analyzeFourPoint-TempVTime-CarbonFilm.ipynb

Kernel: Python 2 (SageMath)

from IPython.core.display import HTML
def css_styling():
    styles = open("custom.css", "r").read()
    return HTML(styles)
css_styling()

AnalyzeFourPointCond

Notebook for analyzing four-point conductance measurements. This notebook only plots the temperature versus time.

Import and set up the notebook.

%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
import scipy.odr as odr
import glob, re

Get Data File

dataFiles = glob.glob('*.csv')
for (i,file) in enumerate(dataFiles):
    print "%d, %s" % (i, file)
iFile = int(raw_input("Enter data file number: "))
dataFile = dataFiles[iFile]
fpData = open(dataFile, 'r')

# Dump the file comments
for line in fpData.readlines():
    if line[0] == '#' and "Temp" not in line:
        print line.strip()
fpData.seek(0)

0, readArduino-201804171428.csv
1, test.csv
2, readArduino-201804191455.csv
3, readArduino-201804121033-Original.csv
4, readArduino-201804121033-Fixed.csv

Enter data file number: 

# readArduino.py
# Tue Apr 17 14:28:30 2018
# wired R

Read Data

fpData.seek(0,0)
temperature = []
resistance = []
resUncert = []

done = False
iLine = 0
nLines = 0
nTemps = 0
while not done:
  try:
    line = fpData.readline().strip()
    if not line:
        done = True
        continue
    nLines += 1
    iLine += 1
    # Check for beginning of a temperature point
    if "#Therm" in line:
        nTemps += 1
        line = fpData.readline().strip()
        nLines += 1
        I = np.zeros((16,), dtype=float)
        V = np.zeros((16,), dtype=float)
        fields = line.split(',')
        temperature.append(float(fields[0]))
        I[0] = float(fields[1])
        V[0] = float(fields[2])
        for i in range(1,16):
            line = fpData.readline().strip()
            nLines += 1
            fields = line.split(',')
            I[i] = float(fields[0])
            V[i] = float(fields[1])
        z, cov = np.polyfit(I, V, 1, cov=True)
        resistance.append(1e3 * z[0])
        resUncert.append(1e3 * np.sqrt(cov[0,0]))
  except:
    print """
ERROR! 
     ERROR!
          ERROR!
               ERROR! 
on line """, nLines
    break
temperature = np.array(temperature)
resistance = np.array(resistance)
resUncert = np.array(resUncert)
print "There are {} lines in the file".format(nLines)
print "There are {} data points".format(nTemps)
print "Last temperature is {}".format(temperature[-1])
print "The last I data are {}".format(I)
print "The last V data are {}".format(V)
print "The last temperature is {} C".format(temperature[-1])
print "The last resistance is {:.2f} +/- {:.2f} Ohms".format(resistance[-1], resUncert[-1])

ERROR! 
     ERROR!
          ERROR!
               ERROR! 
on line  13
There are 13 lines in the file
There are 1 data points
Last temperature is 24.77
The last I data are [ 0.    0.34  0.69  1.03  1.37  1.71  2.06  2.4   0.    0.    0.    0.    0.
  0.    0.    0.  ]
The last V data are [-0.83 -0.8  -0.68 -0.64 -0.49 -0.38 -0.3  -0.15  0.    0.    0.    0.    0.
  0.    0.    0.  ]
The last temperature is 24.77 C

---------------------------------------------------------------------------
IndexError                                Traceback (most recent call last)
<ipython-input-10-c46b9bf1ccfa> in <module>()
     53 print "The last V data are {}".format(V)
     54 print "The last temperature is {} C".format(temperature[-1])
---> 55 print "The last resistance is {:.2f} +/- {:.2f} Ohms".format(resistance[-1], resUncert[-1])

IndexError: index -1 is out of bounds for axis 0 with size 0

Plotting Data Nicely

The cool down happens very fast so the thremistor is cooling much faster than the resistor. So I want to separate the data into two batches, the cool down data, then the data we care about when the temperature slowly went back up.

First I will plot the temperature versus time data. Then work on an algorithm to find when the temperature starts up.

def moving_average(a, n=3) :
    ret = np.cumsum(a, dtype=float)
    ret[n:] = ret[n:] - ret[:-n]
    return ret[n - 1:] / n
# Smooth the temperature
tMA = moving_average(temperature, 10)
minTemp = np.min(tMA)
cool0 = 0
# step through and wait for t to get with in 2.0 of min temp
for (i,t) in enumerate(tMA):
    if t - minTemp < 1.0:
        break
cool1 = i
# Now step form there to where temp starts up
for (i,t) in enumerate(tMA[cool1:]):
    if t - minTemp > 1.5:
        break
cool2 = i + cool1
print cool0, cool1, cool2
    
fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot(range(cool2), tMA[:cool2]+273.15, 'r.')
ax.plot(range(cool2,len(tMA)), tMA[cool2:]+273.15, 'b.')
ax.set_ylabel("Temperture (K)")
ax.set_xlabel("Time (s)")
ax.set_title("R vs T, 330 $\Omega$ Carbon ")

0 28 48

<matplotlib.text.Text at 0x7f0d280be7d0>

fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot(temperature[:cool2]+273.15, resistance[:cool2], 'r.', label="Cooling")
ax.plot(temperature[cool2:]+273.15, resistance[cool2:], 'b.', label="Warming")
ax.set_xlabel("Temperture (K)")
ax.set_ylabel("Resistance ($\Omega$)")
ax.set_title("R vs T, 330 $\Omega$ Carbon ")
ax.legend(loc=3)

<matplotlib.legend.Legend at 0x7f0d285d3210>

print len(temperature)
tMA = moving_average(temperature, 10)
print len(tMA)

3090
3081