Re-Adding the python notebook runfiles
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@@ -0,0 +1,239 @@
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "3a21697e",
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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"import pandas as pd\n",
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"import plotly.express as px\n",
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"import plotly.graph_objects as go\n",
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"from plotly.subplots import make_subplots\n",
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"from pathlib import Path\n",
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"from scipy.optimize import curve_fit"
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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": null,
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"id": "6d9c7578",
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"metadata": {},
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"outputs": [],
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"source": [
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"import ACLC26_comparison_plots_module as cpm"
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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": null,
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"id": "779c2fa6",
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"metadata": {},
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"outputs": [],
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"source": [
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"color_dict = {\n",
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" \"T360U_CO2\": {\"CO2\":\"#807F80\"},\n",
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" \"Ecophysics_NOx_899\": {\"NO\": \"#CC2626\", \"NO2\": \"#0B60AF\", \"NOx\": \"#5533B4\"},\n",
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" \"ICAD_HONO\": {\"HONO\": \"#db2fa8\", \"NO2\": \"#7ddfc9\"}, #\"HONO\": \"#fc9701\" orange\n",
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" \"ICAD_NO2\": {\"NO2\": \"#6cdf72\"}\n",
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" }\n",
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"\n",
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"color_dict2 = {\n",
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" \"T360U_CO2\": {\"CO2\":\"#807F80\"},\n",
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" \"Ecophysics_NOx_899\": {\"NO\": \"#2E73E9\", \"NO2\": \"#A14242\", \"NOx\": \"#644EA0\"},\n",
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" \"ICAD_HONO\": {\"HONO\": \"#BD69E0\", \"NO2\": \"#dd91ca\"}, #\"HONO\": \"#fc9701\" orange\n",
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" \"ICAD_NO2\": {\"NO2\": \"#F9322F\"}\n",
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" }"
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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": null,
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"id": "098925c4",
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"metadata": {},
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"outputs": [],
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"source": [
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"# path to folder where the results of the data analysis were saved\n",
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"savefolderpath = \"C:/Users/leeman_n/OneDrive - Paul Scherrer Institut/Documents/Teaching/2026_AtmosChemLabCourse/ACLC26_DataAnalysis/ACLC26_Output\""
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]
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},
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{
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"cell_type": "markdown",
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"id": "fa780710",
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"metadata": {},
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"source": [
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"Comparison of 3 different experiments with one experiment per panel containing all chosen parameter timeseries:"
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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": null,
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"id": "9a95deca",
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"metadata": {},
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"outputs": [],
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"source": [
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"# compare three different experiments\n",
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"param_list = [\"T360U_CO2-CO2\", \"Ecophysics_NOx_899-NO\", \"Ecophysics_NOx_899-NOx\", \"ICAD_HONO-HONO\", \"ICAD_NO2-NO2\"] # \"Instrument-Parameter\"\n",
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"experiments = [\"20251202_FeCit_CA_Nitrate_1_10_10_RH80\", \"20251204_FeCit_CA_Nitrate_1_10_10_RH50\", \"20251203_CA_Nitrate_1_1_RH80\"] # foldernames from data analysis\n",
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"\n",
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"fig = cpm.compare_3_plots(savefolder_path=savefolderpath, exp_list=experiments,param_list=param_list,color_dict=color_dict)\n",
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"# yrange NOx & HONO (left)\n",
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"fig.update_yaxes(range=(-5,150), row=1, col=1)\n",
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"fig.update_yaxes(range=(-5,300), row=1, col=2)\n",
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"fig.update_yaxes(range=(-2,15), row=1, col=3)\n",
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"# yrange CO2 (right)\n",
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"fig.update_yaxes(range=(-0.5,15), row=1, col=1, secondary_y=True)\n",
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"fig.update_yaxes(range=(-0.5,30), row=1, col=2, secondary_y=True)\n",
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"fig.update_yaxes(range=(-0.2,1.5), row=1, col=3, secondary_y=True)\n",
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"fig.update_layout(height=600, width=1800)\n",
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"\n",
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"\n",
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"#fig.write_html(f\"{savefolderpath}/Comparison_Plots/202612_Comparison_3Experiments.html\") # save interactive plot\n",
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"fig.write_image(f\"{savefolderpath}/Comparison_Plots/202612_Comparison_3Experiments.png\") # save static plot\n",
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"\n",
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"fig.show()"
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]
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},
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{
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"cell_type": "markdown",
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"id": "6cab1e62",
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"metadata": {},
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"source": [
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"Comparison of one parameter timeseries for different experiments in one plot:"
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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": null,
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"id": "4d0b1ac7",
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"metadata": {},
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"outputs": [],
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"source": [
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"# compare for one parameter\n",
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"param_list = [\"ICAD_HONO-HONO\", \"Ecophysics_NOx_899-NOx\"] # values of list elements are added! for one parameter: [\"ICAD_HONO-HONO\"]\n",
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"experiments = [\"20251202_FeCit_CA_Nitrate_1_10_10_RH80\", \"20251204_FeCit_CA_Nitrate_1_10_10_RH50\", \"20251203_CA_Nitrate_1_1_RH80\"]\n",
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"\n",
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"fig = cpm.compare_parameter(savefolder_path=savefolderpath, exp_list=experiments, param_list=param_list)\n",
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"fig.update_layout(height=500, width=1000)\n",
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"fig.show()"
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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": null,
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"id": "204ba2e9",
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"metadata": {},
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"outputs": [],
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"source": [
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"# compile several parameter comparisons in one figure, parameters in [ ] are summed up\n",
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"param_list = [\"T360U_CO2-CO2\", \"ICAD_NO2-NO2\", \"ICAD_HONO-HONO\", \"Ecophysics_NOx_899-NO\", \"Ecophysics_NOx_899-NOx\", [\"ICAD_HONO-HONO\", \"Ecophysics_NOx_899-NOx\"], ]\n",
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"experiments = [\"20251202_FeCit_CA_Nitrate_1_10_10_RH80\", \"20251204_FeCit_CA_Nitrate_1_10_10_RH50\", \"20251203_CA_Nitrate_1_1_RH80\"]\n",
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"\n",
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"layout_dict = {\n",
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" \"nrows\": 2, # number of rows\n",
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" \"ncols\": 3, # number of columns\n",
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" \"hspace\": 0.1, # horizontal space between plots\n",
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" \"vspace\": 0.1, # vertical space between plots\n",
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" \"font_size\": 18, # font size for labels\n",
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" \"title_size\": 16, # font size for titles\n",
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"}\n",
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"\n",
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"# mostly automatically generated subtitles\n",
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"for p in param_list:\n",
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" subts = [p[p.find(\"-\")+1:] + \" (\" + p[:p.find(\"-\")] + \")\" for p in param_list[:-1]]\n",
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"subts.append(\"NOy (HONO + NOx)\") # the one manual subtitle\n",
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"#print(subts)\n",
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"\n",
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"# manual input for subtitles\n",
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"#subts = [\"CO2 (T360U)\", \"NO2 (ICAD NO2)\", \"HONO (ICAD HONO)\", \"NO (Eco NOx)\", \"NOx (Eco NOx)\", \"NOy (HONO + Eco NOx)\"]\n",
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"\n",
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"fig = cpm.compare_n_params(savefolder_path=savefolderpath, exp_list=experiments, param_list=param_list, layout_dict=layout_dict, colors=None, title=None, subtitles=subts)\n",
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"fig.update_layout(height=700, width=1500) # figure size\n",
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"\n",
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"fig.update_yaxes(range=(-0.5,5), row=1, col=1)\n",
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"fig.update_yaxes(range=(-5,50), row=1, col=2)\n",
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"fig.update_yaxes(range=(-5,50), row=1, col=3)\n",
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"fig.update_yaxes(range=(-10,350), row=2, col=1)\n",
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"fig.update_yaxes(range=(-10,350), row=2, col=2)\n",
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"fig.update_yaxes(range=(-10,350), row=2, col=3)\n",
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"\n",
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"#fig.write_html(f\"{savefolderpath}/Comparison_Plots/202612_Comparison_6Panels_RH80_RH50.html\")\n",
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"fig.write_image(f\"{savefolderpath}/Comparison_Plots/202612_Comparison_6Panels_RH80_RH50.png\")\n",
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"fig.show()"
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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": null,
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"id": "26e71bb5",
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"metadata": {},
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"outputs": [],
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"source": [
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"# compile several parameter comparisons in one figure, parameters in [ ] are summed up\n",
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"param_list = [\"T360U_CO2-CO2\", \"ICAD_NO2-NO2\", \"ICAD_HONO-HONO\", \"Ecophysics_NOx_899-NO\", \"Ecophysics_NOx_899-NOx\", [\"ICAD_HONO-HONO\", \"Ecophysics_NOx_899-NOx\"], \n",
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" \"Ecophysics_NOx_899-NO2\", [\"ICAD_NO2-NO2\", \"Ecophysics_NOx_899-NO\"],[\"ICAD_HONO-HONO\", \"ICAD_NO2-NO2\", \"Ecophysics_NOx_899-NO\"]]\n",
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"experiments = [\"20251202_FeCit_CA_Nitrate_1_10_10_RH80\", \"20251204_FeCit_CA_Nitrate_1_10_10_RH50\", \"20251203_CA_Nitrate_1_1_RH80\"]\n",
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"\n",
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"layout_dict = {\n",
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" \"nrows\": 3, # number of rows\n",
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" \"ncols\": 3, # number of columns\n",
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" \"hspace\": 0.1, # horizontal space between plots\n",
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" \"vspace\": 0.1, # vertical space between plots\n",
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" \"font_size\": 18, # font size for labels\n",
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" \"title_size\": 16, # font size for titles\n",
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"}\n",
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"\n",
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"# manual input for subtitles\n",
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"subts = [\"CO2 (T360U)\", \"NO2 (ICAD NO2)\", \"HONO (ICAD HONO)\", \"NO (Eco NOx)\", \"NOx (Eco NOx)\", \"NOy (HONO + Eco NOx)\", \"NO2 (Eco NOx)\", \"NOx v2 (ICAD NO2 + Eco NO)\", \"NOy v2 (ICAD HONO + ICAD NO2 + Eco NO)\"]\n",
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"\n",
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"fig = cpm.compare_n_params(savefolder_path=savefolderpath, exp_list=experiments, param_list=param_list, layout_dict=layout_dict, colors=None, title=None, subtitles=subts)\n",
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"fig.update_layout(height=1000, width=1500) # figure size\n",
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"\n",
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"fig.update_yaxes(range=(-0.5,5), row=1, col=1)\n",
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"fig.update_yaxes(range=(-5,50), row=1, col=2)\n",
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"fig.update_yaxes(range=(-5,50), row=1, col=3)\n",
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"fig.update_yaxes(range=(-10,350), row=2, col=1)\n",
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"fig.update_yaxes(range=(-10,350), row=2, col=2)\n",
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"fig.update_yaxes(range=(-10,350), row=2, col=3)\n",
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"fig.update_yaxes(range=(-10,350), row=3, col=1)\n",
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"fig.update_yaxes(range=(-10,350), row=3, col=2)\n",
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"fig.update_yaxes(range=(-10,350), row=3, col=3)\n",
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"\n",
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"#fig.write_html(f\"{savefolderpath}/Comparison_Plots/202612_Comparison_9Panels_RH80_RH50.html\")\n",
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"fig.write_image(f\"{savefolderpath}/Comparison_Plots/202612_Comparison_9Panels_RH80_RH50.png\")\n",
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"fig.show()"
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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": null,
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"id": "9d0f7b78",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "venv310",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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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": "3.10.19"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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@@ -0,0 +1,971 @@
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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "83bf48ba",
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"metadata": {},
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"source": [
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"# Data Analysis for CWFT Experiments Runfile"
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]
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},
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{
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"cell_type": "markdown",
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"id": "4d16bf54",
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"metadata": {},
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"source": [
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"Atmospheric Chemistry Lab Course 2026 Edition"
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]
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},
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{
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"cell_type": "markdown",
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"id": "9be00b84",
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"metadata": {},
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"source": [
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"Contact nicole.leemann@psi.ch if you encounter any bugs."
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]
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},
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{
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"cell_type": "markdown",
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"id": "4a452fa8",
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"metadata": {},
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"source": [
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"## Import"
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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": null,
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"id": "15c13492",
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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"import pandas as pd\n",
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"import plotly.express as px\n",
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"import plotly.graph_objects as go\n",
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"from plotly.subplots import make_subplots\n",
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"from pathlib import Path\n",
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"from babel.dates import format_date\n",
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"from scipy.optimize import curve_fit\n",
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"import re\n",
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"import ast"
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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": null,
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"id": "0154d14b",
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"metadata": {},
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"outputs": [],
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"source": [
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"import ACLC26_data_analysis_module as dam"
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]
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},
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{
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"cell_type": "markdown",
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"id": "b17b4725",
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"metadata": {},
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"source": [
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"## Initialize Experiment Class"
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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": null,
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"id": "592ecf99",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Input\n",
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"\n",
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"from_summary = False # set to true to load parameters from a summary file instead of manual input\n",
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"\n",
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"savename = \"20251202_FeCit_CA_Nitrate_1_10_10_RH80\" # name that will be used for saving the processed data and data analysis summary of the experiment\n",
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"#savename = \"20251204_FeCit_CA_Nitrate_1_10_10_RH50\"\n",
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"#savename = \"20251203_CA_Nitrate_1_1_RH80\"\n",
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"savefolder = Path(\"C:/Users/leeman_n/OneDrive - Paul Scherrer Institut/Documents/Teaching/2026_AtmosChemLabCourse/ACLC26_DataAnalysis/ACLC26_Output\") / savename # name of the folder to save the outputs and summary of the experiment\n",
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"\n",
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"color_dict = { # colors that will be used for plotting\n",
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" \"T360U_CO2\": [\"#807F80\"], # CO2\n",
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" \"T200_NOx\": [\"#F08080\", \"#84B8E9\", \"#C5A1F5\"], # NO, NO2, NOx \n",
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" \"Ecophysics_NOx_899\": [\"#CC2626\",\"#0B60AF\", \"#5533B4\"], # NO, NO2, NOx\n",
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" \"ICAD_HONO\": [\"#db2fa8\", \"#7ddfc9\"], # HONO, NO2\n",
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" \"ICAD_NO2\": [\"#6cdf72\"] # NO2\n",
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" }\n",
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"\n",
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"if from_summary:\n",
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" FeCit_N = dam.init_from_summary(savefolder, savename, color_dict) # initialize from summary\n",
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"\n",
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"else: # manual input\n",
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" exp_name = \"FeCit/CA/Nitrate 1:10:10 RH 80% (2.12.2026)\" # for plot title (or comparisons)\n",
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"\n",
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" #instrument_list = [\"T360U_CO2\", \"T200_NOx\", \"Ecophysics_NOx_899\", \"ICAD_HONO\", \"ICAD_NO2\", \"Humidity_Sensors\"]\n",
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" instrument_list = [\"T360U_CO2\", \"Ecophysics_NOx_899\", \"ICAD_HONO\", \"ICAD_NO2\", \"Humidity_Sensors\"] # list of all instruments used\n",
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" \n",
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" setup_dict = {\n",
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" \"p_room\": 979, # ambient pressure [mbar]\n",
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" \"T_room\": 23, # room temperature [°C]\n",
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" \"T_tube\": 18, # CWFT temperature [°C]\n",
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" \"T_hum\": 15, # humidifier temperature [°C]\n",
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" \"flow_N2\": 1300, # MFC set flow for N2\n",
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" \"flow_O2\": 300, # MFC set flow for O2\n",
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" \"dilution\": 3000, # MFC set flow for N2 dilution\n",
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" \"dil_BTOF\": 1000, # MFC set flow for BTOF dilution\n",
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" \"tube_length\": 32.6, # tube length [cm]\n",
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" \"tube_diam\": 1.64, # tube inner diameter [cm]\n",
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" \"vol_coat\": 1000 # volume of coating solution [muL]\n",
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" }\n",
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" exp_start = \"2025-12-02 09:00:00\" # YYYY-MM-DD hh:mm:ss (for locating the correct data) \n",
|
||||
" time_tube_in = \"2025-12-02 14:58:19\" # switch from bypass to tube flow \n",
|
||||
" time_lights_on = \"2025-12-02 15:18:25\" # irradiation period\n",
|
||||
" time_lights_off = \"2025-12-02 15:53:37\" \n",
|
||||
" time_lights_on_2 = None # YYYY-MM-DD hh:mm:ss or None # second irradiation period (optional)\n",
|
||||
" time_lights_off_2 = None\n",
|
||||
" time_tube_out = \"2025-12-02 16:09:08\" # switch from tube to bypass flow \n",
|
||||
" exp_end = \"2025-12-02 18:00:00\" # for start and end: choose big enough interval that also includes the timeshifted data \n",
|
||||
"\n",
|
||||
" FeCit_N = dam.experiment(exp_name, instrument_list, setup_dict, exp_start, exp_end, time_tube_in, time_lights_on, time_lights_off, time_tube_out, color_dict, savefolder,\n",
|
||||
" time_lights_on_2, time_lights_off_2) # initialize\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "bf8e0b86",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# set up folders for saving processed data and plots\n",
|
||||
"savefolder.mkdir(parents=True, exist_ok=True) # create folder if it doesn't exist already (parent folder)\n",
|
||||
"\n",
|
||||
"savefolder_data = Path(savefolder) / \"Processed_Data\" # csv files of processed data for each instrument\n",
|
||||
"savefolder_data.mkdir(parents=True, exist_ok=True)\n",
|
||||
"savefolder_plots = Path(savefolder) / \"Plots\" # all saved plots\n",
|
||||
"savefolder_plots.mkdir(parents=True, exist_ok=True)\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "73434a57",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Load raw data"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "92749af5",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"if \"T360U_CO2\" in FeCit_N.instruments:\n",
|
||||
" FeCit_N.get_rawdata_T360U_CO2() \n",
|
||||
" display(FeCit_N.rawdata_co2.head())\n",
|
||||
" print(\"Size: \", FeCit_N.rawdata_co2.shape)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "60744a02",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# if \"T200_NOx\" in FeCit_N.instruments:\n",
|
||||
"# FeCit_N.get_rawdata_T200_NOx()\n",
|
||||
"# display(FeCit_N.rawdata_nox.head())\n",
|
||||
"# print(\"Size: \", FeCit_N.rawdata_nox.shape)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "19002631",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"if \"Humidity_Sensors\" in FeCit_N.instruments:\n",
|
||||
" FeCit_N.get_rawdata_RH()\n",
|
||||
" display(FeCit_N.rawdata_rh.head())\n",
|
||||
" print(\"Size: \", FeCit_N.rawdata_rh.shape)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "f717e5d5",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"if \"ICAD_HONO\" in FeCit_N.instruments:\n",
|
||||
" FeCit_N.get_rawdata_ICAD_HONO()\n",
|
||||
" display(FeCit_N.rawdata_icad_hono.head())\n",
|
||||
" print(\"Size: \", FeCit_N.rawdata_icad_hono.shape)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "85c731f4",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"if \"ICAD_NO2\" in FeCit_N.instruments:\n",
|
||||
" FeCit_N.get_rawdata_ICAD_NO2()\n",
|
||||
" display(FeCit_N.rawdata_icad_no2.head())\n",
|
||||
" print(\"Size: \", FeCit_N.rawdata_icad_no2.shape)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "51a2c112",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"if \"Ecophysics_NOx_899\" in FeCit_N.instruments:\n",
|
||||
" FeCit_N.get_rawdata_NOx_eco()\n",
|
||||
" display(FeCit_N.rawdata_nox_eco.head())\n",
|
||||
" print(\"Size: \", FeCit_N.rawdata_nox_eco.shape)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "07320072",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Preview Plot"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "3f3e99d5",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"For checking and adjusting alignment between instruments"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "e8b2954c",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# copy the output to the cell below for easier adjustment ;)\n",
|
||||
"# set pd.Timestamp(\"None\") to None!\n",
|
||||
"\n",
|
||||
"print(f\"FeCit_N.time_tube_in = pd.Timestamp(\\\"{FeCit_N.time_tube_in}\\\")\")\n",
|
||||
"print(f\"FeCit_N.time_lights_on = pd.Timestamp(\\\"{FeCit_N.time_lights_on}\\\")\")\n",
|
||||
"print(f\"FeCit_N.time_lights_off = pd.Timestamp(\\\"{FeCit_N.time_lights_off}\\\")\")\n",
|
||||
"print(f\"FeCit_N.time_lights_on_2 = pd.Timestamp(\\\"{FeCit_N.time_lights_on_2}\\\")\")\n",
|
||||
"print(f\"FeCit_N.time_lights_off_2 = pd.Timestamp(\\\"{FeCit_N.time_lights_off_2}\\\")\")\n",
|
||||
"print(f\"FeCit_N.time_tube_out = pd.Timestamp(\\\"{FeCit_N.time_tube_out}\\\")\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "152175f8",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# from_summary = False # uncomment this to make adjustments to the parameters from the summary\n",
|
||||
"\n",
|
||||
"if from_summary==False: # only overwrite if not loading from summary\n",
|
||||
"\n",
|
||||
" # set timeshift of instruments (align times to CO2 analyzer)\n",
|
||||
" FeCit_N.timeshift_nox = pd.Timedelta(minutes=0, seconds=0)\n",
|
||||
" FeCit_N.timeshift_nox_eco = pd.Timedelta(minutes=56, seconds=34)\n",
|
||||
" FeCit_N.timeshift_icad_hono = pd.Timedelta(minutes=61, seconds=50)\n",
|
||||
" FeCit_N.timeshift_icad_no2 = pd.Timedelta(minutes=60, seconds=0)\n",
|
||||
" FeCit_N.timeshift_rh = pd.Timedelta(minutes=0, seconds=0)\n",
|
||||
"\n",
|
||||
" # for demo\n",
|
||||
" # FeCit_N.timeshift_nox_eco = pd.Timedelta(minutes=60, seconds=0)\n",
|
||||
" # FeCit_N.timeshift_icad_hono = pd.Timedelta(minutes=60, seconds=0)\n",
|
||||
" # FeCit_N.timeshift_icad_no2 = pd.Timedelta(minutes=60, seconds=0)\n",
|
||||
"\n",
|
||||
" # set irradiation time periods & tube in / out times\n",
|
||||
" FeCit_N.time_tube_in = pd.Timestamp(\"2025-12-02 14:58:19\")\n",
|
||||
" FeCit_N.time_lights_on = pd.Timestamp(\"2025-12-02 15:18:25\")\n",
|
||||
" FeCit_N.time_lights_off = pd.Timestamp(\"2025-12-02 15:53:37\")\n",
|
||||
" FeCit_N.time_lights_on_2 = None\n",
|
||||
" FeCit_N.time_lights_off_2 = None\n",
|
||||
" FeCit_N.time_tube_out = pd.Timestamp(\"2025-12-02 16:09:08\")\n",
|
||||
"\n",
|
||||
" # FeCit_N.time_tube_in = pd.Timestamp(\"2025-12-04 11:47:25\")\n",
|
||||
" # FeCit_N.time_lights_on = pd.Timestamp(\"2025-12-04 12:00:27\")\n",
|
||||
" # FeCit_N.time_lights_off = pd.Timestamp(\"2025-12-04 12:35:41\")\n",
|
||||
" # FeCit_N.time_lights_on_2 = None\n",
|
||||
" # FeCit_N.time_lights_off_2 = None\n",
|
||||
" # FeCit_N.time_tube_out = pd.Timestamp(\"2025-12-04 13:35:26\")\n",
|
||||
"\n",
|
||||
" "
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "44ff59d5",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"preview = FeCit_N.preview_plot(FeCit_N.instruments) # clean up data and make preview plot\n",
|
||||
"#preview.update_xaxes(range=(pd.Timestamp(\"2025-12-04 10:30:00\"), pd.Timestamp(\"2025-12-04 14:30:00\"))) # set x-axis range manually!\n",
|
||||
"preview.update_yaxes(range=(0,5), secondary_y=False) # y-axis range (left)\n",
|
||||
"preview.show()\n",
|
||||
"#preview.write_html(f\"{savefolder_plots}/{savename}_Preview_Plot.html\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "9f65a0b4",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"if \"Humidity_Sensors\" in FeCit_N.instruments:\n",
|
||||
" rhtdp_plot = FeCit_N.RHTDP_plot()\n",
|
||||
" #rhtdp_plot.update_xaxes(range=(pd.Timestamp(\"2025-11-07 13:00:00\"), pd.Timestamp(\"2025-11-07 17:00:00\")))\n",
|
||||
" #rhtdp_plot.update_yaxes(title_text=\"RH [%]\", range=[10, 35], row=1, col=1)\n",
|
||||
" \n",
|
||||
" #rhtdp_plot.show() # uncomment to show the plot"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "45b39e79",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Background Fitting"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "ea43f3ef",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# add column with numeric timeaxis to all datasets\n",
|
||||
"\n",
|
||||
"if \"T360U_CO2\" in FeCit_N.instruments:\n",
|
||||
" FeCit_N.get_num_timeaxis(FeCit_N.predata_co2, ts=pd.Timedelta(minutes=0, seconds=0))\n",
|
||||
"if \"T200_NOx\" in FeCit_N.instruments:\n",
|
||||
" FeCit_N.get_num_timeaxis(FeCit_N.predata_nox, ts=FeCit_N.timeshift_nox)\n",
|
||||
"if \"Ecophysics_NOx_899\" in FeCit_N.instruments:\n",
|
||||
" FeCit_N.get_num_timeaxis(FeCit_N.predata_nox_eco, ts=FeCit_N.timeshift_nox_eco)\n",
|
||||
"if \"ICAD_HONO\" in FeCit_N.instruments:\n",
|
||||
" FeCit_N.get_num_timeaxis(FeCit_N.predata_icad_hono, ts=FeCit_N.timeshift_icad_hono, ts_sign=\"+\")\n",
|
||||
"if \"ICAD_NO2\" in FeCit_N.instruments:\n",
|
||||
" FeCit_N.get_num_timeaxis(FeCit_N.predata_icad_no2, ts=FeCit_N.timeshift_icad_no2, ts_sign=\"+\")\n",
|
||||
"if \"Humidity_Sensors\" in FeCit_N.instruments:\n",
|
||||
" FeCit_N.get_num_timeaxis(FeCit_N.predata_rh, ts=FeCit_N.timeshift_rh)\n",
|
||||
"FeCit_N.predata_icad_hono.head() # preview\n",
|
||||
"FeCit_N.predata_co2.head()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "3cae3223",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# CO2\n",
|
||||
"if \"T360U_CO2\" in FeCit_N.instruments:\n",
|
||||
"\n",
|
||||
" df_data = FeCit_N.predata_co2.copy()\n",
|
||||
" if from_summary==False:\n",
|
||||
" FeCit_N.bkgint_co2 = ['2025-12-02 12:15:00', '2025-12-02 13:30:00'] # manual input interval for bkg fit\n",
|
||||
"\n",
|
||||
" pred_start, pred_end = pd.Timestamp(FeCit_N.bkgint_co2[0]), pd.Timestamp(FeCit_N.bkgint_co2[1]) # if load from summary\n",
|
||||
"\n",
|
||||
" # fit the background with linear function and return plot & fit parameters\n",
|
||||
" bkgfit_plot, popt, pcov, residuals = FeCit_N.get_bkg_fit(df_data, pred_start, pred_end, param=\"raw CO2 [ppm]\", mode=\"lin\")\n",
|
||||
" bkgfit_plot.update_layout(height=500, width=1500) # figure size\n",
|
||||
" bkgfit_plot.update_yaxes(range=(2,4))\n",
|
||||
" #FeCit_N.add_timemarkers(bkgfit_plot) # add yellow rectangle to mark irradiation time\n",
|
||||
" bkgfit_plot.show()\n",
|
||||
" #bkgfit_plot.write_html(f\"{savefolder_plots}/{savename}_Background_T360U_CO2.html\") # save interactive plot\n",
|
||||
" bkgfit_plot.write_image(f\"{savefolder_plots}/{savename}_Background_T360U_CO2.png\") # save static plot\n",
|
||||
"\n",
|
||||
" FeCit_N.bkgcorr_co2 = [popt] # save the parameters of the background fit\n",
|
||||
"\n",
|
||||
" print(popt)\n",
|
||||
"\n",
|
||||
" # residuals_plot = px.scatter(x=df_data[\"Time since Irradiation [min]\"],y=residuals, title=\"residuals\")\n",
|
||||
" # residuals_plot.update_layout(height=500, width=1500)\n",
|
||||
" # residuals_plot.show()\n",
|
||||
"\n",
|
||||
" # y_true = df_data[\"raw CO2 [ppm]\"].to_numpy()\n",
|
||||
" # ss_res = (residuals**2).sum()\n",
|
||||
" # ss_tot = ((y_true - y_true.mean())**2).sum()\n",
|
||||
"\n",
|
||||
" # r2 = 1 - ss_res / ss_tot\n",
|
||||
" # print(r2)\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "f3b108f1",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# NOx eco\n",
|
||||
"if \"Ecophysics_NOx_899\" in FeCit_N.instruments:\n",
|
||||
"\n",
|
||||
" df_data = FeCit_N.predata_nox_eco.copy()\n",
|
||||
" if from_summary==False:\n",
|
||||
" FeCit_N.bkgint_nox_eco = ['2025-12-02 13:00:00', '2025-12-02 15:15:00'] # manual input\n",
|
||||
" #FeCit_N.bkgint_nox_eco = ['2025-12-04 10:40:00', '2025-12-04 12:00:00']\n",
|
||||
"\n",
|
||||
" pred_start, pred_end = pd.Timestamp(FeCit_N.bkgint_nox_eco[0]), pd.Timestamp(FeCit_N.bkgint_nox_eco[1]) # if load from summary\n",
|
||||
"\n",
|
||||
" # individual plots\n",
|
||||
" bkgfit_plot_poly, popt_poly, pcov_poly, resi_poly = FeCit_N.get_bkg_fit(df_data, pred_start, pred_end, param=\"raw NO2 [ppb]\", mode=\"poly\")\n",
|
||||
" #bkgfit_plot_poly.show()\n",
|
||||
" #bkgfit_plot_logdec, popt_logdec, pcov_logdec, resi_logdec = FeCit_N.get_bkg_fit(df_data, pred_start, pred_end, param=\"raw NO2 [ppb]\", mode=\"log_decay\")\n",
|
||||
" #bkgfit_plot_logdec.show()\n",
|
||||
" bkgfit_plot1, popt1, pcov1, resi1 = FeCit_N.get_bkg_fit(df_data, pred_start, pred_end, param=\"raw NO [ppb]\", mode=\"lin\")\n",
|
||||
" #bkgfit_plot1.show()\n",
|
||||
" bkgfit_plot2, popt2, pcov2, resi2 = FeCit_N.get_bkg_fit(df_data, pred_start, pred_end, param=\"raw NO2 [ppb]\", mode=\"lin\")\n",
|
||||
" #bkgfit_plot2.show()\n",
|
||||
" bkgfit_plot3, popt3, pcov3, resi3 = FeCit_N.get_bkg_fit(df_data, pred_start, pred_end, param=\"raw NOx [ppb]\", mode=\"lin\")\n",
|
||||
" #bkgfit_plot3.show()\n",
|
||||
"\n",
|
||||
" # combined plot\n",
|
||||
" fig = make_subplots(\n",
|
||||
" rows=2,\n",
|
||||
" cols=2,\n",
|
||||
" subplot_titles=[\"NO\", \"NO2 lin\", \"NOx\", \"NO2 log decay\"],\n",
|
||||
" horizontal_spacing = 0.03,\n",
|
||||
" vertical_spacing = 0.1\n",
|
||||
" )\n",
|
||||
"\n",
|
||||
" for trace in bkgfit_plot1.data:\n",
|
||||
" fig.add_trace(trace, row=1, col=1)\n",
|
||||
"\n",
|
||||
" for trace in bkgfit_plot2.data:\n",
|
||||
" fig.add_trace(trace, row=1, col=2)\n",
|
||||
"\n",
|
||||
" for trace in bkgfit_plot3.data:\n",
|
||||
" fig.add_trace(trace, row=2, col=1)\n",
|
||||
"\n",
|
||||
" #for trace in bkgfit_plot_logdec.data:\n",
|
||||
" # fig.add_trace(trace, row=2, col=2)\n",
|
||||
"\n",
|
||||
" fig.update_layout(\n",
|
||||
" showlegend=True,\n",
|
||||
" title_text=\"Ecophysics NOx 899\"\n",
|
||||
" )\n",
|
||||
" fig.update_layout(height=750, width=1500)\n",
|
||||
" #FeCit_N.add_timemarkers(fig)\n",
|
||||
" fig.show()\n",
|
||||
" #fig.write_html(f\"{savefolder_plots}/{savename}_Background_Ecophysics_NOx_899.html\")\n",
|
||||
" fig.write_image(f\"{savefolder_plots}/{savename}_Background_Ecophysics_NOx_899.png\") # save static plot\n",
|
||||
"\n",
|
||||
" FeCit_N.bkgcorr_nox_eco = [popt1, popt2, popt3] # save fit parameters\n",
|
||||
" print(FeCit_N.bkgcorr_nox_eco)\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "bada713d",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# NOx\n",
|
||||
"if \"T200_NOx\" in FeCit_N.instruments:\n",
|
||||
"\n",
|
||||
" df_data = FeCit_N.predata_nox.copy()\n",
|
||||
" if from_summary==False:\n",
|
||||
" FeCit_N.bkgint_nox = ['2025-12-02 13:00:00', '2025-12-02 15:15:00'] # manual input\n",
|
||||
"\n",
|
||||
" pred_start, pred_end = pd.Timestamp(FeCit_N.bkgint_nox[0]), pd.Timestamp(FeCit_N.bkgint_nox[1]) # if load from summary\n",
|
||||
" \n",
|
||||
" bkgfit_plot1, popt1, pcov1, resi1 = FeCit_N.get_bkg_fit(df_data, pred_start, pred_end, param=\"raw NO [ppb]\", mode=\"lin\")\n",
|
||||
" #bkgfit_plot1.show()\n",
|
||||
" bkgfit_plot2, popt2, pcov2, resi2 = FeCit_N.get_bkg_fit(df_data, pred_start, pred_end, param=\"raw NO2 [ppb]\", mode=\"lin\")\n",
|
||||
" #bkgfit_plot2.show()\n",
|
||||
" bkgfit_plot3, popt3, pcov3, resi3 = FeCit_N.get_bkg_fit(df_data, pred_start, pred_end, param=\"raw NOx [ppb]\", mode=\"lin\")\n",
|
||||
" #bkgfit_plot3.show()\n",
|
||||
"\n",
|
||||
" fig = make_subplots(\n",
|
||||
" rows=2,\n",
|
||||
" cols=2,\n",
|
||||
" subplot_titles=[\"NO\", \"NO2\", \"NOx\", \" \"],\n",
|
||||
" horizontal_spacing = 0.03,\n",
|
||||
" vertical_spacing = 0.1\n",
|
||||
" )\n",
|
||||
"\n",
|
||||
" for trace in bkgfit_plot1.data:\n",
|
||||
" fig.add_trace(trace, row=1, col=1)\n",
|
||||
"\n",
|
||||
" for trace in bkgfit_plot2.data:\n",
|
||||
" fig.add_trace(trace, row=1, col=2)\n",
|
||||
"\n",
|
||||
" for trace in bkgfit_plot3.data:\n",
|
||||
" fig.add_trace(trace, row=2, col=1)\n",
|
||||
"\n",
|
||||
" fig.update_layout(\n",
|
||||
" #height=800,\n",
|
||||
" showlegend=True,\n",
|
||||
" title_text=\"T200 NOx\"\n",
|
||||
" )\n",
|
||||
" #FeCit_N.add_timemarkers(fig)\n",
|
||||
" fig.update_layout(height=750, width=1500)\n",
|
||||
" fig.show()\n",
|
||||
" #fig.write_html(f\"{savefolder_plots}/{savename}_Background_T200_NOx.html\")\n",
|
||||
" fig.write_image(f\"{savefolder_plots}/{savename}_Background_T200_NOx.png\") # save static plot\n",
|
||||
"\n",
|
||||
" FeCit_N.bkgcorr_nox = [popt1, popt2, popt3] # save fit parameters\n",
|
||||
" print(FeCit_N.bkgcorr_nox)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "68fd32d5",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# ICAD HONO\n",
|
||||
"if \"ICAD_HONO\" in FeCit_N.instruments:\n",
|
||||
"\n",
|
||||
" df_data = FeCit_N.predata_icad_hono.copy()\n",
|
||||
" if from_summary==False:\n",
|
||||
" FeCit_N.bkgint_icad_hono = ['2025-12-02 11:00:00', '2025-12-02 15:00:00'] # manual input\n",
|
||||
"\n",
|
||||
" pred_start, pred_end = pd.Timestamp(FeCit_N.bkgint_icad_hono[0]), pd.Timestamp(FeCit_N.bkgint_icad_hono[1]) # if load from summary\n",
|
||||
" \n",
|
||||
" bkgfit_plot1, popt1, pcov1, resi1 = FeCit_N.get_bkg_fit(df_data, pred_start, pred_end, param=\"raw HONO [ppb]\", mode=\"lin\")\n",
|
||||
" #bkgfit_plot1.show()\n",
|
||||
" bkgfit_plot2, popt2, pcov2, resi2 = FeCit_N.get_bkg_fit(df_data, pred_start, pred_end, param=\"raw NO2 [ppb]\", mode=\"lin\")\n",
|
||||
" #bkgfit_plot2.show()\n",
|
||||
"\n",
|
||||
" fig = make_subplots(\n",
|
||||
" rows=1,\n",
|
||||
" cols=2,\n",
|
||||
" subplot_titles=[\"HONO\", \"NO2\"],\n",
|
||||
" horizontal_spacing = 0.03,\n",
|
||||
" vertical_spacing = 0.1\n",
|
||||
" )\n",
|
||||
"\n",
|
||||
" for trace in bkgfit_plot1.data:\n",
|
||||
" fig.add_trace(trace, row=1, col=1)\n",
|
||||
"\n",
|
||||
" for trace in bkgfit_plot2.data:\n",
|
||||
" fig.add_trace(trace, row=1, col=2)\n",
|
||||
"\n",
|
||||
" #FeCit_N.add_timemarkers(fig)\n",
|
||||
" fig.update_layout(height=450, width=1500, title_text=\"ICAD HONO\")\n",
|
||||
" fig.show()\n",
|
||||
" #fig.write_html(f\"{savefolder_plots}/{savename}_Background_ICAD_HONO.html\")\n",
|
||||
" fig.write_image(f\"{savefolder_plots}/{savename}_Background_ICAD_HONO.png\") # save static plot\n",
|
||||
"\n",
|
||||
" FeCit_N.bkgcorr_icad_hono = [popt1, popt2] # save fit parameters\n",
|
||||
" print(FeCit_N.bkgcorr_icad_hono)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "b9597687",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# ICAD NO2\n",
|
||||
"if \"ICAD_NO2\" in FeCit_N.instruments:\n",
|
||||
" \n",
|
||||
" df_data = FeCit_N.predata_icad_no2.copy()\n",
|
||||
" if from_summary==False:\n",
|
||||
" FeCit_N.bkgint_icad_no2 = ['2025-12-02 12:00:00', '2025-12-02 15:00:00'] # manual input\n",
|
||||
"\n",
|
||||
" pred_start, pred_end = pd.Timestamp(FeCit_N.bkgint_icad_no2[0]), pd.Timestamp(FeCit_N.bkgint_icad_no2[1]) # if load from summary\n",
|
||||
" \n",
|
||||
" bkgfit_plot, popt, pcov, residuals = FeCit_N.get_bkg_fit(df_data, pred_start, pred_end, param=\"raw NO2 [ppb]\", mode=\"lin\")\n",
|
||||
" bkgfit_plot.update_layout(height=500, width=1500)\n",
|
||||
" #FeCit_N.add_timemarkers(bkgfit_plot)\n",
|
||||
" bkgfit_plot.show()\n",
|
||||
" #bkgfit_plot.write_html(f\"{savefolder_plots}/{savename}_Background_ICAD_NO2.html\")\n",
|
||||
" bkgfit_plot.write_image(f\"{savefolder_plots}/{savename}_Background_ICAD_NO2.png\") # save static plot\n",
|
||||
"\n",
|
||||
" FeCit_N.bkgcorr_icad_no2 = [popt] # save fit parameters\n",
|
||||
" print(FeCit_N.bkgcorr_icad_no2)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "1630159c",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Final Processing"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "bb2ad088",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"Finish processing the instrument data (correct for timeshifts, background and dilution) and save the cleaned dataframes in a csv file (one per instrument)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "f2b9eb53",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"FeCit_N.process_data(savefolder, savename)\n",
|
||||
"FeCit_N.data_co2.head() # preview"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "0577973c",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Summary"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "534940ef",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"savefile = f\"{savefolder}/{savename}_DA_Summary.txt\" # save summary of data analysis in this file\n",
|
||||
"FeCit_N.get_summary(savefile)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "3cdfb3ec",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Plots"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "e2b41f4a",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"### One Instrument per Figure"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "e6f6c555",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# CO2\n",
|
||||
"if \"T360U_CO2\" in FeCit_N.instruments:\n",
|
||||
"\n",
|
||||
" #data = pd.read_csv(f\"{savefolder}/Processed_Data/{savename}_Data_T360U_CO2.csv\", sep=';') # get data from file\n",
|
||||
" data = FeCit_N.data_co2.copy() # get data from experiment\n",
|
||||
"\n",
|
||||
" fig_co2 = FeCit_N.plot_one_instrument(instr=\"T360U_CO2\", data=data, plot_raw = False)\n",
|
||||
" fig_co2.update_xaxes(range=(-30, 60))\n",
|
||||
" fig_co2.update_yaxes(range=(-2,35))\n",
|
||||
" #fig_co2.update_yaxes(range=(-0.05,0.5))\n",
|
||||
" fig_co2.update_layout(height=500, width=1500)\n",
|
||||
" fig_co2.update_layout( \n",
|
||||
" margin=dict(l=70, r=210, t=70, b=70) # control margins to keep the plot area consistent between plots\n",
|
||||
" )\n",
|
||||
" fig_co2.show()\n",
|
||||
" #fig_co2.write_html(f\"{savefolder_plots}/{savename}_Plot_T360U_CO2.html\")\n",
|
||||
" fig_co2.write_image(f\"{savefolder_plots}/{savename}_Plot_T360U_CO2.png\") # save static plot"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "f297db4c",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# NOx\n",
|
||||
"if \"T200_NOx\" in FeCit_N.instruments:\n",
|
||||
"\n",
|
||||
" #data = pd.read_csv(f\"{savefolder}/Processed_Data/{savename}_Data_T200_NOx.csv\", sep=';') # get data from file\n",
|
||||
" data = FeCit_N.data_nox.copy() # get data from experiment\n",
|
||||
"\n",
|
||||
" fig_nox = FeCit_N.plot_one_instrument(instr=\"T200_NOx\", data=data, plot_raw = False)\n",
|
||||
" fig_nox.update_xaxes(range=(-30, 60))\n",
|
||||
" #fig_nox.update_yaxes(range=(-10,40))\n",
|
||||
" fig_nox.update_layout(height=500, width=1500)\n",
|
||||
" fig_nox.update_layout(\n",
|
||||
" margin=dict(l=70, r=210, t=70, b=70) # control margins to keep the plot area consistent between plots\n",
|
||||
" )\n",
|
||||
" fig_nox.show()\n",
|
||||
" #fig_nox.write_html(f\"{savefolder_plots}/{savename}_Plot_T200_NOx.html\")\n",
|
||||
" fig_nox.write_image(f\"{savefolder_plots}/{savename}_Plot_T200_NOx.png\") # save static plot"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "774f3ba0",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# NOx eco\n",
|
||||
"if \"Ecophysics_NOx_899\" in FeCit_N.instruments:\n",
|
||||
"\n",
|
||||
" #data = pd.read_csv(f\"{savefolder}/Processed_Data/{savename}_Data_Ecophysics_NOx_899.csv\", sep=';') # get data from file\n",
|
||||
" data = FeCit_N.data_nox_eco.copy() # get data from experiment\n",
|
||||
"\n",
|
||||
" fig_nox_eco = FeCit_N.plot_one_instrument(instr=\"Ecophysics_NOx_899\", data=data, plot_raw = False)\n",
|
||||
" fig_nox_eco.update_xaxes(range=(-30, 60))\n",
|
||||
" #fig_nox_eco.update_yaxes(range=(-5,80))\n",
|
||||
" fig_nox_eco.update_layout(height=500, width=1500)\n",
|
||||
" fig_nox_eco.update_layout(\n",
|
||||
" margin=dict(l=70, r=210, t=70, b=70) # control margins to keep the plot area consistent between plots\n",
|
||||
" )\n",
|
||||
" fig_nox_eco.show()\n",
|
||||
" #fig_nox_eco.write_html(f\"{savefolder_plots}/{savename}_Plot_Ecophysics_NOx_899.html\")\n",
|
||||
" fig_nox_eco.write_image(f\"{savefolder_plots}/{savename}_Plot_Ecophysics_NOx_899.png\") # save static plot"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "4138edbb",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# ICAD HONO\n",
|
||||
"if \"ICAD_HONO\" in FeCit_N.instruments:\n",
|
||||
"\n",
|
||||
" inst = \"ICAD_HONO\"\n",
|
||||
" #data = pd.read_csv(f\"{savefolder}/Processed_Data/{savename}_Data_ICAD_HONO.csv\", sep=';') # get data from file\n",
|
||||
" data = FeCit_N.data_icad_hono.copy() # get data from experiment\n",
|
||||
"\n",
|
||||
" fig_hono = FeCit_N.plot_one_instrument(instr=\"ICAD_HONO\", data=data, plot_raw = False)\n",
|
||||
" fig_hono.update_xaxes(range=(-30, 60))\n",
|
||||
" #fig_hono.update_yaxes(range=(-2,5))\n",
|
||||
" fig_hono.update_layout(height=500, width=1500)\n",
|
||||
" fig_hono.update_layout(\n",
|
||||
" margin=dict(l=70, r=210, t=70, b=70) # control margins to keep the plot area consistent between plots\n",
|
||||
" )\n",
|
||||
" fig_hono.show()\n",
|
||||
" #fig_hono.write_html(f\"{savefolder_plots}/{savename}_Plot_ICAD_HONO.html\")\n",
|
||||
" fig_hono.write_image(f\"{savefolder_plots}/{savename}_Plot_ICAD_HONO.png\") # save static plot"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "5a92726a",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# ICAD NO2\n",
|
||||
"if \"ICAD_NO2\" in FeCit_N.instruments:\n",
|
||||
"\n",
|
||||
" #data = pd.read_csv(f\"{savefolder}/Processed_Data/{savename}_Data_ICAD_NO2.csv\", sep=';') # get data from file\n",
|
||||
" data = FeCit_N.data_icad_no2.copy() # get data from experiment\n",
|
||||
"\n",
|
||||
" fig_no2 = FeCit_N.plot_one_instrument(instr=\"ICAD_NO2\", data=None, plot_raw = False)\n",
|
||||
" fig_no2.update_xaxes(range=(-30, 60))\n",
|
||||
" fig_no2.update_yaxes(range=(-1,8))\n",
|
||||
" fig_no2.update_layout(height=500, width=1500)\n",
|
||||
" fig_no2.update_layout(\n",
|
||||
" margin=dict(l=70, r=210, t=70, b=70) # control margins to keep the plot area consistent between plots\n",
|
||||
" )\n",
|
||||
" fig_no2.show()\n",
|
||||
" #fig_no2.write_html(f\"{savefolder_plots}/{savename}_Plot_ICAD_NO2.html\")\n",
|
||||
" fig_no2.write_image(f\"{savefolder_plots}/{savename}_Plot_ICAD_NO2.png\") # save static plot"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "ff36304f",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"if \"Humidity_Sensors\" in FeCit_N.instruments:\n",
|
||||
"\n",
|
||||
" rh_plot = FeCit_N.RHTDP_plot(num_timeaxis=True) # make RH-temperature-dewpoint plot\n",
|
||||
" FeCit_N.add_timemarkers(rh_plot) # add yellow rectangle to mark irradiation period\n",
|
||||
" rh_plot.update_layout(height=500, width=1500, showlegend=True)\n",
|
||||
" rh_plot.update_xaxes(range=(-30, 60))\n",
|
||||
"\n",
|
||||
" #rh_plot.update_yaxes(range=(20, 30), row=1)\n",
|
||||
" #rh_plot.update_yaxes(range=(-0, 10), row=3)\n",
|
||||
" rh_plot.update_yaxes(range=(10, 30), row=1)\n",
|
||||
" rh_plot.update_yaxes(range=(-5, 5), row=3)\n",
|
||||
"\n",
|
||||
" rh_plot.update_layout(\n",
|
||||
" margin=dict(l=70, r=210, t=70, b=70) # control margins to keep the plot area consistent between plots\n",
|
||||
" )\n",
|
||||
"\n",
|
||||
" # dummy legend for irradiation\n",
|
||||
" rh_plot.add_trace(\n",
|
||||
" go.Scatter(\n",
|
||||
" x=[None],\n",
|
||||
" y=[None],\n",
|
||||
" mode=\"markers\",\n",
|
||||
" marker=dict(\n",
|
||||
" size=12,\n",
|
||||
" symbol=\"square\",\n",
|
||||
" color=\"gold\",\n",
|
||||
" opacity=0.3\n",
|
||||
" ),\n",
|
||||
" name=\"Irradiation\",\n",
|
||||
" showlegend=True,\n",
|
||||
" ),\n",
|
||||
" row=1, col=1\n",
|
||||
" )\n",
|
||||
" rh_plot.show()\n",
|
||||
" #rh_plot.write_html(f\"{savefolder_plots}/{savename}_Plot_Humidity_Sensors.html\")\n",
|
||||
" rh_plot.write_image(f\"{savefolder_plots}/{savename}_Plot_Humidity_Sensors.png\") # save static plot"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "7043e2b1",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"### Multiple Instruments per Figure"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "975678b0",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"Note: Do not plot CO2 here as it will use the wrong yaxis unit label. Use plot_multiple_2axes to plot CO2 with other traces (below)."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "fe45e82b",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"instrs = [\"ICAD_HONO\", \"ICAD_NO2\"] # instruments to plot\n",
|
||||
"title = \"ICADs\"\n",
|
||||
"\n",
|
||||
"if set(instrs).issubset(set(FeCit_N.instruments)): # if chosen instruments were all actually used\n",
|
||||
"\n",
|
||||
" fig_icad = FeCit_N.plot_multiple(title, instrs)\n",
|
||||
" fig_icad.update_xaxes(range=(-30, 60))\n",
|
||||
" fig_icad.update_yaxes(range=(-5,45))\n",
|
||||
" fig_icad.update_layout(height=500, width=1500)\n",
|
||||
" fig_icad.update_layout(\n",
|
||||
" margin=dict(l=70, r=210, t=70, b=70) # control margins to keep the plot area consistent between plots\n",
|
||||
" )\n",
|
||||
" fig_icad.show()\n",
|
||||
" #fig_icad.write_html(f\"{savefolder_plots}/{savename}_Plot_ICADs.html\")\n",
|
||||
" #fig_icad.write_image(f\"{savefolder_plots}/{savename}_Plot_ICADs.png\") # save static plot\n",
|
||||
"else:\n",
|
||||
" print(\"One or more instruments in instrs are not in instrument_list. Skip plot.\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "24bf11de",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"Multiple Instruments Figures with 2 y-axes:"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "7a20aa3c",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"instrs1 = [\"T360U_CO2\"] # instruments to plot on left axis (never mix CO2 with other instruments because of different units)\n",
|
||||
"instrs2 = FeCit_N.instruments[1:-1] # everything except the first (CO2)\n",
|
||||
"title = \"All parameters\"\n",
|
||||
"\n",
|
||||
"if set(instrs1).issubset(set(FeCit_N.instruments)) and set(instrs2).issubset(set(FeCit_N.instruments)):\n",
|
||||
" fig = FeCit_N.plot_multiple_2axes(title, instrs1, instrs2)\n",
|
||||
" fig.update_xaxes(range=(-30, 60))\n",
|
||||
"\n",
|
||||
" ymin, ymax = -5, 35 # y-axis range \n",
|
||||
" #ymin, ymax = -0.5, 1\n",
|
||||
" fig.update_yaxes(range=(ymin,ymax), secondary_y=False)\n",
|
||||
" fig.update_yaxes(range=(ymin*10,ymax*10), secondary_y=True) # right axis scaled based on left axis\n",
|
||||
"\n",
|
||||
" fig.update_layout(height=600, width=1800)\n",
|
||||
" fig.update_layout(\n",
|
||||
" margin=dict(l=70, r=210, t=70, b=70) # control margins to keep the plot area consistent between plots\n",
|
||||
" )\n",
|
||||
" fig.show()\n",
|
||||
" fig.write_html(f\"{savefolder_plots}/{savename}_Plot_All.html\") # save interactive plot\n",
|
||||
" fig.write_image(f\"{savefolder_plots}/{savename}_Plot_All.png\") # save static plot\n",
|
||||
"else:\n",
|
||||
" print(\"One or more instruments in instrs1 or instrs2 are not in instrument_list. Skip plot.\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "d5c913e0",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"instrs1 = [\"Ecophysics_NOx_899\"] # instruments to plot on left axis\n",
|
||||
"instrs2 = [\"ICAD_HONO\", \"ICAD_NO2\"] # instruments to plot on right axis\n",
|
||||
"title = \"NOx analyser vs ICADs\"\n",
|
||||
"\n",
|
||||
"if set(instrs1).issubset(set(FeCit_N.instruments)) and set(instrs2).issubset(set(FeCit_N.instruments)):\n",
|
||||
" fig = FeCit_N.plot_multiple_2axes(title, instrs1, instrs2)\n",
|
||||
" fig.update_xaxes(range=(-30, 60))\n",
|
||||
" #fig.update_yaxes(range=(-10,40))\n",
|
||||
" fig.update_layout(height=500, width=1500)\n",
|
||||
" fig.update_layout(\n",
|
||||
" margin=dict(l=70, r=210, t=70, b=70) # control margins to keep the plot area consistent between plots\n",
|
||||
" )\n",
|
||||
" fig.show()\n",
|
||||
"else:\n",
|
||||
" print(\"One or more instruments in instrs1 or instrs2 are not in instrument_list. Skip plot.\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "8e61aea5",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "venv310",
|
||||
"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": "3.10.19"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
Reference in new issue
Block a user