Commit dba917dd authored by amedvedova's avatar amedvedova
Browse files

Added a notebook looking at the calibration of the global radiation sensor

parent 22384e15
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "3dfdd20d",
"metadata": {},
"outputs": [],
"source": [
"# imports\n",
"import numpy as np\n",
"import pandas as pd\n",
"import datetime\n",
"import matplotlib.pyplot as plt"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "dfff3b83",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# load 10-minute data of glom: voltage and W/m^2 values\n",
"tawes_10min = pd.read_csv('tawes_uibk_radiation.txt',\n",
" skiprows=np.arange(0, 83),\n",
" skipfooter=1,\n",
" index_col=0,\n",
" delimiter=r'\\s+',\n",
" engine='python')\n",
"\n",
"# convert index (dates) to human-readable format\n",
"tawes_10min.index = pd.to_datetime(tawes_10min.index.values, unit='s', origin='unix')\n",
"\n",
"# plot glo vs. glow\n",
"plt.plot(tawes_10min.glo, tawes_10min.glow, 'x'); "
]
},
{
"cell_type": "markdown",
"id": "1f75b564",
"metadata": {},
"source": [
"- Interesting, apparently there are two sets of calibration coefficients - but both look linear. Let's see what the coefficients are."
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "b2de0d97",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([ 60. , 63.33333333, 64. , 64.16666667,\n",
" 64.21052632, 64.28571429, 64.28571429, 64.33333333,\n",
" 64.34782609, 64.35897436, 64.375 , 64.38596491,\n",
" 64.3902439 , 64.4 , 64.40677966, 64.41176471,\n",
" 64.41558442, 64.41860465, 64.42105263, 64.42307692,\n",
" 64.42622951, 64.42857143, 64.43037975, 64.43181818,\n",
" 64.43298969, 64.43396226, 64.43478261, 64.44444444,\n",
" 64.45378151, 64.45454545, 64.45544554, 64.45652174,\n",
" 64.45783133, 64.45945946, 64.46153846, 64.46280992,\n",
" 64.46428571, 64.46601942, 64.46808511, 64.47058824,\n",
" 64.47154472, 64.47368421, 64.47619048, 64.47761194,\n",
" 64.47916667, 64.48 , 64.48275862, 64.48275862,\n",
" 64.48598131, 64.48717949, 64.48979592, 64.49152542,\n",
" 64.49275362, 64.49438202, 64.49541284, 64.5 ,\n",
" 64.5045045 , 64.50549451, 64.50704225, 64.50819672,\n",
" 64.50980392, 64.51219512, 64.51327434, 64.51612903,\n",
" 64.52054795, 64.52380952, 64.52830189, 64.53125 ,\n",
" 64.53333333, 64.54545455, 64.56521739, 64.57142857,\n",
" 64.58333333, 64.59459459, 64.61538462, 64.64285714,\n",
" 64.66666667, 64.70588235, 65. , 96.66666667,\n",
" 97.5 , 97.69230769, 97.77777778, 97.82608696,\n",
" 97.85714286, 97.89473684, 97.91666667, 97.93103448,\n",
" 97.94117647, 97.94871795, 97.95454545, 97.95918367,\n",
" 97.96296296, 97.96610169, 97.96875 , 97.97101449,\n",
" 97.97297297, 98. , 98.01652893, 98.01724138,\n",
" 98.01801802, 98.01886792, 98.01980198, 98.02083333,\n",
" 98.02197802, 98.02325581, 98.02469136, 98.02631579,\n",
" 98.02816901, 98.03030303, 98.03278689, 98.03418803,\n",
" 98.03571429, 98.03738318, 98.03921569, 98.04123711,\n",
" 98.04347826, 98.04597701, 98.04878049, 98.05084746,\n",
" 98.05194805, 98.05309735, 98.05555556, 98.05555556,\n",
" 98.05825243, 98.05970149, 98.06122449, 98.06451613,\n",
" 98.06722689, 98.06818182, 98.07017544, 98.07228916,\n",
" 98.0733945 , 98.07692308, 98.08080808, 98.08219178,\n",
" 98.08510638, 98.08823529, 98.08988764, 98.0952381 ,\n",
" 98.0952381 , 98.10126582, 98.10344828, 98.10810811,\n",
" 98.11320755, 98.125 , 98.13953488, 98.14814815,\n",
" 98.15789474, 98.18181818, 98.18181818, 98.21428571,\n",
" 98.23529412, 98.33333333, 98.57142857, 100. ,\n",
" nan])"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"tawes_10min['coeffs'] = tawes_10min['glow'] / tawes_10min['glo']\n",
"\n",
"np.unique(tawes_10min['coeffs'])"
]
},
{
"cell_type": "markdown",
"id": "8cda764a",
"metadata": {},
"source": [
"- Not linear after all! One set of coefficients runs between 60 and 65, the second one between ~96 and 100.\n",
"- When are those two sets used?"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "ead459d4",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x504 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# Plot data as points based on the calibration coefficients\n",
"fig, ax = plt.subplots(figsize=[10, 7])\n",
"tawes_10min.coeffs[tawes_10min['coeffs'] < 65].plot(ax=ax, style='.', ms=1)\n",
"tawes_10min.coeffs[tawes_10min['coeffs'] > 95].plot(ax=ax, style='.', ms=1)\n",
"ax.autoscale(enable=True, axis='x', tight=True);"
]
},
{
"cell_type": "markdown",
"id": "8a7537b7",
"metadata": {},
"source": [
"- Calibration coefficients changed in late 2021 - what happened there?\n",
"- Let's see if the 10 min/1 min data coincide..."
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "76be0da4",
"metadata": {},
"outputs": [],
"source": [
"# load data\n",
"tawes = pd.read_csv('tawes_data.csv', sep=';', skiprows=[0], index_col=0, \n",
" parse_dates=True, infer_datetime_format=True)\n",
"\n",
"# select some data variables\n",
"# Glom: Solar incoming radiation (GLOM): Schenk 8101 (Schenk, Wien) Sternpyranometer sensor, \n",
"# mounted on concrete platform at ACINN rooftop, artificially ventilated and heated\n",
"tawes = tawes[['tl2', 'rf2', 'som', 'glom']]"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "f2a1b02d",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x504 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# Let's compare the raw voltages of 10min / 1 min data\n",
"fig, ax = plt.subplots(figsize=[10, 7])\n",
"tawes.glom.plot(ax=ax, label='1 min')\n",
"tawes_10min.glo.plot(ax=ax, alpha=0.5, label='10 min raw')\n",
"ax.legend(fontsize=14)\n",
"ax.set_ylim(bottom=0)\n",
"ax.autoscale(enable=True, axis='x', tight=True);"
]
},
{
"cell_type": "markdown",
"id": "7abf8a65",
"metadata": {},
"source": [
"- In the 10 min data (orange) we can see when the calibration changed - that's a huge difference!\n",
"- Those two datasets do not coincide much - what happens if I resample the 1 min data to 10 min?"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "b97214af",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x504 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# Get 10 min averages from the 10 min data\n",
"tawes_1_to_10 = tawes.resample('10T').mean()\n",
"\n",
"# Let's compare the raw voltages of 10min / 1 min data\n",
"fig, ax = plt.subplots(figsize=[10, 7])\n",
"tawes_1_to_10.glom.plot(ax=ax, label='1 min resampled')\n",
"tawes_10min.glo.plot(ax=ax, alpha=0.5, label='10 min')\n",
"ax.legend(fontsize=14)\n",
"ax.set_ylim(bottom=0)\n",
"ax.autoscale(enable=True, axis='x', tight=True);"
]
},
{
"cell_type": "markdown",
"id": "14959f74",
"metadata": {},
"source": [
"- That looks better, but it still doesn't match\n",
"- Is there a systematic difference between the two?\n",
"- **TODO:** Check - could it be that the 10-min interval means are \"shifted\"? (e.g. not an average of minutes 00-10, 10-21 etc, but rather 05-15, 15-25..?)\n",
"- Even if, that still doesn't resolve the issue with calibration coefficients - the relationship between mV and W/m^2 is NOT linear and that means that I can't process the 1-minute data"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "9cc3e2b5",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.10"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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