def __init__(self,
xlfile=EXPERIMENT_DB(),
sheet='TGA',
prompt=None,
debug=0):
delim = ',' #@UnusedVariable
self._raw_columns = {'time:sec' : [0, 'Relative Time [s]'],
'mass' : [1, 'Mass [mg]'],
'temp' : [2, 'Temperature [C]'],
'change' : [3, 'Weight Change [%]']
}
# After defining the key parameters, we execute our superclasses init
# which access excel file, pulls info into self._row, and then parses data into self._data_array
Experiment.__init__(self,
xlfile = xlfile,
sheet = sheet,
prompt = prompt,
delim = ',',
txt_col = 6,
debug = debug)
# save information from Excel file
self._curves.add('time:hr', self._curves['time:sec']/3600., 'Time / hr')
def __init__(self,
xlfile=EXPERIMENT_DB(),
sheet='DSC',
prompt=None,
debug=0):
# self._raw_columns = {
# 'Curve', [column, 'label']
# }
Experiment.__init__(self,
xlfile = xlfile,
sheet = sheet,
prompt = prompt,
delim = '\t',
txt_col = 6,
debug = debug)
self._raw_columns = {
'time:min' : [0, 'Time (min)'],
'heat:flow' : [1, 'Heat Flow (mW)'],
'temp:set' : [3, 'Set Point Temperature ($\degree$C)'],
'temp:act' : [4, 'Temperature ($\degree$C)'],
'heat:cal' : [6, 'Heat Flow Calibration']
}
self._ascii_file = self._path + os.sep + 'data' + os.sep + self.p.get('txt:file')
self._baseline_file = self._path + os.sep + 'data' + os.sep + self.p.get('baseline:file')
self._data_array = remove_with_blanks(
io.parse_ascii(self._ascii_file , '\t')[1:]
)
self._baseline_array = remove_with_blanks(
io.parse_ascii(self._baseline_file, '\t')[1:]
)
# if we have defined _raw_columns then add all of those curves (defined for each exp type)
if hasattr(self, '_raw_columns'):
self._curves = Curve(self._data_array,self._raw_columns)
self._baseline = Curve(self._baseline_array,self._raw_columns)
else:
self._curves = Curve(self._data_array)
self._baseline = Curve(self._baseline_array)
if hasattr(self, '_curves'):
self._curves.add('time:sec', self._curves['time:min']*60., 'Time (sec)')
self._curves.add('time:hr', self._curves['time:sec']/3600., 'Time (hr)')
self.subtract_baseline()
self.c = self._curves
self.pl = self._curves.ex_plot
self.twin = self._curves.ex_twinplot
self.sub = self._curves.ex_subplot
def __init__(self,
xlfile=EXPERIMENT_DB,
sheet='TGMS',
prompt=None,
debug=0):
# self._raw_columns = {'Curve', [column, 'label']
# }
self._raw_columns = {'rel_sec' : [0, 'Relative Time [s]'],
'mass' : [1, 'Mass [mg]'],
'temp' : [2, 'Temperature [C]'],
'change' : [3, 'Weight Change [%]']
}
Experiment.__init__(self,
xlfile = xlfile,
sheet = sheet,
prompt = prompt,
delim = ',',
txt_col = 6,
dat = None,
debug = debug)
# save information from Excel file
row = self._row
row_params = {
}
self.init_param(row_params)
# construct experiment name
self.set_param('Name', '%s-%s.%i' % (row[1], row[2], row[3]))
# initial date and time (for reference)
dcol = 1 # date column in txt file @UnusedVariable
tcol = 2 # time column in txt file @UnusedVariable
# we do all plots based off relative time
self.add_curve('rel_hr',[float(sec)/3600 for sec in self._curves['rel_sec']], 'Relative Time [hr]')
self._labels = {}
def __init__(self,
xlfile=EXPERIMENT_DB,
sheet='',
prompt=None,
debug=0):
# self._raw_columns = {
# 'Curve', [column, 'label']
# }
Experiment.__init__(self,
xlfile = xlfile,
sheet = sheet,
prompt = prompt,
delim = '\t',
txt_col = 6,
debug = debug)
# save information from Excel file
row = self._row
row_params = {
}
if hasattr(self, '_curves'):
self._curves.add('time:hr', self._curves['time:sec']/3600., 'Time (hr)')
self._curves.add('time:min', self._curves['time:sec']/60., 'Time (min)')
# initial date and time (for reference)
dcol = 1 # date column in txt file
tcol = 2 # time column in txt file
self.get_init(self._data_array[dcol][0], self._data_array[tcol][0])
# we do all plots based off relative time
self.get_reltimes()
self.add_curve('rel_hr',[float(sec)/3600 for sec in self._curves['rel_sec']], 'Relative Time [hr]')
self._labels = {}
def __init__(self,
xlfile=EXPERIMENT_DB,
sheet='TGA',
prompt=None,
debug=0):
delim = ','
self._raw_columns = {'rel_sec' : [0, 'Relative Time [s]'],
'mass' : [1, 'Mass [mg]'],
'temp' : [2, 'Temperature [C]'],
'change' : [3, 'Weight Change [%]']
}
# After defining the key parameters, we execute our superclasses init
# which access excel file, pulls info into self._row, and then parses data into self._data_array
Experiment.__init__(self,
xlfile = xlfile,
sheet = sheet,
prompt = prompt,
delim = ',',
txt_col = 6,
dat = None,
debug = debug)
# save information from Excel file
row = self._row
row_params = {
}
self.add_curve('rel_hr',[float(sec)/3600 for sec in self._curves['rel_sec']], 'Relative Time [hr]')
# Construct experiment name
self.set_param('Name', '%s-%s.%s' % (row[1], row[2], row[3]))
self._labels = {'N':'\n',
'n':self.get_param('Name')}
def __init__(self,
xlfile=EXPERIMENT_DB(),
sheet='IR',
prompt=None,
debug=0):
Experiment.__init__(self,
xlfile = xlfile,
sheet = sheet,
prompt = prompt,
delim = '\t',
txt_col = 8,
debug = debug)
# save information from Excel file
row = self._row
self._raw_columns = {'wave_uc' : [0, 'Wavenumber (cm$^{-1}$)'],
'wave' : [1, 'Wavenumber (cm$^{-1}$)'],
'trans' : [2, 'Transmitance'],
'abs' : [3, 'Absorbance (A.U)'],
'n_trans' : [4, 'Transmitance (%)'],
'n_absl' : [5, 'Absorbance (%)']
}
self._data_array = io.parse_jdx(self._ascii_file)
self._curves = Curve(self._data_array,self._raw_columns)
# important parameter in excel file
self._row_params = {
}
# construct experiment name
self._params.set('Name', '%s-%s.%s' % (row[1], row[2], row[3]))
self._curves._labels = {'N':'\n',
'n':self._params.get('Name'),
}
def __init__(self,
xlfile=EXPERIMENT_DB(),
sheet='LABVIEW',
prompt=None,
debug=0,
autoload=False):
self._raw_columns = {
'time:sec' : [ 0, 'Time (s)' ],
'flow:dig' : [ 1, 'Flow (ccm)' ],
'flow:inert' : [ 2, 'Flow (ccm)' ],
'flow:rxn' : [ 3, 'Flow (ccm)' ],
'press:in' : [ 4, 'Pin (psig)' ],
'press:out' : [ 5, 'Pout (psig)' ],
'temp:in' : [ 6, 'Temperature of Inlet ($\degree$C)' ],
'temp:rxn' : [ 7, 'Temperature of Reactor ($\degree$C)' ],
'ms:14' : [ 8, '14' ],
'ms:18' : [ 9, '18' ],
'ms:28' : [ 10, '28' ],
'ms:32' : [ 11, '32' ],
'ms:40' : [ 12, '40' ],
'ms:44' : [ 13, '44' ],
'int:h2o' : [ 14, 'Intensity (a.u)' ],
'int:n2' : [ 15, 'Intensity (a.u)' ],
'int:o2' : [ 16, 'Intensity (a.u)' ],
'int:ar' : [ 17, 'Intensity (a.u)' ],
'int:co2' : [ 18, 'Intensity (a.u)' ],
'conc:a:co2' : [ 24, 'Concentration (mol %)' ]
}
# After defining the key parameters, we execute our superclasses init
# which access excel file, pulls info into self._row, and then parses data into self._data_array
Experiment.__init__(self,
xlfile=xlfile,
sheet=sheet,
prompt=prompt,
delim = ',',
txt_col = 6,
debug=debug,
autoload=autoload)
if hasattr(self, '_curves'):
self._curves.add('time:hr', self._curves['time:sec']/3600., 'Time (hr)')
self._curves.add('time:min', self._curves['time:sec']/60., 'Time (min)')
"""
lower case is adsorption
n = name
N = new line
t, T = temp
r = ramp rate
D = temp change
p, P = pressure
h = water concentration
b = book number
"""
# TODO define better checks and do error proofing
# most likely with try statements
if (os.path.isfile(self._pick_file) and autoload is True) or (not os.path.isfile(self._ascii_file)) or (self._params.get('status') == 'No'):
pass
else:
# FIXME is this the best way?
# try:
# construct experiment name
p = self._params
p.set('name', '%s-%s-%s' % (p['sorbent'], p['exp'],p['run']))
self.prompt = prompt
# find new way to determine stage
self.get_stage()
# save mass settings
self.cal_curves()
self.__check__('Experimental notes: ' , p['notes'])
self.get_flux()
if type(self.p.get('loading')) is float:
self.get_coverage()
"""
c, C = coverage (corrected)
z, Z = trapezoidal capacity
m, M = mid point capacity (uncorrected)
i, I = mid point capacity (corrected)
"""
new_labels = {}
self._curves._labels.update(new_labels)
def __init__(self,
xlfile=EXPERIMENT_DB(),
sheet='PFR',
prompt=None,
debug=0,
autoload=True):
self._raw_columns = {
'time:sec' : [3, 'Time / s'],
'raw:he' : [4,'He Concentration / %'],
'raw:h2o' : [5, 'H$_2$O Concentration / %'],
'raw:co2' : [6, 'CO$_2$ Concentration / %'],
'int:he' : [7, 'He Intensity [m/z]'],
'int:h2o' : [8, 'H20 Intensity [m/z]'],
'int:co2' : [9, 'CO2 Intensity [m/z]']
}
self._row_params = {'#' : 0,
'book' : 4,
'status' : 7,
'Name' : 1,
'date' : 6,
'time:dry' : 24,
'Run' : 3,
'conc:He' : 6,
'conc:H2O' : 9,
'conc:CO2' : 10,
'flow:in' : 11,
'flow:rxn' : 12,
'timing:abs' : range(13,18),
'temp:ads' : 20,
'temp:des' : 21,
'temp:spg' : 22,
'temp:ramp' : 23,
'comment' : 29,
'loading' : 27,
'mass:1' : 25,
'mass:2' : 26
}
# After defining the key parameters, we execute our superclasses init
# which access excel file, pulls info into self._row, and then parses data into self._data_array
Experiment.__init__(self,
xlfile=xlfile,
sheet=sheet,
prompt=prompt,
delim = '\t',
txt_col = 5,
debug=debug,
autoload=autoload)
if hasattr(self, '_curves'):
self._curves.add('time:hr', self._curves['time:sec']/3600., 'Time / hr')
self._curves.add('time:hr', self._curves['time:sec']/3600., 'Time / hr')
"""
lower case is adsorption
n = name
N = new line
t, T = temp
r = ramp rate
D = temp change
p, P = pressure
h = water concentration
b = book number
"""
self._curves._labels = {
'N':'\n',
'b':self._params.get('Book'),
'n':self._params.get('Name'),
't':'$\mathrm{T}_{ADS} :$ \t\t$%0.1f\,^{\circ}\mathrm{C}$' % (self._params.get('temp:ads')),
'T':'$\mathrm{T}_{DES} :$ \t\t$%0.1f\,^{\circ}\mathrm{C}$' % (self._params.get('temp:des')),
'r':'$\mathrm{Ramp:}$ \t$%s\,^{\circ}\mathrm{C/min}$' % (self._params.get('temp:ramp')),
'D':'$\Delta\mathrm{T:}$ \t$%0.1f\,^{\circ}\mathrm{C}$' % (self._params.get('temp:des') - self._params.get('temp:ads')),
'p':'$p_{CO_2}$/$p_0:$ \t$0.1$',
'P':'p$_{CO_2}$/p$_0:$ \t$0.1$ -> $0.0$',
'h':'%0.1f%% H$_{2}$O' % (100.0*self._params.get('conc:H2O'))
}
if (os.path.isfile(self._pick_file) and autoload is True) or (not os.path.isfile(self._ascii_file)) or (self._params.get('status') == 'No'):
pass
else:
#save parameter information from row of excel file
row = self._row
# construct experiment name
self._params.set('Name', '%s-%s.%s' % (row[1], row[2], row[3]))
# Flux correction from run 11
self._params.set('Void', PBR_VOID_SPACE)
self.prompt = prompt
date = self._curves._raw[1][0]
time = self._curves._raw[2][0]
# Parse date into Year Month Day
# M/D/Y -> Y, M, D
init_date = [[int(v) for v in date.split('/')][i] for i in [2,0,1]]
#Parse time into a list of hour, minutes, and seconds
init_time = [int(a) for a in time.split()[0].split(':')]
if time.split()[1] == 'PM' and init_time[0] != 12:
init_time[0] += 12
init = init_date + [int(v) for v in init_time]
# Create datetime object for first point (which we will use as our baseline when evaluating relative time)
self._init = datetime.datetime(*init)
rel = []
# TODO is there a more obvious way / modular to do this?
for time in self._params.get('timing:abs'):
rel_abs = list(self._init.timetuple()[0:3]) + [int(v) for v in time.split(':')]
# print rel_abs
# create datetime object for each point
rel_abs = datetime.datetime(*rel_abs)
rel.append(float((rel_abs - self._init).seconds)/3600.)
self._params.set('timing:rel',rel)
# stage needs time:hr to complete
self.get_stage()
# save mass settings
m1 = self._params.get('mass:1')
m2 = self._params.get('mass:2')
try:
self._params.set('mass:dm',float(m1)- float(m2))
except ValueError:
pass
try:
self._params.set('mass:act',float(m1))
except ValueError:
pass
try:
self._params.set('mass:act',float(m2))
except ValueError:
pass
self.get_temp()
self.get_flux()
self.get_coverage()
# TODO add additional method abbreviations for quick access: i.e. self.c = self._curves.get
"""
c, C = coverage (corrected)
z, Z = trapezoidal capacity
m, M = mid point capacity (uncorrected)
i, I = mid point capacity (corrected)
"""
new_labels = {
'i':'$\mathrm{Mol}_{ADS}\ :$ \t$%0.2f$ $\mathrm{mol\ }CO_2/kg$' % (abs(self._params.get('capc:ads_mid'))),
'I':'$\mathrm{Mol}_{DES}\ :$ \t$%0.2f$ $\mathrm{mol\ }CO_2/kg$' % (abs(self._params.get('capc:des_mid'))),
'm':'$\mathrm{Mol}_{ADS}:$ \t$%0.2f$ $\mathrm{mol\ }CO_2/kg$' % (self._params.get('cap:ads_mid')),
'M':'$\mathrm{Mol}_{DES}:$ \t$%0.2f$ $\mathrm{mol\ }CO_2/kg$' % (self._params.get('cap:des_mid')),
'c':'$\mathrm{Eff}_{ADS}:$ \t$%0.2f$ $\mathrm{mol\ }CO_2/\mathrm{mol\ }N$' % (self._params.get('effc:ads')),
'C':'$\mathrm{Eff}_{DES}:$ \t$%0.2f$ $\mathrm{mol\ }CO_2/\mathrm{mol\ }N$' % (self._params.get('effc:des')),
'z':'$\mathrm{Mol}_{ADS}:$ \t$%0.2f$ $\mathrm{mol\ }CO_2/kg$' % (self._params.get('cap:ads_trap')),
'X':'$\mathrm{Mol}_{PDES}:$ \t$%0.2f$ $\mathrm{mol\ }CO_2/kg$' % (self._params.get('cap:desp_trap')),
'Y':'$\mathrm{Mol}_{TDES}:$ \t$%0.2f$ $\mathrm{mol\ }CO_2/kg$' % (self._params.get('cap:dest_trap'))
}
self._curves._labels.update(new_labels)
self._save()
