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I am trying to get the derivative of this CSV data set, and this is code I have so far I thought it would be similar to this matlab code:

dy=diff(y)./diff(x)
plot(x(2:end),dy)

This is my attempt at the code:

import csv
data = list( csv.reader(open('C:/images/TEST1.txt','rU')) )
data = map(lambda x: [float(x[0]),float(x[1])],data)
P = list_plot(data, plotjoined= True, color = 'blue', xmin = 0, xmax = 3)
TeraHertz = text('Tera Hertz', (1.5,-.9)) 
Absorbance = text('Absorbance', (0.8,5))
g = P + TeraHertz + Absorbance
g.show()
latex(g)
g.save('TeraHertzTEST1.pgf')
t=diff(x[1]).diff(x[0])
l = plot(x[0],t)
l.show()

I am trying to get the derivative of this CSV data set, and this is code I have so far I thought it would be similar to this matlab code:

dy=diff(y)./diff(x)
plot(x(2:end),dy)

Data Set:

0,2.58612
0.00616025,2.20018
0.0123205,1.56186
0.0184807,0.371172
0.024641,0.327379
0.0308012,0.368863
0.0369615,0.322228
0.0431217,0.171899
0.049282,-0.0635003
0.0554422,-0.110747
0.0616025,0.0701394
0.0677627,0.202381
0.073923,0.241264
0.0800832,0.193697
0.0862434,0.0797016
0.0924037,0.0103144
0.0985639,0.096153
0.104724,0.216782

There's more data...a lot more This is my attempt at the code:

import csv
data = list( csv.reader(open('C:/images/TEST1.txt','rU')) )
data = map(lambda x: [float(x[0]),float(x[1])],data)
P = list_plot(data, plotjoined= True, color = 'blue', xmin = 0, xmax = 3)
TeraHertz = text('Tera Hertz', (1.5,-.9)) 
Absorbance = text('Absorbance', (0.8,5))
g = P + TeraHertz + Absorbance
g.show()
latex(g)
g.save('TeraHertzTEST1.pgf')
t=diff(x[1]).diff(x[0])
l = plot(x[0],t)
l.show()

I am trying to get the derivative of this CSV data set, and this is code I have so far I thought it would be similar to this matlab code:

dy=diff(y)./diff(x)
plot(x(2:end),dy)

Data Set:

0,2.58612
0.00616025,2.20018
0.0123205,1.56186
0.0184807,0.371172
0.024641,0.327379
0.0308012,0.368863
0.0369615,0.322228
0.0431217,0.171899
0.049282,-0.0635003
0.0554422,-0.110747
0.0616025,0.0701394
0.0677627,0.202381
0.073923,0.241264
0.0800832,0.193697
0.0862434,0.0797016
0.0924037,0.0103144
0.0985639,0.096153
0.104724,0.216782

There's more data...a lot more This is my attempt at the code:

import csv
data = list( csv.reader(open('C:/images/TEST1.txt','rU')) )
data = map(lambda x: [float(x[0]),float(x[1])],data)
P = list_plot(data, plotjoined= True, color = 'blue', xmin = 0, xmax = 3)
TeraHertz = text('Tera Hertz', (1.5,-.9)) 
Absorbance = text('Absorbance', (0.8,5))
g = P + TeraHertz + Absorbance
g.show()
latex(g)
g.save('TeraHertzTEST1.pgf')
t=diff(x[1]).diff(x[0])
l = plot(x[0],t)
l.show()

I am trying to get the derivative of this CSV data set, and this is code I have so far I thought it would be similar to this matlab code:

dy=diff(y)./diff(x)
plot(x(2:end),dy)

Data Set:

0,2.58612
0.00616025,2.20018
0.0123205,1.56186
0.0184807,0.371172
0.024641,0.327379
0.0308012,0.368863
0.0369615,0.322228
0.0431217,0.171899
0.049282,-0.0635003
0.0554422,-0.110747
0.0616025,0.0701394
0.0677627,0.202381
0.073923,0.241264
0.0800832,0.193697
0.0862434,0.0797016
0.0924037,0.0103144
0.0985639,0.096153
0.104724,0.216782

There's more data...a lot more This is my attempt at the code:

import csv
data = list( csv.reader(open('C:/images/TEST1.txt','rU')) )
data = map(lambda x: [float(x[0]),float(x[1])],data)
P = list_plot(data, plotjoined= True, color = 'blue', xmin = 0, xmax = 3)
TeraHertz = text('Tera Hertz', (1.5,-.9)) 
Absorbance = text('Absorbance', (0.8,5))
g = P + TeraHertz + Absorbance
g.show()
latex(g)
g.save('TeraHertzTEST1.pgf')
t=diff(x[1]).diff(x[0])
l = plot(x[0],t)
l.show()