) #print "\n%sOpened spacial mask file %s, variable=%s, val=%s%s\n"%(c.yellow, maskf, variable, value, c.clear) mask = f.variables[variable][0][0] #print "type(mask)=%s, mask.shape=%s"%(type(mask), mask.shape) self.space = mask==value if type(self.space) != type(mask): print "%sError! self.space's type changed to %s%s"%(c.red, type(self.space), c.clear) f.close() except Exception as ex: print "%sSomething went wrong masking space with mask file %s (exists?: %r) %s%s"%(c.red, maskf, os.path.isfile(maskf), ex, c.clear) raise
def test_02_testLoadFromFileSucceed(self):
my = DataFile("bundesliga","mourinho","win1win2","chelsea")
my.setPassword("samplePassword123")
fileOperation = FileOperations()
fileOperation.SaveFileInfo(my,"sample.p")
my.league = "barclays premier league"
my = fileOperation.LoadFileInfo("sample.p","samplePassword123")
self.failIf(my.league != "bundesliga","Fail")
def __init__(self, filename):
self.data = DataFile(filename, "float")
self.N = self.data.rawnum()
self.para = DataFile(
os.path.split(filename)[0] + '/' + 'parameters.dat')
self.__read_data__()
self.__read_param__()
self.__set_linked_list__()
if filename.split('.')[-1] == "bz2":
self.t = os.path.split(filename)[-1].split('.')[0] + '.'
self.t = self.t + os.path.split(filename)[-1].split('.')[1]
self.t = float(self.t)
else:
self.t = float(os.path.splitext(os.path.split(filename)[-1])[0])
def main():
cpybook_path = 'test.cpy'
data_file_path = 'test.txt'
# Create object model to represent the Copybook
cpybook_parser = CopyBookParser.CopyBookParser(cpybook_path,
data_file_path)
cpybook = cpybook_parser.create_copybook()
# Create object model to represent the Data File
data_file = DataFile(data_file_path)
cpybook_comparer = CopyBookCompare(cpybook, data_file)
cpybook_comparer.compare_copybook_with_data()
def __init__(self,filename): self.conc=DataFile(filename, mode='r', open=True) self.ni = self.conc.dimensions['COL'] self.nj = self.conc.dimensions['ROW'] self.nk = self.conc.dimensions['LAY'] # TSTEP is unlimited, so python has problems reading it # So instead we'll examine the shape of a variable # Let's assume TFLAG exists shape = self.conc.variables['TFLAG'].shape # This first element is TSTEP self.nt = shape[0] ns = len(self.conc.variables.keys())
def getDataFiles(args, config):
dataFiles = des_filesearcher.getDataFiles(
config.getOption("data_location"))
filtered = des_filesearcher.filterDataFiles(
dataFiles,
PARSER_CONF,
config,
verboseFilter=(args.verbose > 1),
verbosePass=(args.verbose > 2))
if args.include_files:
for f in args.include_files.split(","):
if f not in [x.getDataPath() for x in filtered]:
filtered.append(
DataFile(config.getOption("data_location"),
os.path.normpath(f)))
return (dataFiles, filtered)
def __init__(self, name, address, adapter):
self.name = name
self.address = address
self.adapter = adapter
self.battery = 0.0
self.temperature = 0.0
self.velocity = 0.0
self.data_to_log = bytearray()
self.dataFileTemperature = DataFile(self.name, 'Temperature')
self.dataFileVelocity = DataFile(self.name, 'Velocity')
self.dataFileBatteryLevel = DataFile(self.name, 'BatteryLevel')
print "Create testo device with name: ", self.name, " address: ", self.address
self.connect()
def changeFile(self, newfile): self.conc.close(); self.conc=DataFile(newfile, mode='r', open=True)
from FileNames import FileNames
from FormatFile import FormatFile
from DataFile import DataFile
from Query import Query
dataFolder = "data"
specFolder = "specs"
specFile = "testformat1.csv"
dataFile = "testformat1_2015-06-28.txt"
specPath = specFolder + "/" + specFile
dataPath = dataFolder + "/" + dataFile
name = FileNames(dataFile)
print(name.dataFileName, name.specFileName, name.Date)
spec = FormatFile(specFolder + "/" + name.specFileName)
print(spec.getFormat())
data = DataFile(dataPath, spec.getFormat())
print(data.data)
q = Query()
for row in data.data:
print(
q.insert_query(name.tableName, [col[0] for col in spec.getFormat()],
row))
class TestoDevice(object):
##################################################################################################################
# variables
##################################################################################################################
name = None
address = None
adapter = None
device = None
##################################################################################################################
# FUNCTIONS DEFINITION
##################################################################################################################
# constructor
def __init__(self, name, address, adapter):
self.name = name
self.address = address
self.adapter = adapter
self.battery = 0.0
self.temperature = 0.0
self.velocity = 0.0
self.data_to_log = bytearray()
self.dataFileTemperature = DataFile(self.name, 'Temperature')
self.dataFileVelocity = DataFile(self.name, 'Velocity')
self.dataFileBatteryLevel = DataFile(self.name, 'BatteryLevel')
print "Create testo device with name: ", self.name, " address: ", self.address
self.connect()
def connect(self):
print "Trying to connect with: ", self.name
# self.adapter.start()
self.device = self.adapter.connect(self.address, 10.0)
if self.device._connected:
print "Connected with: ", self.name
aa = self.device.discover_characteristics()
print "Characteristic from with: ", self.name
for bb in aa:
#print aa[bb].uuid, aa[bb].handle, aa[bb].descriptors,
try:
if aa[bb].handle == 3 or aa[bb].handle ==24:
value = self.device.char_read(bb, 1)
print "Characterostic handle:\t", aa[bb].handle, "value\t", value
#value2 = self.device.char_read_handle(aa[bb].handle, 1)
#print aa[bb].handle, 'value2:\t ", "%02X'% value2
#for ch in value:
# print ch, '\t', chr(ch),
if aa[bb].handle == 40:
print "Subscrobe to handle: ", aa[bb].handle
self.device.subscribe(bb, callback=self.callback_fun)
time.sleep(1)
except pygatt.exceptions.NotificationTimeout:
print "TIMEOUT"
except:
print "Error:", sys.exc_info()
self.device.char_write_handle(37, self.convert_str_bytearray('5600030000000c69023e81'), True, 5)
self.device.char_write_handle(37, self.convert_str_bytearray('200000000000077b'), True, 5)
self.device.char_write_handle(37, self.convert_str_bytearray('04001500000005930f0000004669726d77617265'), True, 5)
self.device.char_write_handle(37, self.convert_str_bytearray('56657273696f6e304f'), True, 5)
self.device.char_write_handle(37, self.convert_str_bytearray('04001500000005930f0000004669726d77617265'), True, 5)
self.device.char_write_handle(37, self.convert_str_bytearray('56657273696f6e304f'), True, 5)
self.device.char_write_handle(37, self.convert_str_bytearray('04001600000005d7100000004d6561737572656d'), True, 5)
self.device.char_write_handle(37, self.convert_str_bytearray('656e744379636c656161'), True, 5)
self.device.char_write_handle(37, self.convert_str_bytearray('110000000000035a'), True, 5)
#print self.device.get_rssi()
#print self.device._connected
def callback_fun(self, handle, data):
if data[0]==16:
self.data_to_log = bytearray()
self.data_to_log = self.data_to_log + data
else:
self.data_to_log = self.data_to_log + data
print (datetime.datetime.now().strftime("%H:%M:%S>") + ' ' + self.name + '> '),
if len(self.data_to_log) > 12:
if self.data_to_log[12]==0x42: #B > BatteryLevel
print (self.data_to_log[12:24] + ' '),
print (str(struct.unpack('f', self.data_to_log[24:28])[0]))
self.battery = struct.unpack('f', self.data_to_log[24:28])[0]
self.dataFileBatteryLevel.addRow(datetime.datetime.now().strftime("%H:%M:%S") ,self.battery)
if self.data_to_log[12]==0x54: #T > Temperature
print (self.data_to_log[12:23] + ' '),
print (str(struct.unpack('f', self.data_to_log[23:27])[0]))
self.temperature = struct.unpack('f', self.data_to_log[23:27])[0]
self.dataFileTemperature.addRow(datetime.datetime.now().strftime("%H:%M:%S") ,self.temperature)
if self.data_to_log[12]==0x56: #V > Velocity
print (self.data_to_log[12:20] + ' '),
print (str(struct.unpack('f', self.data_to_log[20:24])[0]))
self.velocity = struct.unpack('f', self.data_to_log[20:24])[0]
self.dataFileVelocity.addRow(datetime.datetime.now().strftime("%H:%M:%S") ,self.velocity)
def convert_str_bytearray(self, s):
split_string = lambda x, n: [x[i:i+n] for i in range(0, len(x), n)]
a = split_string(s,2)
ba = bytearray()
for z in a:
ba.append(int(z,16))
return ba
def loadScalarField(self):
""" Open up the mortality and population files and read
their values. Generate a field to multiply forcing by.
Forcing = F * Pop * Mortality * VSL
"""
if self.beta is None:
raise ForcingException("Must supply concentration response factor")
if self._mortality_fname is None or self._mortality_var is None:
raise ForcingException("Must supply mortality file")
if self._pop_fname is None or self._pop_var is None:
raise ForcingException("Must supply population file")
# This is optional
#if self.vsl is None:
# raise ForcingException("Must specify statistical value of life (in millions)")
# Open the mortality file
try:
mortality = DataFile(self._mortality_fname, mode='r', open=True)
except IOError as ex:
Forcing.error("Error! Cannot open mortality file %s. File exists? %r"%(self._mortality_fname, os.path.isfile(self._mortality_fname)))
raise
# Check dimensions
if not (mortality.dimensions['COL'] == self.ni and mortality.dimensions['ROW'] == self.nj):
raise ValueError("Error, dimensions in mortality file %s do not match domain."%self._mortality_fname)
# Read the field
try:
# dims are TSTEP, LAY, ROW, COL.. so skip TSTEP and LAY
# this should be made more general, or the file should be made better.
mfld = mortality.variables[self._mortality_var][0][0]
except IOError as e:
raise e
except IndexError as e:
raise ForcingFileDimensionException("Mortality NetCDF file seems to have incompatible dimensions. Currently require shape (TSTEP, LAY, ROW, COL). This is marked to be improved, as the data does not vary with time or layer.")
# Close the file
if self._pop_fname != self._pop_fname:
mortality.close()
# Open the population file
try:
pop = DataFile(self._pop_fname, mode='r', open=True)
except IOError as ex:
Forcing.error("Error! Cannot open population file %s"%(self._pop_fname))
raise
# Check dimensions
if not (pop.dimensions['COL'] == self.ni and pop.dimensions['ROW'] == self.nj):
raise ValueError("Error, dimensions in population file %s do not match domain."%self._pop_fname)
else:
# Same file?
pop = mortality
# Read the field
try:
# dims are TSTEP, LAY, ROW, COL.. so skip TSTEP and LAY
pfld = pop.variables[self._pop_var][0][0]
except IOError as e:
raise e
except IndexError as e:
raise ForcingFileDimensionException("Population NetCDF file seems to have incompatible dimensions. Currently require shape (TSTEP, LAY, ROW, COL). This is marked to be improved, as the data does not vary with time or layer.")
pop.close()
# Debug, remember, when debugging this against plotted data or fortran
# code: values like (70,70) started at index 1 whereas we started at
# index 0, so (70,70)=(69,69)
#print "[j=%d,i=%d] = mfld * mfld_scale * pfld * self.beta / 365 = %e %e %e %e %e = %e"%(self.debug_j, self.debug_i, mfld[self.debug_j,self.debug_i], (10.**-4), pfld[self.debug_j,self.debug_i], self.beta, 365.0, mfld[self.debug_j,self.debug_i]*(10.**-4)*pfld[self.debug_j,self.debug_i]*self.beta/365.0)
# (mfld * pfld) is element wise multiplication, not matrix multiplication
# Take leap years into account?
Forcing.debug("[TODO]: Leap years are not yet accounted for.")
self.timeInvariantScalarMultiplcativeFld = mfld * self.mort_scale / 365.0 * pfld * self.beta
if self.vsl is not None:
self.timeInvariantScalarMultiplcativeFld = self.timeInvariantScalarMultiplcativeFld * self.vsl
class Data:
"""Data - this class reads particles information from file"""
def __init__(self, filename):
self.data = DataFile(filename, "float")
self.N = self.data.rawnum()
self.para = DataFile(
os.path.split(filename)[0] + '/' + 'parameters.dat')
self.__read_data__()
self.__read_param__()
self.__set_linked_list__()
if filename.split('.')[-1] == "bz2":
self.t = os.path.split(filename)[-1].split('.')[0] + '.'
self.t = self.t + os.path.split(filename)[-1].split('.')[1]
self.t = float(self.t)
else:
self.t = float(os.path.splitext(os.path.split(filename)[-1])[0])
def __read_data__(self):
self.id = self.data.getcol(1)
self.phaseId = self.data.getcol(2)
self.x = self.data.getcol(3)
self.y = self.data.getcol(4)
self.u = self.data.getcol(5)
self.v = self.data.getcol(6)
self.m = self.data.getcol(7)
self.p = self.data.getcol(8)
self.d = self.data.getcol(9)
self.di = self.data.getcol(10)
self.o = self.data.getcol(11)
self.nu = self.data.getcol(12)
self.mi = self.data.getcol(13)
self.gamma = self.data.getcol(14)
self.s = self.data.getcol(15)
self.b = self.data.getcol(16)
self.c = self.data.getcol(17)
self.nx = self.data.getcol(18)
self.ny = self.data.getcol(19)
self.na = self.data.getcol(20)
self.cu = self.data.getcol(21)
self.stx = self.data.getcol(22)
self.sty = self.data.getcol(23)
self.tp = self.data.getcol(24)
def __read_param__(self):
i = 1
for raw in self.para.getcol(1):
value = self.para.get(2, i)
if (raw == "H"): self.H = float(value)
if (raw == "I_H"): self.I_H = float(value)
if (raw == "DH"): self.DH = float(value)
if (raw == "DR"): self.DR = float(value)
if (raw == "XCV"): self.XCV = float(value)
if (raw == "YCV"): self.YCV = float(value)
#if (raw == "NX"): self.NX = int(value)
#if (raw == "NY"): self.NY = int(value)
if (raw == "NCX"): self.NXC = int(value)
if (raw == "NCY"): self.NYC = int(value)
if (raw == "T_BOUNDARY_PERIODICITY"): self.B_PER = int(value)
if (raw == "V_N"): self.V_N = float(value)
if (raw == "V_S"): self.V_S = float(value)
if (raw == "V_E"): self.V_E = float(value)
if (raw == "V_W"): self.V_W = float(value)
if (raw == "N"): self.N0 = int(value)
if (raw == "NC"): self.NC = int(value)
if (raw == "GAMMA"): self.GAMMA = float(value)
if (raw == "SOUND"): self.SOUND = float(value)
if (raw == "NU"): self.NU = float(value)
if (raw == "G_X"): self.G_X = float(value)
if (raw == "G_Y"): self.G_Y = float(value)
if (raw == "KNORM"): self.KNORM = float(value)
if (raw == "GKNORM"): self.GKNORM = float(value)
if (raw == "TIME"): self.TIME = float(value)
if (raw == "DT"): self.DT = float(value)
if (raw == "NOUT"): self.NOUT = int(value)
if (raw == "SIGMA"): self.SIGMA = float(value)
if (raw == "T_SHARP"): self.T_SHARP = int(value)
if (raw == "SHARP"): self.SHARP = float(value)
if (raw == "T_SURF_TENS"): self.T_SURF_TENS = int(value)
if (raw == "T_XSPH"): self.T_XSPH = int(value)
if (raw == "XSPH"): self.XSPH = float(value)
i += 1
self.NX = int(self.XCV / self.DR)
self.NY = int(self.YCV / self.DR)
def __set_linked_list__(self):
self.h = [-1 for i in range(self.NC)]
self.l = [-1 for i in range(self.N)]
for i in range(self.N):
if KERNEL_TYPE <= 3:
xc = long(0.5 * self.x[i] / self.H)
yc = long(0.5 * self.y[i] / self.H)
else:
xc = long(self.x[i] / (self.H * 3.0))
yc = long(self.y[i] / (self.H * 3.0))
c = xc + yc * self.NXC
if (xc < self.NXC) and (yc < self.NYC) and (xc >= 0) and (yc >= 0):
self.l[i] = self.h[c]
self.h[c] = i
label_object_array = volume_map.get(sub_folder_key)
sub_folder_full_path = (os.path.join(root, sub_folder))
data_file_list = os.listdir(sub_folder_full_path)
for each_file in data_file_list:
print(each_file)
suffix_index = each_file.rfind('.')
suffix = each_file[suffix_index + 1:len(each_file)]
file_name = each_file[0:suffix_index]
if (suffix != 'dcm'):
continue
split_name_array = file_name.split('_')
data_slice_index = int(split_name_array[-3]) - 1
for each_label_object in label_object_array:
if (each_label_object.slice_num == data_slice_index):
data_object = DataFile(each_file,
sub_folder_full_path, 0,
volume_key)
pair_list.append([
each_label_object.loading_path,
data_object.loading_path
])
file.write(each_label_object.loading_path +
'@@@@' + data_object.loading_path +
'\n')
print('~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~')
file_count = file_count + 1
print(file_count)
print(each_label_object.loading_path + '@@@@' +
data_object.loading_path)
file.close()
print('Finished')
import os
from FileNames import FileNames
from FormatFile import FormatFile
from DataFile import DataFile
from Query import Query
from Db import Db
dataFolder = "data"
specFolder = "specs"
db = Db()
q = Query()
for filename in os.listdir(dataFolder):
name = FileNames(filename)
spec = FormatFile(specFolder+"/"+name.specFileName)
data = DataFile(dataFolder+"/"+filename, spec.getFormat())
for row in data.getData():
query, params = q.insert_query(name.tableName, spec.getCols(), row)
print(query, params)
db.insert(query, params)
def initForceFile(self, conc, fpath, species = None):
""" Initialize a forcing file.
This method opens the NetCDF file in read/write mode, copies the
dimensions, copies I/O Api attributes over, and any other common
initialization that should be applied to all files
Keyword Arguments:
conc:*DataFile*
Concentration file to use as a template
fpath:*string*
Path (dir and name) of the forcing file to initialize
species:*string[]*
List of species to create
Returns:
NetCDFFile
Writable NetCDF File
"""
if not isinstance(conc, DataFile) or conc is None:
raise ValueError("Concentration file must be a DataFile")
# Make sure the concentration file is open
conc.open()
# Debug
c=bc()
# fpath should not exist
if os.path.exists(fpath):
# TEMP, remove
os.remove(fpath)
Forcing.debug("Deleted %s!"%(fpath))
#raise IOError("%s already exists."%fpath)
#print "Opening %s for writing"%fpath
force = DataFile(fpath, mode='w', open=True)
# Exceptions, so we don't needlessly create huge forcing files
exceptions={'LAY': self.nk_f}
Forcing.copyDims(conc, force, exceptions=exceptions)
Forcing.copyIoapiProps(conc, force)
if species is None:
species = self.species
# First, check the sample concentration file vs the concentration file
try:
#var = conc.variables['TFLAG'].getValue()
var = conc.variables['TFLAG']
except IOError as e:
# Pointless try loop for now, but I'll add to it later if needed.
raise
if var.shape[0] != self.nt:
#print "conc.shape = %s, sample.shape = %s"%(str(var.shape), str((self.nt, self.nk, self.nj, self.ni)))
raise BadSampleConcException("Input file's dimensions (time steps) not not match those of the sample concentration file! Cannot continue.")
# Create the variables we'll be writing to
#print "Initializing %s"%fpath
for s in species:
try:
var = force.createVariable(s, 'f', ('TSTEP', 'LAY', 'ROW', 'COL'))
z=np.zeros((self.nt,self.nk_f,self.nj,self.ni), dtype=np.float32)
var[:,:,:,:] = z
#Forcing.debug("Created zero variable %s in %s"%(s, force.basename))
except (IOError, ValueError) as ex:
print "%sWriting error %s%s when trying to create variable %s (%sTSTEP=%d, LAY=%d, ROW=%d, COL=%d%s)=%s%s%s in today's file.\n"%(c.red, type(ex), c.clear, s, c.blue, self.nt, self.nk_f, self.nj, self.ni, c.clear, c.orange, str(z.shape), c.clear), ex
print "Current variable names: %s\n"%(" ".join(map(str, force.variables.keys())))
# Copy over TFLAG
vsrc = conc.variables['TFLAG'][:]
force.createVariable('TFLAG', 'i', ('TSTEP', 'VAR', 'DATE-TIME'))
vdest = force.variables['TFLAG']
try:
vdest[:]=vsrc[:]
except (IOError, ValueError) as ex:
print "%sWriting error %s%s when trying to write TFLAG variable"%(c.red, type(ex), c.clear)
print "%sshape(vsrc)=%s, shape(vdest)=%s%s"%(c.cyan, str(vsrc.shape), str(vdest.shape), c.clear)
raise
## Fix geocode data
## http://svn.asilika.com/svn/school/GEOG%205804%20-%20Introduction%20to%20GIS/Project/webservice/fixIoapiProjection.py
## fixIoapiSpatialInfo
# Sync the file before sending it off
force.sync()
# Close the files
conc.close()
force.close()
# From now on, force will be read and written to, so change the mode
force.mode='a'
return force
def __init__(self):
"""Instantitae user Session"""
self.db = DataFile()
import os
from FileNames import FileNames
from FormatFile import FormatFile
from DataFile import DataFile
from Query import Query
from Db import Db
dataFolder = "data"
specFolder = "specs"
db = Db()
q = Query()
for filename in os.listdir(dataFolder):
name = FileNames(filename)
spec = FormatFile(specFolder + "/" + name.specFileName)
data = DataFile(dataFolder + "/" + filename, spec.getFormat())
for row in data.getData():
query, params = q.insert_query(name.tableName, spec.getCols(), row)
print(query, params)
db.insert(query, params)
def FindFiles(file_format, path=None, date_min=None, date_max=None):
""" Find the concentration files that match the pattern/format provided
Keyword Arguments:
path:*string*
Path to look for files
file_format:*string*
A format containing wildcards (*) and date indicators,
i.e. YYYY, YY, MM, DD or JJJ for Julian day
date_min:*Datetime*
If set, this is the minimum accepted date
date_max:*Datetime*
If set, this is the maximum accepted date
Returns:
*list[DataFile]*
Returns a list of Datafiles
"""
if path == None:
path = self.inputPath
if path == None:
raise ValueError("Must provide a path to search")
if path[-1] != "/":
path=path+"/"
#files=os.listdir( "/mnt/mediasonic/opt/output/morteza/frc-8h-US/" ) # Obviously change this..
files=os.listdir(path)
if date_min!=None and not isinstance(date_min, date):
raise TypeError("Minimum date may either be None or a DateTime")
if date_max!=None and not isinstance(date_max, date):
raise TypeError("Maximum date may either be None or a DateTime")
# Backup
reg=file_format
# Year
reg=re.sub(r'YYYY', '\\d{4}', reg)
reg=re.sub(r'MM', '\\d{2}', reg)
reg=re.sub(r'DD', '\\d{2}', reg)
reg=re.sub(r'JJJ', '\\d{3}', reg)
reg=re.sub(r'\*', '.*', reg)
#print "RE: %s"% reg
cfiles=[]
for f in files:
#print "Does %s match?"%f
if re.search(reg, f):
#print "%s matches"%f
df=DataFile(f, path=path, file_format=file_format)
df.loadDate()
#is_between_date = df.date>=date_min and df.date<=date_max
#print "df.date=%s, between [%s %s]?=%r type(df.date)=%s, type(date_min)=%s"%(df.date, date_min, date_max, is_between_date, type(df.date), type(date_min))
if (date_min == None and date_max == None) or ( (date_min != None and df.date >= date_min) and (date_max != None and df.date <= date_max) ):
#print "File added"
cfiles.append(df)
#return sorted(cfiles, key=lambda student: .age)
return sorted(cfiles)
class ForcingValidator:
LAY_SURFACE_NAME='Surface'
ni=None
nj=None
nk=None
ns=None
nt=None
conc = None
def __init__(self,filename):
self.conc=DataFile(filename, mode='r', open=True)
self.ni = self.conc.dimensions['COL']
self.nj = self.conc.dimensions['ROW']
self.nk = self.conc.dimensions['LAY']
# TSTEP is unlimited, so python has problems reading it
# So instead we'll examine the shape of a variable
# Let's assume TFLAG exists
shape = self.conc.variables['TFLAG'].shape
# This first element is TSTEP
self.nt = shape[0]
ns = len(self.conc.variables.keys())
def close(self):
try:
self.conc.close()
except IOError:
# nothing.. it's closed.
self.conc = None
def __del__(self):
self.close()
def changeFile(self, newfile):
self.conc.close();
self.conc=DataFile(newfile, mode='r', open=True)
def getDate(self):
""" Again, not a validator just a getter. Useful to know the date
of the concentration file being used. Since we're using an
I/O Api file, we'll look at the SDATE attribute.
Returns:
datetime
"""
self.conc.loadDate()
return self.conc.date
# # Get the sdate, in the format YYYYJJJ
# if not hasattr(self.conc, 'SDATE'):
# raise IOError("Sample concentration file does not seem to be a proper I/O Api file.")
#
# sdate=str(getattr(self.conc, 'SDATE'))
# # Sometimes sdate has brackets around it
# if sdate[0] == "[" and sdate[-1] == "]":
# sdate=sdate[1:-1]
# year=int(sdate[:4])
# jday=int(sdate[4:])
#
# date = datetime.date(year, 1, 1)
# days = datetime.timedelta(days=jday-1) # -1 because we started at day 1
# date=date+days
#
# return date
def getLayers(self):
"""Return a list of layers. This isn't really a validator, but
it shares a lot of the functionality. Assumes that there's
always a ground layer.
Returns:
list of layers
"""
num_layers = self.conc.dimensions['LAY']
layers=[self.LAY_SURFACE_NAME]
for l in range(2, num_layers):
layers+=str(l)
return layers
def getTimes(self):
"""Return a list of times(hours). This isn't really a validator, but
it shares a lot of the functionality. Assumes that there's
always a ground layer.
Returns:
list of times
"""
shape = self.conc.variables['TFLAG'].shape
nt = shape[0]
times=list(xrange(nt))
# Cut off the 25th time
for t in range(0, nt-1):
times[t]=str(t)
return times
def getSpecies(self):
"""Return a list of species. This isn't really a validator, but
it shares a lot of the functionality
Returns:
list of species
"""
vars = self.conc.variables.keys()
for i, var in enumerate(vars):
vars[i]=var.upper()
vars=sorted(vars)
pri_vars = []
normal_vars = []
# Put some of the important ones up top
for var in vars:
# Select case basically
if var in ['O3', 'NO', 'NO2']:
pri_vars.append(var)
elif var == "TFLAG":
continue
else:
normal_vars.append(var)
return pri_vars+normal_vars
# Check to ensure all the chosen species are available
# Species is a string vector
def validateSpecies(self, species):
"""Validate species against a sample datafile variables
Keyword Arguments:
species -- Vector of species names to use
Raises:
ValidationError - if invalid species is input
Returns:
TRUE if valid, false otherwise
"""
#print "Got species", '[%s]' % ', '.join(map(str, species))
vars = self.conc.variables.keys()
for i in range(0, len(vars)):
vars[i]=vars[i].upper()
notFound=[]
for s in species:
found=False
for v in vars:
if v == s:
found=True
break
if found == False:
notFound.append(s)
if len(notFound)>0:
raise ValidationError("Invalid species: ", '[%s]' % ', '.join(map(str, notFound)))
return False;
return True
def validateLayers(self,layers):
"""Validate layers against a sample datafile file
Keyword Arguments:
layers -- Vector of layers to use
Raises:
ValidationError - if invalid layer is input
Returns:
TRUE if valid, false otherwise
"""
num_layers = self.conc.dimensions['LAY']
for l in layers:
if l > num_layers:
raise ValidationError("Invalid layer: ", l)
return False
return True
def validateTimes(self,times):
"""Validate times against a sample datafile file
Keyword Arguments:
times -- Vector of times to use
Raises:
ValidationError -- if invalid times step is input
Returns:
TRUE if valid, false otherwise
"""
# Not yet implemented
return True
def ValidateDataFileSurface(self, filename):
""" Validates a datafile by checking if it's 2D surface domani
(ni,nj) matches the sample file """
datafile=DataFile(filename, mode='r', open=True)
#print "COL %d, self.ni: %d - ROW: %d, self.nj: %d"%(datafile.dimensions['COL'], self.ni, datafile.dimensions['ROW'], self.nj)
return datafile.dimensions['COL'] == self.ni and datafile.dimensions['ROW'] == self.nj
def __init__(self):
self.username = USERNAME
self.botname = BOTNAME
self.db = DataFile()
_collectParsed(args, config)
elif args.mode == "collect-parsed-div":
_collectParsedDiv(args, config)
elif args.mode == "compare-collected-div":
_compareCollectedDiv(args, config)
elif args.mode == "collected-div-count-first":
_collectedDivCountFirst(args, config)
elif args.mode == "collected-div-device-overlap":
_collectedDivDeviceOverlap(args, config)
elif args.mode == "plot":
_plot(args, config)
else:
if args.specific_files:
df = [
DataFile(config.getOption("data_location"),
os.path.normpath(x))
for x in args.specific_files.split(",")
]
files, filtered = df, df
else:
files, filtered = getDataFiles(args, config)
if args.mode == "parse": _parse(files, filtered, args, config)
elif args.mode == "send": _send(files, filtered, args, config)
elif args.mode == "parse-send" or args.mode == "send-parse":
_parseSend(files, filtered, args, config)
elif args.mode == "list":
_list(files, filtered, args, config)
elif args.mode == "impossible-timestamps":
_impossibleTimestamps(files, filtered, args, config)
elif args.mode == "output":
