Updated Notebook files
This commit is contained in:
Radu C. Martin
parent
0afd8dfc79
commit
c915a9e472
25 changed files with 1073 additions and 909 deletions
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@ -1,5 +1,12 @@
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Library to compute solar angles and irradiation components:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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@ -9,6 +16,13 @@
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"import pvlib"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Math libraries:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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@ -65,6 +79,13 @@
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"| 8 | 21.07.2017 20:00 | 24.07.2017 06:00 |"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"First, manually check one experiment to see the available and the missing data."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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@ -110,6 +131,28 @@
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"measured_vals"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"The available data has, therefore, the following columns:"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"| Power | HVAC Electrical Power consumption |\n",
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"|-------------|-----------------------------------|\n",
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"| Setpoint | HVAC Setpoint Temperature |\n",
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"| OutsideTemp | Outside Temperature measurement |\n",
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"| SupplyTemp | HVAC Air Supply Temperature |\n",
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"| InsideTemp | Inside Temperature measurement 1 |\n",
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"| LakeTemp | Inside Temperature measurement 2 |\n",
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"| SolRad | Solar Irradiation measurement |\n",
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"| SolRad_DA | Solar Irradiation, daily average |"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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@ -117,6 +160,13 @@
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"## Transform MATLAB struct to a Dataframe"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Transform one matlab array to a dataframe:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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@ -136,6 +186,13 @@
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" return df_field"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Iterate over the all the experiments and compute the corresponding dataframes:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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@ -147,6 +204,13 @@
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" dict_dfs[var] = df_from_mb_struct(mat_exp1[exp_id], var)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Combine all the dataframes together:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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@ -373,6 +437,13 @@
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"### Export plots necessary in the report"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Plot the electrical power consumption of the HVAC system (including the fans):"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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@ -410,6 +481,13 @@
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"plt.savefig(\"../Thesis/Plots/Fan_baseline.pdf\", bbox_inches='tight')"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Plot the setpoint and measured temperatures:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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@ -727,6 +805,13 @@
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"<img src=\"Images/solar_angles.png\" alt=\"Diagram of the zenith/azimuth angles definition\" width=\"500\"/>"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Compute the solar position angles for all the experimental times of day:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 16,
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@ -1022,6 +1107,13 @@
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"## Compute the Solar radiation components"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Compute `DNI`, `DHI` and `KT` from `GHI`, `zenith` and `datetime` info:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 20,
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@ -1118,6 +1210,13 @@
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"df_erbs.head()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Compute the `GHI` from the Erbs DNI and DHI and compare it with the initially measured values as a sanity check:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 21,
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@ -1127,13 +1226,6 @@
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"erbs_ghi = df_erbs['dhi'] + df_erbs['dni']*np.cos(np.radians(df_solarposition['zenith']))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Compare `erbs_ghi` with measured ghi to confirm they are the same:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 22,
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@ -1460,6 +1552,13 @@
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"df['SolRad']"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Confirm that `poa_components` computes the same values as `get_ground_diffuse` and `get_sky_diffuse`:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 27,
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@ -1481,6 +1580,13 @@
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"print(df_ground_diffuse.equals(df_poa_components['poa_ground_diffuse']))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Plot all the computed irradiance values, compare them to the glocal irradiation, as a sanity check:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 28,
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"# Compile the WDB vector"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"This section compiles the WDB vector as defined in the CARNOT documentation from all the measurements/calculations."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Start by adding the timevalue required by CARNOT -- the number of seconds since the start of the simulation:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 29,
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"df_wdb['poa_diffuse'] = df_poa_components['poa_diffuse']"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Set the unknown values to their respective default values:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 33,
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@ -1628,6 +1755,13 @@
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"df_wdb['time'] = df_wdb['time'].astype('int')"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Make sure all the required columns are present and are in the correct order:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 37,
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.5"
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"version": "3.9.6"
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},
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"toc-autonumbering": true,
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"toc-showcode": false,
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.5"
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"version": "3.9.6"
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},
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"toc-autonumbering": false,
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"toc-showmarkdowntxt": false
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"execution_count": 5,
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"id": "cde7cb35-5a17-4b8a-9fe0-f1b6afe02055",
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"metadata": {},
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"outputs": [],
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"outputs": [
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{
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"ename": "FileNotFoundError",
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"evalue": "[Errno 2] No such file or directory: '../Data/CARNOT_experimental_validation/Exp1_table.csv'",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;31mFileNotFoundError\u001b[0m Traceback (most recent call last)",
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"\u001b[0;32m<ipython-input-5-b08114576033>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0midx\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m8\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mdfs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"../Data/CARNOT_experimental_validation/Exp{idx}_table.csv\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrename\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcolumns\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m{\u001b[0m\u001b[0;34m'Power'\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m'SimulatedHeat'\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3\u001b[0m \u001b[0mdfs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0midx\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'ExperimentTime'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mdfs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0midx\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mTsample\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0;36m24\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0;36m3600\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;32m~/.local/lib/python3.9/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36mread_csv\u001b[0;34m(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, squeeze, prefix, mangle_dupe_cols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, dayfirst, cache_dates, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, doublequote, escapechar, comment, encoding, dialect, error_bad_lines, warn_bad_lines, delim_whitespace, low_memory, memory_map, float_precision, storage_options)\u001b[0m\n\u001b[1;32m 608\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mupdate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkwds_defaults\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 609\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 610\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0m_read\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 611\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 612\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;32m~/.local/lib/python3.9/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m_read\u001b[0;34m(filepath_or_buffer, kwds)\u001b[0m\n\u001b[1;32m 460\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 461\u001b[0m \u001b[0;31m# Create the parser.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 462\u001b[0;31m \u001b[0mparser\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mTextFileReader\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 463\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 464\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mchunksize\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0miterator\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;32m~/.local/lib/python3.9/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, f, engine, **kwds)\u001b[0m\n\u001b[1;32m 817\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moptions\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"has_index_names\"\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"has_index_names\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 818\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 819\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_make_engine\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mengine\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 820\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 821\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mclose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"\u001b[0;32m~/.local/lib/python3.9/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m_make_engine\u001b[0;34m(self, engine)\u001b[0m\n\u001b[1;32m 1048\u001b[0m )\n\u001b[1;32m 1049\u001b[0m \u001b[0;31m# error: Too many arguments for \"ParserBase\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1050\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mmapping\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mengine\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moptions\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# type: ignore[call-arg]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1051\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1052\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_failover_to_python\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"\u001b[0;32m~/.local/lib/python3.9/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, src, **kwds)\u001b[0m\n\u001b[1;32m 1865\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1866\u001b[0m \u001b[0;31m# open handles\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1867\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_open_handles\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msrc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1868\u001b[0m \u001b[0;32massert\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhandles\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1869\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mkey\u001b[0m \u001b[0;32min\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0;34m\"storage_options\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"encoding\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"memory_map\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"compression\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"\u001b[0;32m~/.local/lib/python3.9/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m_open_handles\u001b[0;34m(self, src, kwds)\u001b[0m\n\u001b[1;32m 1360\u001b[0m \u001b[0mLet\u001b[0m \u001b[0mthe\u001b[0m \u001b[0mreaders\u001b[0m \u001b[0mopen\u001b[0m \u001b[0mIOHanldes\u001b[0m \u001b[0mafter\u001b[0m \u001b[0mthey\u001b[0m \u001b[0mare\u001b[0m \u001b[0mdone\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0mtheir\u001b[0m \u001b[0mpotential\u001b[0m \u001b[0mraises\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1361\u001b[0m \"\"\"\n\u001b[0;32m-> 1362\u001b[0;31m self.handles = get_handle(\n\u001b[0m\u001b[1;32m 1363\u001b[0m \u001b[0msrc\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1364\u001b[0m \u001b[0;34m\"r\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"\u001b[0;32m~/.local/lib/python3.9/site-packages/pandas/io/common.py\u001b[0m in \u001b[0;36mget_handle\u001b[0;34m(path_or_buf, mode, encoding, compression, memory_map, is_text, errors, storage_options)\u001b[0m\n\u001b[1;32m 640\u001b[0m \u001b[0merrors\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\"replace\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 641\u001b[0m \u001b[0;31m# Encoding\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 642\u001b[0;31m handle = open(\n\u001b[0m\u001b[1;32m 643\u001b[0m \u001b[0mhandle\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 644\u001b[0m \u001b[0mioargs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmode\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: '../Data/CARNOT_experimental_validation/Exp1_table.csv'"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"for idx in range(1, 8):\n",
|
||||
" dfs.append(pd.read_csv(f\"../Data/CARNOT_experimental_validation/Exp{idx}_table.csv\").rename(columns = {'Power': 'SimulatedHeat'}))\n",
|
||||
|
|
@ -314,7 +333,7 @@
|
|||
"ax3[0].set_ylabel(\"Temperature [°C]\")\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"fig.legend([l1, l2, l3], labels=labels, loc = 'upper right')\n",
|
||||
"#fig.legend([l1, l2, l3], labels=labels, loc = 'upper right')\n",
|
||||
"fig.suptitle(\"Comparison of CARNOT simulation with real Polydome measurements\")\n",
|
||||
"\n",
|
||||
"# Adjusting the sub-plots\n",
|
||||
|
|
@ -361,6 +380,8 @@
|
|||
"\n",
|
||||
"fig.suptitle(\"Experiment 7\")\n",
|
||||
"\n",
|
||||
"fig.legend([l1, l2, l3], labels=labels, loc = 'upper right')\n",
|
||||
"\n",
|
||||
"# Adjusting the sub-plots\n",
|
||||
"plt.subplots_adjust(right=0.95)\n",
|
||||
"fig.subplots_adjust(hspace=0.55)\n",
|
||||
|
|
@ -393,7 +414,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.9.5"
|
||||
"version": "3.9.6"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
|
|
|
|||
|
|
@ -3282,7 +3282,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.9.5"
|
||||
"version": "3.9.6"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
|
|
|
|||
|
|
@ -361,7 +361,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.9.4"
|
||||
"version": "3.9.6"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
|
|
|
|||
|
|
@ -2868,7 +2868,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.9.4"
|
||||
"version": "3.9.6"
|
||||
},
|
||||
"toc-autonumbering": false,
|
||||
"toc-showmarkdowntxt": false,
|
||||
|
|
|
|||
|
|
@ -1476,7 +1476,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.9.4"
|
||||
"version": "3.9.6"
|
||||
},
|
||||
"toc-autonumbering": false,
|
||||
"toc-showmarkdowntxt": false,
|
||||
|
|
|
|||
|
|
@ -978,7 +978,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.9.4"
|
||||
"version": "3.9.5"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
|
|
|
|||
|
|
@ -2953,7 +2953,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.9.4"
|
||||
"version": "3.9.6"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
|
|
|
|||
|
|
@ -3189,7 +3189,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.9.4"
|
||||
"version": "3.9.5"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
|
|
|
|||
|
|
@ -2815,7 +2815,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.9.5"
|
||||
"version": "3.9.6"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
|
|
|
|||
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
|
|
@ -1879,7 +1879,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.9.4"
|
||||
"version": "3.9.6"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
|
|
|
|||
|
|
@ -1326,7 +1326,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.9.4"
|
||||
"version": "3.9.6"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
|
|
|
|||
|
|
@ -1761,7 +1761,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.9.4"
|
||||
"version": "3.9.6"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
|
|
|
|||
|
|
@ -2367,7 +2367,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.9.4"
|
||||
"version": "3.9.6"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
|
|
|
|||
|
|
@ -296,7 +296,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.9.4"
|
||||
"version": "3.9.6"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
|
|
|
|||
|
|
@ -97,7 +97,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.9.4"
|
||||
"version": "3.9.6"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
|
|
|
|||
File diff suppressed because one or more lines are too long
BIN
Notebooks/Performance_test_exps.png
Normal file
BIN
Notebooks/Performance_test_exps.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 336 KiB |
|
|
@ -228,7 +228,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.9.3"
|
||||
"version": "3.9.6"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
|
|
|
|||
BIN
Notebooks/dict_cols.pkl
Normal file
BIN
Notebooks/dict_cols.pkl
Normal file
Binary file not shown.
BIN
Notebooks/gp_model.pkl
Normal file
BIN
Notebooks/gp_model.pkl
Normal file
Binary file not shown.
BIN
Notebooks/prediction_20_steps.png
Normal file
BIN
Notebooks/prediction_20_steps.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 70 KiB |
Loading…
Add table
Add a link
Reference in a new issue