def U_wash(self):
"""
U_wash provides a list the following outputs for the Age Calculation:
[0]: 233 unfiltered wash in cps
[1]: 234 unfiltered wash in cps
[2]: 234 unfiltered wash in cps
"""
#233 wash value
working_a = isofilter.IsoFilter(self.filename_U, "C", 44)
self.three_wash = working_a.getMean()
#234 wash value
working_b = isofilter.IsoFilter(self.filename_U, "D", 44)
self.four_wash = working_b.getMean()
#235 wash value
working_c = isofilter.IsoFilter(self.filename_U, "E", 44)
self.five_wash = working_c.getMean()
while self.inquiry:
print "BACKGROUND VALUES FOR AGE CALC:"
print "233 wash value: " + str(self.three_wash) + ' cps'
print "234 wash value: " + str(self.four_wash) + ' cps'
print "235 wash value: " + str(self.five_wash) + ' cps'
break
lstU_wash = [self.three_wash, self.four_wash, self.five_wash]
return lstU_wash
def Th_wash(self):
"""
Th_wash provides a list of the following outputs for the Age Calculation:
[0]: 230 unfiltered wash in cpm
"""
#230 wash value
working_a = isofilter.IsoFilter(self.filename_Th, "D", 28)
self.zero_wash = working_a.getMean()
#calculate "darknoise" value for Age calculation
self.darknoise = self.zero_wash * 60
while self.inquiry:
print "230 wash value/darknoise: " + str(self.darknoise) + ' cpm'
break
return self.darknoise
def __init__(self, spike_input, AS_input, filename_input, inquiry_input):
spike = str(spike_input)
spike_six_three_dictionary = {
"DIII-B": 1.008398,
"DIII-A": 1.008398,
"1I": 1.010128,
"1H": 1.010128
}
#derives 236/233 value of spike from preset dictionary
if spike in spike_six_three_dictionary:
self.spike = float(spike_six_three_dictionary[spike])
else:
print 'ERROR: You did not enter a valid spike option'
#allows you the ability to print as you go
inquiry = str(inquiry_input)
if inquiry.lower() == "y":
self.inquiry = True
else:
self.inquiry = False
print "Program ran but without printing"
#AS is the abundant sensitivity 237/238, measured through the AS method on the ICP-MS
self.AS = float(AS_input)
#uses the filename given for your U run
filename = str(filename_input)
#236/233 filtered measured mean and 2s error
working = isofilter.IsoFilter(filename, "G", 44)
a = working.getMean()
b = working.getStanddev()
c = working.getCounts()
self.six_three_mean_meas = working.Filtered_mean(a, b, c)
self.six_three_err_meas = working.Filtered_err(a, b, c)
#235/233 filtered measured mean and 2s error
working_b = isofilter.IsoFilter(filename, "H", 44)
a = working_b.getMean()
b = working_b.getStanddev()
c = working_b.getCounts()
self.five_three_mean_meas = working_b.Filtered_mean(a, b, c)
self.five_three_err_meas = working_b.Filtered_err(a, b, c)
#234/235 filtered measured mean and 2s error
working_c = isofilter.IsoFilter(filename, "I", 44)
a = working_c.getMean()
b = working_c.getStanddev()
c = working_c.getCounts()
self.four_five_mean_meas = working_c.Filtered_mean(a, b, c)
self.four_five_err_meas = working_c.Filtered_err(a, b, c)
self.four_five_counts = working_c.Filtered_counts(a, b, c)
#233 unfiltered mean and counts
working_d = isofilter.IsoFilter(filename, "C", 44)
self.three_mean_meas = working_d.getMean()
self.three_counts = working_d.getCounts()
#constants to be used throughout the class
self.wt_235 = 235.043924
self.wt_233 = 233.039629
self.wt_236 = 236.045563
self.wt_234 = 234.040947
self.eight_five_rat = 137.83
self.AS_six_eight = self.AS / 5
self.AS_four_eight = self.AS / 20
self.eight_five_rat_err_rel = 0.0003
def __init__(self, spike_input, AS_input, filename_input, inquiry_input,
lstU_Th):
spike = str(spike_input)
spike_six_three_dictionary = {
"DIII-B": 1.008398,
"DIII-A": 1.008398,
"1I": 1.010128,
"1H": 1.010128
}
#derives 236/233 value of spike from preset dictionary
if spike in spike_six_three_dictionary:
self.spike = float(spike_six_three_dictionary[spike])
else:
print 'ERROR: You did not enter a valid spike option'
#allows you the ability to print as you go
inquiry = str(inquiry_input)
if inquiry.lower() == "y":
self.inquiry = True
else:
self.inquiry = False
print "Program ran but without printing"
#AS is the abundant sensitivity 237/238, measured through the AS method on the ICP-MS
self.AS = float(AS_input)
#uses the filename given for your Th run
filename = str(filename_input)
#Compiles the values of the lstU_Th provided by your U_normalization_forTh function
self.six_three_mean_meas = lstU_Th[0]
self.six_three_err_meas = lstU_Th[1]
self.five_three_norm = lstU_Th[2]
self.five_three_norm_err = lstU_Th[3]
self.six_three_corr = lstU_Th[4]
self.six_three_corr_err = lstU_Th[5]
#Note: Hai's macro only filters 230/229 column
#230/232 filtered measured mean and 2s error
working = isofilter.IsoFilter(filename, "G", 28)
self.zero_two_mean_meas = working.getMean() / 1.02
self.zero_two_counts = working.getCounts()
self.zero_two_standdev_meas = working.getStanddev()
self.zero_two_rel_err_meas = (
2 * self.zero_two_standdev_meas /
(self.zero_two_counts**0.5)) / self.zero_two_mean_meas
self.zero_two_rel_err = max(self.zero_two_rel_err_meas, 0.02)
self.zero_two_err_meas = self.zero_two_mean_meas * self.zero_two_rel_err
#230/229 filtered measured mean and 2s error
working_b = isofilter.IsoFilter(filename, "E", 28)
a = working_b.getMean()
b = working_b.getStanddev()
c = working_b.getCounts()
self.zero_nine_mean_meas = working_b.Filtered_mean(a, b, c)
self.zero_nine_err_meas = working_b.Filtered_err(a, b, c)
#232/229 filtered measured mean and 2s error
working_c = isofilter.IsoFilter(filename, "F", 28)
self.nine_two_mean_meas = working_c.getMean()
self.two_nine_mean_meas = 1 / (self.nine_two_mean_meas / 1.02)
self.two_nine_counts = working.getCounts()
self.nine_two_standdev_meas = working_c.getStanddev()
self.nine_two_rel_err_meas = (
2 * self.nine_two_standdev_meas /
(self.two_nine_counts**0.5)) / self.nine_two_mean_meas
self.two_nine_rel_err = max(self.nine_two_rel_err_meas, 0.02)
self.two_nine_err_meas = self.two_nine_mean_meas * self.two_nine_rel_err
#229 unfiltered mean and counts
working_d = isofilter.IsoFilter(filename, "C", 28)
self.nine_mean_meas = working_d.getMean()
self.nine_counts = working_d.getCounts()
#constants to be used throughout the class
self.wt_233 = 233.039629
self.wt_236 = 236.045563
self.wt_229 = 229.031756
self.wt_230 = 230.033128
self.wt_232 = 232.038051
self.AS_zero_nine = self.AS
self.AS_zero_two = self.AS_zero_nine / 5
self.AS_two_nine = self.AS_zero_two / 3
self.eight_five_rat = 137.83
self.eight_five_rat_err_rel = 0.0003