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Report on flame experiment
{
"metadata": {
"name": "Experiment-Copy1-Copy0"
},
"nbformat": 3,
"nbformat_minor": 0,
"worksheets": [
{
"cells": [
{
"cell_type": "heading",
"level": 1,
"metadata": {},
"source": "Report on the experiment on the signal generated when a gentle flame is applied to the leaf of a tomato plant"
},
{
"cell_type": "code",
"collapsed": false,
"input": "from IPython.core.display import Image\nImage(filename='./flame/flame.jpg')",
"language": "python",
"metadata": {},
"outputs": [
{
"jpeg": 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VQlPGBjNX7kkMwPUHHFUXGe2RVsldiBwc9cEUgXHIqRweR2puMHnpSuBLdXU9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\n",
"output_type": "pyout",
"prompt_number": 46,
"text": "<IPython.core.display.Image at 0xa83a490>"
}
],
"prompt_number": 46
},
{
"cell_type": "code",
"collapsed": false,
"input": "from numpy import *\nfrom scipy import signal\nfrom scipy.signal import filter_design as fd\nfrom matplotlib import pyplot as plt\nimport scipy\nimport scipy.fftpack",
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 47
},
{
"cell_type": "code",
"collapsed": false,
"input": "from nptdms import TdmsFile\ntdms_file_EL1_ref = TdmsFile(\"./flame/data/experimentLS.tdms\")\ntdms_file_EL2_ref = TdmsFile(\"./flame/data/experimentPS.tdms\")\n'''\ngruppi = tdms_file_EL2_ref.groups()\nprint gruppi\nchannels = tdms_file_EL2_ref.group_channels('Untitled')\nprint channels\n'''\nchannel1 = tdms_file_EL1_ref.object('Readings', 'Voltage_0')\ndata1 = channel1.data\ntime1 = channel1.time_track()\nchannel2 = tdms_file_EL2_ref.object('Untitled', 'Voltage_1')\ndata2 = channel2.data\ntime2 = channel2.time_track()\n# do stuff with data\n#sample_per_sec = 1000\nfigsize(20,5)\nfigure(1)\nplot(time1,data1)\nfigure(2)\nplot(time2,data2)",
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "pyout",
"prompt_number": 40,
"text": "[<matplotlib.lines.Line2D at 0x319fdf90>]"
},
{
"output_type": "display_data",
"png": 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{
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}
],
"prompt_number": 40
},
{
"cell_type": "code",
"collapsed": false,
"input": "from scipy.signal import lfilter, firwin\n#------------------------------------------------\n# Create a FIR filter and apply it to signal.\n#------------------------------------------------\n# The Nyquist rate of the signal.\nsample_rate = 1000.\nnyq_rate = sample_rate / 2.\n \n# The cutoff frequency of the filter: 6KHz = 6000.0\ncutoff_hz = 0.2\n#cutoff_hz = 0.003\n \n# Length of the filter (number of coefficients, i.e. the filter order + 1)\nnumtaps = 29\n \n# Use firwin to create a lowpass FIR filter\nfir_coeff = firwin(numtaps, cutoff_hz/nyq_rate)\n \n# Use lfilter to filter the signal with the FIR filter\nfiltered_data1 = lfilter(fir_coeff, 1.0, data1)\nfiltered_data2 = lfilter(fir_coeff, 1.0, data2)",
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 41
},
{
"cell_type": "code",
"collapsed": false,
"input": "figsize(20,5)\nfigure(1)\nplot(time1,filtered_data1)\nfigure(2)\nplot(time2,filtered_data2)",
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "pyout",
"prompt_number": 42,
"text": "[<matplotlib.lines.Line2D at 0x42725b90>]"
},
{
"output_type": "display_data",
"png": 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NwR/34YeHf27OOy98m8xMZ33TJsv65Rezbj8X9rEbb7Ss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\n8fKaWVb3+Oc/JROQiOhWxOASERERdSiWNW+cycmRL4Z79wK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k/scff1y1atVSTk5OkddassRfnzhRSkoKvn/uXOmZZ6SvvpJuvtn27bOPtGGD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\nRK5CYII=\n"
}
],
"prompt_number": 42
},
{
"cell_type": "markdown",
"metadata": {},
"source": "The flame has been applied at time 300. Note the delay in the propagation of the signal which is about 2 minute (120 secs)"
}
],
"metadata": {}
}
]
}
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