{ "cells": [ { "attachments": {}, "cell_type": "markdown", "id": "b192c227", "metadata": {}, "source": [ "# Reiche Zeche Hydro-Geochemical Data Analysis\n", "\n", "A jupyter notebook to summarize and visualize the data from the Reiche Zeche hydro-geochemical data. " ] }, { "cell_type": "code", "execution_count": 26, "id": "a6905205-6c71-43c1-bc0b-09fc0a7beb47", "metadata": {}, "outputs": [], "source": [ "#setup system\n", "%matplotlib inline\n", "import numpy as np\n", "import pandas as pd\n", "import plotly.express as px\n", "import plotly.graph_objects as go\n", "import plotly.subplots as spx\n", "from scipy.stats import linregress\n", "from matplotlib.colors import LinearSegmentedColormap, to_hex\n", "\n", "#for hysteresis analysis\n", "import hysteresis_analysis as hys" ] }, { "cell_type": "code", "execution_count": null, "id": "ce6d20a3", "metadata": {}, "outputs": [], "source": [ "#Legacy compatibility of site naming:\n", "#Site 1 -> C4\n", "#Site 2 -> A12\n", "#Site 3A -> B4\n", "#Site 3B -> B3" ] }, { "cell_type": "markdown", "id": "cb75e96f", "metadata": {}, "source": [ "## General Data" ] }, { "cell_type": "code", "execution_count": 3, "id": "6e81c15c", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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rsdstassfcWindvabarPrecEToPMscPDSISMI
date
2021-01-011.63801.6559442.4034970.5753640.00.5411790.359917NaN
2021-01-021.89180.6416672.2763890.5532430.00.4790790.386655NaN
2021-01-031.1910-0.0131942.3562500.5919434.60.1878520.413394NaN
2021-01-040.85680.0111111.4062500.6128040.00.1046630.440132NaN
2021-01-050.8310-0.1131941.9631940.6036291.40.1016300.466870NaN
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" ], "text/plain": [ " rsds tas sfcWind vabar Prec EToPM scPDSI \\\n", "date \n", "2021-01-01 1.6380 1.655944 2.403497 0.575364 0.0 0.541179 0.359917 \n", "2021-01-02 1.8918 0.641667 2.276389 0.553243 0.0 0.479079 0.386655 \n", "2021-01-03 1.1910 -0.013194 2.356250 0.591943 4.6 0.187852 0.413394 \n", "2021-01-04 0.8568 0.011111 1.406250 0.612804 0.0 0.104663 0.440132 \n", "2021-01-05 0.8310 -0.113194 1.963194 0.603629 1.4 0.101630 0.466870 \n", "\n", " SMI \n", "date \n", "2021-01-01 NaN \n", "2021-01-02 NaN \n", "2021-01-03 NaN \n", "2021-01-04 NaN \n", "2021-01-05 NaN " ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#Meteo data\n", "meteod = pd.read_csv('Meteo.csv', index_col=0)\n", "meteod.index = pd.to_datetime(meteod.index)\n", "meteod.head()" ] }, { "cell_type": "code", "execution_count": 4, "id": "f90d38d9", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Site 1Site 2Site 3BSite 3AHydPhase
time
2022-02-02 09:00:00NaNNaN389.975938589.665971Flush
2022-02-02 10:00:00NaNNaN386.301252586.192299Flush
2022-02-02 11:00:00NaNNaN382.626566582.718627Flush
2022-02-02 12:00:00NaNNaN380.014839580.273554Flush
2022-02-02 13:00:00NaNNaN382.819680583.556714Flush
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" ], "text/plain": [ " Site 1 Site 2 Site 3B Site 3A HydPhase\n", "time \n", "2022-02-02 09:00:00 NaN NaN 389.975938 589.665971 Flush\n", "2022-02-02 10:00:00 NaN NaN 386.301252 586.192299 Flush\n", "2022-02-02 11:00:00 NaN NaN 382.626566 582.718627 Flush\n", "2022-02-02 12:00:00 NaN NaN 380.014839 580.273554 Flush\n", "2022-02-02 13:00:00 NaN NaN 382.819680 583.556714 Flush" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#Flow data\n", "Qx = pd.read_csv('Flow.csv', index_col=0)\n", "Qx.index = pd.to_datetime(Qx.index)\n", "\n", "#Flow phases:\n", "#Qx['HydPhase'] = 'Flush'\n", "#Qx.loc['2022-02-25':'2022-08-12', 'HydPhase'] = 'Declining'\n", "#Qx.loc['2022-08-12':'2023-02-03', 'HydPhase'] = 'Low Flow'\n", "#Qx.loc['2023-05-05':'2023-09-22', 'HydPhase'] = 'Declining'\n", "#Qx.loc['2023-09-22':'2023-12-12', 'HydPhase'] = 'Low Flow' \n", "\n", "Qx.head()\n", "#px.scatter(x=Qx.index, y=np.ones(len(Qx)), color=Qx.HydPhase, template='none')" ] }, { "cell_type": "code", "execution_count": 5, "id": "57f55582", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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campaignsite_idECpHlevel_numdoc_mgLdic_mgLdateMn_mgLNi_mgL...Cd_mgLPb_mgLFe_mgLAl_mgLCu_mgLZn_mgLQ_mLsPLIEventHydPhase
Sample_ID
B11_011B1115172.7530.73540.32792022-02-025.42600.04224...0.396400.370919.90005.99401.588044.770NaN515.82Flush, Year 1flush
B3_011B34013.7831.22500.32932022-02-020.44160.01535...0.057140.44090.58470.81340.16315.320386.3094.82Flush, Year 1flush
B4_011B45633.4130.69480.38072022-02-021.23700.02052...0.149700.87841.51502.54600.360513.720582.72192.51Flush, Year 1flush
B6_011B67483.1730.57540.67882022-02-021.89500.02888...0.232600.74831.51804.83900.543220.130NaN242.41Flush, Year 1flush
A6_022A64294.1221.20000.29192022-02-170.78480.01330...0.064930.15470.10251.26600.12945.397NaN69.84Flush, Year 1flush
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5 rows × 21 columns

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" ], "text/plain": [ " campaign site_id EC pH level_num doc_mgL dic_mgL \\\n", "Sample_ID \n", "B11_01 1 B11 1517 2.75 3 0.7354 0.3279 \n", "B3_01 1 B3 401 3.78 3 1.2250 0.3293 \n", "B4_01 1 B4 563 3.41 3 0.6948 0.3807 \n", "B6_01 1 B6 748 3.17 3 0.5754 0.6788 \n", "A6_02 2 A6 429 4.12 2 1.2000 0.2919 \n", "\n", " date Mn_mgL Ni_mgL ... Cd_mgL Pb_mgL Fe_mgL Al_mgL \\\n", "Sample_ID ... \n", "B11_01 2022-02-02 5.4260 0.04224 ... 0.39640 0.3709 19.9000 5.9940 \n", "B3_01 2022-02-02 0.4416 0.01535 ... 0.05714 0.4409 0.5847 0.8134 \n", "B4_01 2022-02-02 1.2370 0.02052 ... 0.14970 0.8784 1.5150 2.5460 \n", "B6_01 2022-02-02 1.8950 0.02888 ... 0.23260 0.7483 1.5180 4.8390 \n", "A6_02 2022-02-17 0.7848 0.01330 ... 0.06493 0.1547 0.1025 1.2660 \n", "\n", " Cu_mgL Zn_mgL Q_mLs PLI Event HydPhase \n", "Sample_ID \n", "B11_01 1.5880 44.770 NaN 515.82 Flush, Year 1 flush \n", "B3_01 0.1631 5.320 386.30 94.82 Flush, Year 1 flush \n", "B4_01 0.3605 13.720 582.72 192.51 Flush, Year 1 flush \n", "B6_01 0.5432 20.130 NaN 242.41 Flush, Year 1 flush \n", "A6_02 0.1294 5.397 NaN 69.84 Flush, Year 1 flush \n", "\n", "[5 rows x 21 columns]" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#Physicochemical data\n", "pcd = pd.read_csv('Fulldat_PC.csv',index_col=0)\n", "pcd.date = pd.to_datetime(pcd.date)\n", "\n", "#pcd = pcd.loc[pcd.date.sort_values().index] \n", "\n", "#Flow phases:\n", "pcd['HydPhase'] = 'flush'\n", "pcd.loc[(pcd.date>=pd.to_datetime('2022-02-25')) & (pcd.date<=pd.to_datetime('2022-08-12')), 'HydPhase'] = 'declining'\n", "pcd.loc[(pcd.date>=pd.to_datetime('2022-08-12')) & (pcd.date<=pd.to_datetime('2023-02-03')), 'HydPhase'] = 'low flow'\n", "pcd.loc[(pcd.date>=pd.to_datetime('2023-05-05')) & (pcd.date<=pd.to_datetime('2023-09-22')), 'HydPhase'] = 'declining'\n", "pcd.loc[(pcd.date>=pd.to_datetime('2023-09-22')) & (pcd.date<=pd.to_datetime('2023-12-12')), 'HydPhase'] = 'low flow' \n", "\n", "pcd.head()" ] }, { "cell_type": "code", "execution_count": 6, "id": "af990d4b", "metadata": {}, "outputs": [ { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plot.ly" }, "data": [ { "fillpattern": { "shape": "" }, "hovertemplate": "variable=wet
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Reiche Zeche" }, "tracegroupgap": 0 }, "margin": { "t": 60 }, "template": { "data": { "scatter": [ { "type": "scatter" } ] } }, "xaxis": { "anchor": "y", "domain": [ 0, 1 ], "range": [ "2022-02-02T09:00:00", "2024-03-06T09:00:00" ], "title": { "text": "" } }, "yaxis": { "anchor": "x", "domain": [ 0, 1 ], "title": { "text": "Discharge Q (mL/s)" } } } } }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# plot flow data\n", "Qx1 = Qx.iloc[:,:4].rolling('5D').mean()\n", "fig = px.line(Qx1*np.nan,template='none')#.update_traces(marker=dict(opacity=1, size=2)) #,marginal_y='box'\n", "fig.add_trace(go.Scatter(x=Qx1.index, y=Qx1['Site 1'], mode='lines', name='Site 1', line_color='#1f77b4', showlegend=False))\n", "fig.add_trace(go.Scatter(x=Qx1.index, y=Qx1['Site 2'], mode='lines', name='Site 2', line_color='#ff7f0e', showlegend=False))\n", "fig.add_trace(go.Scatter(x=Qx1.index, y=Qx1['Site 3B'], mode='lines', name='Site 3B', line_color='#2ca02c', showlegend=False))\n", "fig.add_trace(go.Scatter(x=Qx1.index, y=Qx1['Site 3A'], mode='lines', name='Site 3A', line_color='#d62728', showlegend=False))\n", "\n", "fig.update_layout(xaxis_title='', yaxis_title='Discharge Q (mL/s)', legend_title_text='Gauges
Reiche Zeche',xaxis_range=[Qx.index[0],Qx.index[-1]])\n", "fig.show()" ] }, { "cell_type": "code", "execution_count": 10, "id": "5d3194c5", "metadata": {}, "outputs": [ { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plot.ly" }, "data": [ { "hovertemplate": "site_id=B11
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"figmp.add_trace(go.Scatter(x=pcd.loc[pcd.site_id.str.contains('C4'),'date'], y=pcd.loc[pcd.site_id.str.contains('C4'),'PLI'], mode='lines+markers', name='Site 1', line_color='#1f77b4'))\n", "figmp.add_trace(go.Scatter(x=pcd.loc[pcd.site_id.str.contains('A12'),'date'], y=pcd.loc[pcd.site_id.str.contains('A12'),'PLI'], mode='lines+markers', name='Site 2', line_color='#ff7f0e'))\n", "figmp.add_trace(go.Scatter(x=pcd.loc[pcd.site_id.str.contains('B3'),'date'], y=pcd.loc[pcd.site_id.str.contains('B3'),'PLI'], mode='lines+markers', name='Site 3B', line_color='#2ca02c'))\n", "figmp.add_trace(go.Scatter(x=pcd.loc[pcd.site_id.str.contains('B4'),'date'], y=pcd.loc[pcd.site_id.str.contains('B4'),'PLI'], mode='lines+markers', name='Site 3A', line_color='#d62728'))\n", "labels_to_show_in_legend = ['Site 1', 'Site 2', 'Site 3A', 'Site 3B']\n", "for trace in figmp['data']: \n", " if (not trace['name'] in labels_to_show_in_legend):\n", " trace['showlegend'] = False\n", 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Index (PLI)" } } } } }, "metadata": {}, "output_type": "display_data" } ], "source": [ "\n", "figx = spx.make_subplots(rows=4, cols=1, row_heights=[0.1, 0.1, 0.4, 0.4])\n", "\n", "figsc_traces = []\n", "fig_traces = []\n", "figp_traces = []\n", "figmp_traces = []\n", "for trace in range(len(figsc[\"data\"])):\n", " figsc_traces.append(figsc[\"data\"][trace])\n", "for trace in range(len(figp[\"data\"])):\n", " figp_traces.append(figp[\"data\"][trace])\n", "for trace in range(len(fig[\"data\"])):\n", " fig_traces.append(fig[\"data\"][trace])\n", "for trace in range(len(figmp[\"data\"])):\n", " figmp_traces.append(figmp[\"data\"][trace])\n", "\n", "for traces in figsc_traces:\n", " figx.append_trace(traces, row=1, col=1)\n", "for traces in figp_traces:\n", " figx.append_trace(traces, row=2, col=1)\n", "for traces in fig_traces:\n", " figx.append_trace(traces, row=3, col=1)\n", "for traces in figmp_traces:\n", " figx.append_trace(traces, row=4, col=1)\n", "\n", "\n", "figx.update_layout(template='none')\n", "figx.update_xaxes(range=[Qx.index[0],Qx.index[-1]])\n", "figx['layout']['yaxis']['title']='Drought
index'\n", "figx['layout']['yaxis2']['title']='Precip
(mm/14d)'\n", "figx['layout']['yaxis3']['title']='Drainage
Q (mL/s)'\n", "figx['layout']['yaxis4']['title']='Pollution Load
Index (PLI)'\n", "figx['layout']['yaxis4']['range']=[0,1500]\n", "figx.show()\n", "#figx.write_image('hygc_RZ.pdf',width=1200,height=800)" ] }, { "cell_type": "code", "execution_count": null, "id": "ce93f27f", "metadata": {}, "outputs": [ { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plot.ly" }, "data": [ { "fillpattern": { "shape": "" }, "hovertemplate": "site_id=B3
date=%{x}
load=%{y}", "legendgroup": "B3", "line": { "color": "#1F77B4" }, "marker": { "symbol": "circle" }, "mode": "lines", "name": "B3", "orientation": "v", "showlegend": true, "stackgroup": "1", "type": "scatter", "x": [ "2022-02-02T00:00:00", "2022-03-01T00:00:00", "2022-03-14T00:00:00", "2022-03-28T00:00:00", "2022-04-21T00:00:00", "2022-05-12T00:00:00", "2022-06-07T00:00:00", "2022-06-28T00:00:00", "2022-06-30T00:00:00", "2022-07-19T00:00:00", "2022-08-12T00:00:00", "2022-08-29T00:00:00", "2022-09-01T00:00:00", "2022-09-22T00:00:00", "2022-10-13T00:00:00", "2022-11-02T00:00:00", "2022-11-29T00:00:00", "2022-12-20T00:00:00", "2023-01-25T00:00:00", "2023-02-09T00:00:00", "2023-02-21T00:00:00", "2023-03-21T00:00:00", "2023-04-13T00:00:00", "2023-05-05T00:00:00", "2023-05-26T00:00:00", "2023-06-19T00:00:00", "2023-07-12T00:00:00", "2023-11-09T00:00:00", "2023-12-12T00:00:00", "2024-01-16T00:00:00", "2024-02-12T00:00:00", "2024-03-06T00:00:00", "2024-05-13T00:00:00" ], "xaxis": "x", "y": [ 0.17756202240000002, 0.18220567679999997, 0.213524309088, 0.23928574176, 0.30087251712, 0.33746651136, 0.46122332256, 0.75901900608, 0.56337907104, 0.57713427072, 0.63799221024, 0.64748076192, 0.6144196377600001, 0.6019029648000002, 0.55215939168, 0.61128489024, 0.6801129100800001, 0.8944490880000001, 0.6325672320000001, 0.33912400896000006, 0.4687517952, 0.33695098070400004, 0.31031830598399995, 0.31233969792, 0.2783334528, 0.33170974848000007, 0.36657194111999997, 0.6279267225600002, 0.96138136224, 0.253220414976, 0.26865271296000004, 0.216177278976, 0.30057851519999995 ], "yaxis": "y" }, { "fillpattern": { "shape": "" }, "hovertemplate": "site_id=B4
date=%{x}
load=%{y}", "legendgroup": "B4", "line": { "color": "#FF7F0E" }, "marker": { "symbol": "circle" }, "mode": "lines", "name": "B4", "orientation": "v", "showlegend": true, "stackgroup": "1", "type": "scatter", "x": [ "2022-02-02T00:00:00", "2022-03-01T00:00:00", "2022-03-28T00:00:00", "2022-04-21T00:00:00", "2022-05-12T00:00:00", "2022-06-07T00:00:00", "2022-06-28T00:00:00", "2022-06-30T00:00:00", "2022-07-19T00:00:00", "2022-08-12T00:00:00", "2022-08-29T00:00:00", "2022-09-22T00:00:00", "2022-10-13T00:00:00", "2022-11-02T00:00:00", "2022-11-29T00:00:00", "2022-12-20T00:00:00", "2023-01-25T00:00:00", "2023-02-09T00:00:00", "2023-02-21T00:00:00", "2023-03-21T00:00:00", "2023-04-13T00:00:00", "2023-05-05T00:00:00", "2023-05-26T00:00:00", "2023-06-19T00:00:00", "2023-07-12T00:00:00", "2023-08-03T00:00:00", "2023-09-07T00:00:00", "2023-10-18T00:00:00", "2023-11-09T00:00:00", "2023-12-12T00:00:00", "2024-01-16T00:00:00", "2024-02-12T00:00:00", "2024-03-06T00:00:00" ], "xaxis": "x", "y": [ 0.69076094976, 0.7431015945599999, 1.1151719625599998, 1.29121579008, 1.55378094912, 1.25580590784, 1.1037104495999999, 1.5636364070400002, 1.62796713408, 1.6189427923200002, 1.51973870976, 1.3881681331199998, 1.2659326444799996, 2.7872381664, 3.389392512, 4.82134464, 8.4491092224, 1.2612008448, 0.9753180192, 0.59432308416, 0.6353259494400001, 0.6476889168, 0.9423107568, 1.5206395680000002, 1.7484462144000001, 1.2749355417600001, 2.1625532927999997, 3.6207518399999996, 4.8556765440000005, 6.2837555328, 0.35103024000000005, 0.434834352, 0.19245478175999997 ], "yaxis": "y" } ], "layout": { "legend": { "title": { "text": "site_id" }, "tracegroupgap": 0 }, "margin": { "t": 60 }, "template": { "data": { "scatter": [ { "type": "scatter" } ] } }, "xaxis": { "anchor": "y", "domain": [ 0, 1 ], "range": [ "2022-02-02T09:00:00", "2024-03-06T09:00:00" ], "title": { "text": "date" } }, "yaxis": { "anchor": "x", "domain": [ 0, 1 ], "title": { "text": "load" } } } } }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#Zn load plot\n", "dummy = pd.DataFrame((0.000001*(pcd.Q_mLs*86.4*pcd.Zn_mgL)).dropna())\n", "dummy.columns = ['load']\n", "dummy['site_id'] = pcd.loc[dummy.index,'site_id']\n", "dummy.index = pcd.loc[dummy.index,'date']\n", "\n", "fig2 = px.area(dummy.loc[dummy.site_id.str.contains('B3|B4')], y='load', color='site_id', template='none')\n", "fig2.update_xaxes(range=[Qx.index[0],Qx.index[-1]])\n", "fig2.show()\n", "#fig2.write_image('load_Zn.pdf',width=1200,height=300)" ] }, { "cell_type": "code", "execution_count": 13, "id": "550521fa", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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y1_1y1_2y2_1y2_2d1_1d1_2d2_1d2_2peakshare1peaktime1peakshare2peaktime2
B3124.49671065.52812887.46818548.473897272.093.0255.061.00.3448400.2547950.3565780.193038
B4350.209069452.144716299.949926300.123740272.093.0255.061.00.5635230.2547950.5001450.193038
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" ], "text/plain": [ " y1_1 y1_2 y2_1 y2_2 d1_1 d1_2 d2_1 d2_2 \\\n", "B3 124.496710 65.528128 87.468185 48.473897 272.0 93.0 255.0 61.0 \n", "B4 350.209069 452.144716 299.949926 300.123740 272.0 93.0 255.0 61.0 \n", "\n", " peakshare1 peaktime1 peakshare2 peaktime2 \n", "B3 0.344840 0.254795 0.356578 0.193038 \n", "B4 0.563523 0.254795 0.500145 0.193038 " ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# calculate load shares\n", "d0='2022-02-02'\n", "d1='2022-11-01'\n", "d2='2023-02-02'\n", "d3='2023-10-15'\n", "d4='2023-12-15'\n", "\n", "six='B3'\n", "y1_1 = dummy.loc[(dummy.site_id.str.contains(six)) & (dummy.index=d1) & (dummy.indexd2) & (dummy.index=d3) & (dummy.index=d1) & (dummy.indexd2) & (dummy.index=d3) & (dummy.index\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
2H_m2H_cal2H_err18O_m18O_cal18O_errkxdatecampaignpositiondev_meddev_med_posIdentifier_mine1Group
P
P-165-68.916000-68.2605030.080500-9.797500-9.7370970.0202509.02022-03-013A15.0022511.227158A1_3Mine
P-175-68.060000-67.4162290.026593-10.042667-10.0263200.01605210.02022-03-013A14.1936050.393474A1_3Mine
P-176-68.175333-67.5345430.171197-10.037000-10.0194960.04243710.02022-03-013A24.3096440.681456A2_3Mine
P-177-66.564667-65.9213050.117667-9.738333-9.7170120.04931710.02022-03-013A32.6705420.442339A3_3Mine
P-178-64.123333-63.4762810.021111-9.433000-9.4080640.01276410.02022-03-013A40.2068280.374180A4_3Mine
.............................................
P-9629-35.521667-35.2514460.029827-4.891667-5.1201380.005884603.02020-07-080NaNNaNNaNNaNPrecip
P-10098-33.202000-33.5979480.044713-4.124333-4.4944330.011850628.02020-07-250NaNNaNNaNNaNPrecip
P-10099-35.339667-35.7084450.079220-5.271333-5.6108090.006481628.02020-08-020NaNNaNNaNNaNPrecip
P-10399-36.400667-36.8537450.358990-5.472333-5.7220690.046503643.02024-08-210NaNNaNNaNNaNPrecip
P-11016-44.398667-43.8745040.051910-7.465333-7.4852710.013948677.02024-09-160NaNNaNNaNNaNPrecip
\n", "

1484 rows × 14 columns

\n", "" ], "text/plain": [ " 2H_m 2H_cal 2H_err 18O_m 18O_cal 18O_err \\\n", "P \n", "P-165 -68.916000 -68.260503 0.080500 -9.797500 -9.737097 0.020250 \n", "P-175 -68.060000 -67.416229 0.026593 -10.042667 -10.026320 0.016052 \n", "P-176 -68.175333 -67.534543 0.171197 -10.037000 -10.019496 0.042437 \n", "P-177 -66.564667 -65.921305 0.117667 -9.738333 -9.717012 0.049317 \n", "P-178 -64.123333 -63.476281 0.021111 -9.433000 -9.408064 0.012764 \n", "... ... ... ... ... ... ... \n", "P-9629 -35.521667 -35.251446 0.029827 -4.891667 -5.120138 0.005884 \n", "P-10098 -33.202000 -33.597948 0.044713 -4.124333 -4.494433 0.011850 \n", "P-10099 -35.339667 -35.708445 0.079220 -5.271333 -5.610809 0.006481 \n", "P-10399 -36.400667 -36.853745 0.358990 -5.472333 -5.722069 0.046503 \n", "P-11016 -44.398667 -43.874504 0.051910 -7.465333 -7.485271 0.013948 \n", "\n", " kx date campaign position dev_med dev_med_pos \\\n", "P \n", "P-165 9.0 2022-03-01 3 A1 5.002251 1.227158 \n", "P-175 10.0 2022-03-01 3 A1 4.193605 0.393474 \n", "P-176 10.0 2022-03-01 3 A2 4.309644 0.681456 \n", "P-177 10.0 2022-03-01 3 A3 2.670542 0.442339 \n", "P-178 10.0 2022-03-01 3 A4 0.206828 0.374180 \n", "... ... ... ... ... ... ... \n", "P-9629 603.0 2020-07-08 0 NaN NaN NaN \n", "P-10098 628.0 2020-07-25 0 NaN NaN NaN \n", "P-10099 628.0 2020-08-02 0 NaN NaN NaN \n", "P-10399 643.0 2024-08-21 0 NaN NaN NaN \n", "P-11016 677.0 2024-09-16 0 NaN NaN NaN \n", "\n", " Identifier_mine1 Group \n", "P \n", "P-165 A1_3 Mine \n", "P-175 A1_3 Mine \n", "P-176 A2_3 Mine \n", "P-177 A3_3 Mine \n", "P-178 A4_3 Mine \n", "... ... ... \n", "P-9629 NaN Precip \n", "P-10098 NaN Precip \n", "P-10099 NaN Precip \n", "P-10399 NaN Precip \n", "P-11016 NaN Precip \n", "\n", "[1484 rows x 14 columns]" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# read in isotope data\n", "isodata = pd.read_csv('Isotopes.csv',index_col=0)\n", "isodata.date = pd.to_datetime(isodata.date)\n", "isodata = isodata[['2H_m', '2H_cal', '2H_err', '18O_m', '18O_cal', '18O_err', 'kx', 'date',\n", " 'campaign', 'position', 'dev_med', 'dev_med_pos', 'Identifier_mine1', 'Group']] \n", "isodata.campaign = isodata.campaign.values.astype(int)\n", "isodata\n" ] }, { "cell_type": "code", "execution_count": 15, "id": "43dd719e", "metadata": {}, "outputs": [ { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plot.ly" }, "data": [ { "hovertemplate": "variable=std_all
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}, "template": { "data": { "scatter": [ { "type": "scatter" } ] } }, "xaxis": { "anchor": "y", "domain": [ 0, 1 ], "range": [ "2022-02-02T09:00:00", "2024-03-06T09:00:00" ], "title": { "text": "date" } }, "yaxis": { "anchor": "x", "domain": [ 0, 1 ], "title": { "text": "value" }, "type": "log" } } } }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# isotopic difference time series\n", "\n", "cqi2 = pd.merge(cqi,loc_dev,how='left',left_on='campaign',right_on='campaign')\n", "#fig3 = px.scatter(cqi2,x='date',y=['std_all','std_2/3','std_3','std_2/3A','std_2/3B'],template='none')\n", "fig3 = px.scatter(cqi2,x='date',y=['std_2/3B','std_2/3A'],template='none',log_y=True)#, marginal_y='box')\n", "# Add vertical lines connecting the pairs\n", "for date in cqi2['date'].unique():\n", " # Get the two y-values for this date\n", " subset = cqi2[cqi2['date'] == date]\n", " if len(subset) >= 2: # Ensure we have both values\n", " y_values = [subset['std_2/3A'].iloc[0], subset['std_2/3B'].iloc[0]]\n", " # Remove any NaN values\n", " y_values = [y for y in y_values if not pd.isna(y)]\n", " \n", " if len(y_values) == 2:\n", " fig3.add_trace(go.Scatter(\n", " x=[date, date],\n", " y=[min(y_values), max(y_values)],\n", " mode='lines',\n", " line=dict(color='gray', width=1),\n", " showlegend=False,\n", " hoverinfo='skip'\n", " ))\n", "\n", "fig3.update_xaxes(range=[Qx.index[0],Qx.index[-1]])\n", "fig3.show()\n", "#fig3.write_image('isodiff.pdf',width=1200,height=300)" ] }, { "cell_type": "code", "execution_count": 17, "id": "103530c2", "metadata": {}, "outputs": [], "source": [ "# read site 2 autosampler data plus sampling data from stratification analysis \n", "autosampler = pd.read_csv('Site2_autosampler_PC.csv',index_col=0)\n", "autosampler.date = pd.to_datetime(autosampler.date)\n", "autosampler['dss'] = autosampler.date - autosampler.date.min()\n", "autosampler['doy'] = autosampler.date.dt.dayofyear\n", "#autosampler\n", "\n", "stratsample = pd.read_csv('Site2_stratified_sampling_PC.csv',index_col=0)\n", "stratsample.date = pd.to_datetime(stratsample.date)\n", "stratsample['dss'] = stratsample.date - autosampler.date.min()\n", "stratsample['doy'] = stratsample.date.dt.dayofyear\n", "#stratsample\n", "\n", "spec = pd.read_csv('Site2_spectrolyzer_autosampler_prediction.csv',index_col=0)\n", "spec['date'] = pd.to_datetime(spec.index)\n", "spec['dss'] = spec.date - autosampler.date.min()\n", "spec.dss = spec.dss.dt.days\n", "spec['doy'] = spec.date.dt.dayofyear\n", "#spec daily\n", "\n", "spechourly = pd.read_csv('Site2_Cdspec_Qlogg_hourly.csv')\n", "spechourly['date'] = pd.to_datetime(spechourly['date'], utc=True)\n", "#spec hourly \n" ] }, { "cell_type": "code", "execution_count": null, "id": "1ac9e8cd", "metadata": {}, "outputs": [ { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plot.ly" }, "data": [ { "marker": { "color": "black", "symbol": "cross" }, "mode": "markers", "name": 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], "y": [ 0.11, 0.18, 3.55, 0.35 ] } ], "layout": { "legend": { "font": { "size": 18 }, "orientation": "h", "x": 0, "xanchor": "left", "y": 4, "yanchor": "top" }, "template": { "data": { "scatter": [ { "type": "scatter" } ] } }, "xaxis": { "dtick": "M2", "range": [ "2022-05-01", "2023-03-01" ], "tickfont": { "size": 18 }, "title": { "font": { "size": 20 }, "text": "Date" } }, "yaxis": { "tickfont": { "size": 18 }, "title": { "font": { "size": 20 }, "text": "Cd (mg L⁻¹)" }, "type": "log" } } } }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#time series plot for Cd\n", "\n", "# 1. Get bottom points (Top sampling group)\n", "top_df = stratsample.loc[stratsample.Group == 'Top sampling'].copy()\n", "top_df = top_df[(top_df.date >= '2022-06-28') & (top_df.date <= '2022-10-13')]\n", "top_df = top_df.sort_values('date') # ensure proper order\n", "\n", "# 2. Define polygon by stacking bottom then top\n", "x_poly = list(top_df.date) + list(top_df.date[::-1]) # bottom + reversed top\n", "y_poly = list(top_df.Cd_mgL) + [6]*len(top_df) #time series plot\n", "\n", "#time series plot\n", "cmapx = [(0,'#e6f598'),(0.1,'#ffffbf'),(0.2,'#fee08b'),(0.3,'#fdae61'),(0.4,'#f46d43'),(0.5,'#d53e4f'),(0.6,'#9e0142'),(0.7,'#abdda4'),(0.8,'#66c2a5'),(0.9,'#3288bd'),(1,'#5e4fa2')]\n", "\n", "figa = go.Figure()\n", "\n", "\n", "figa.add_trace(go.Scatter(x=stratsample.loc[stratsample.Group=='Top sampling','date'], y=stratsample.loc[stratsample.Group=='Top sampling','Cd_mgL'], mode='markers', marker_symbol='cross', marker_color='black', name='Top'))\n", "figa.add_trace(go.Scatter(x=stratsample.loc[stratsample.Group=='Bottom sampling','date'], y=stratsample.loc[stratsample.Group=='Bottom sampling','Cd_mgL'], mode='markers', marker_symbol='x', marker_color='darkmagenta', name='Bottom'))\n", "\n", "figa.add_trace(go.Scatter(x=stratsample.loc[stratsample.date>'2022-10-12'].loc[stratsample.Group=='Top sampling','date'], y=stratsample.loc[stratsample.date>'2022-10-12'].loc[stratsample.Group=='Top sampling','Cd_mgL'], showlegend=False,\n", "fill=None,line=dict(width=0), mode='lines', line_color='lightgray',opacity=0.2))\n", "figa.add_trace(go.Scatter(x=stratsample.loc[stratsample.date>'2022-10-12'].loc[stratsample.Group=='Bottom sampling','date'], y=stratsample.loc[stratsample.date>'2022-10-12'].loc[stratsample.Group=='Bottom sampling','Cd_mgL'], showlegend=False,\n", "fill='tonexty',line=dict(width=0), mode='lines', line_color='lightgray',opacity=0.3))\n", "\n", "# 3. Add filled shape using Scatter\n", "figa.add_trace(go.Scatter(x=x_poly,y=y_poly,mode='none', fill='toself',fillcolor='lightgray',line=dict(width=0),opacity=0.4,showlegend=True,name = 'Stratification',hoverinfo='skip'))\n", "\n", "figa.update_xaxes(range=['2022-05-01', '2023-03-01'],title=dict(text='Date', font=dict(size=20)), tickfont=dict(size=18),dtick=\"M2\")\n", "\n", "figa.update_yaxes(type=\"log\",title=dict(text='Cd (mg L⁻¹)', font=dict(size=20)), tickfont=dict(size=18))\n", "\n", "\n", "figa.update_layout(legend=dict(orientation=\"h\",x=0,y=4,xanchor=\"left\",yanchor=\"top\",font=dict(size=18)),template='none')\n", "\n", "#dont need to show spec daily points if i am showing hourly points, just want the color scale here\n", "figa.add_trace(go.Scatter(x=spec['date'],y=spec['Cd_pred'],mode='markers',name='Spectrolyzer daily',marker=dict(color=spec['dss'],colorscale=cmapx,colorbar=dict(title=dict(text='Days'))),marker_symbol='cross', opacity = 0, showlegend=False))\n", "figa.add_trace(go.Scatter(x=spechourly['date'],y=spechourly['Cd_pred'],mode='markers',name='Spectrolyzer',marker=dict(color=spechourly['time_index'],colorscale=cmapx,showscale=False)))\n", "figa.add_trace(go.Scatter(x=autosampler.date, y=autosampler.Cd_mgL, mode='markers', marker_symbol='circle-open', marker_color='black', name='Autosampler', opacity=0.6))\n", "\n", "\n", "figa.add_trace(go.Scatter(x=['2022-06-07', '2022-06-28', '2022-06-28', '2022-06-07'],y=[0.11, 0.18, 3.55, 0.35],mode='none',fill='toself',fillcolor='lightgrey', line=dict(width=0),opacity=0.4,showlegend=False,hoverinfo='skip'))\n", "\n", "#figa.add_trace(go.Scatter(x=spec.date, y=spec.Cd_pred, marker=dict(color=spec.dss, colorscale=cmapx, colorbar=dict(title=dict(text='Days'))),mode='markers'))\n", "figa.show()\n", "#figa.write_image('cd_time_series.pdf',width=800,height=600)\n", "\n" ] }, { "cell_type": "code", "execution_count": null, "id": "6fce1c4c", "metadata": {}, "outputs": [ { "data": { 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271.869202633479, 270.151578277406, 259.486426663724, 255.090456992519, 242.957314410208, 242.629867690887 ] } ], "layout": { "legend": { "font": { "size": 18 }, "orientation": "h", "x": 0, "xanchor": "left", "y": 4, "yanchor": "top" }, "template": { "data": { "scatter": [ { "type": "scatter" } ] } }, "xaxis": { "dtick": "M2", "range": [ "2022-05-01", "2023-03-01" ], "tickfont": { "size": 18 }, "title": { "font": { "size": 20 }, "text": "Date" } }, "yaxis": { "tickfont": { "size": 18 }, "tickvals": [ 0, 500, 1000 ], "title": { "font": { "size": 20 }, "text": "Q (mL s⁻¹)" } } } } }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#time series plot for Q\n", "cmapx = [(0,'#e6f598'),(0.1,'#ffffbf'),(0.2,'#fee08b'),(0.3,'#fdae61'),(0.4,'#f46d43'),(0.5,'#d53e4f'),(0.6,'#9e0142'),(0.7,'#abdda4'),(0.8,'#66c2a5'),(0.9,'#3288bd'),(1,'#5e4fa2')]\n", "\n", "figa = go.Figure()\n", "#dont need to show spec daily points if i am showing hourly points, just want the color scale here\n", "figa.add_trace(go.Scatter(x=spec['date'],y=spec['Q_mLs'],mode='markers',name='Spectrolyzer daily',marker=dict(color=spec['dss'],colorscale=cmapx,colorbar=dict(title=dict(text='Days'))),marker_symbol='cross', opacity = 0, showlegend=False))\n", "figa.add_trace(go.Scatter(x=spechourly['date'],y=spechourly['Q_mLs'],mode='markers',name='Spectrolyzer',marker=dict(color=spechourly['time_index'],colorscale=cmapx,showscale=False)))\n", "\n", "figa.update_xaxes(range=['2022-05-01', '2023-03-01'],title=dict(text='Date', font=dict(size=20)), tickfont=dict(size=18),dtick=\"M2\" )\n", "figa.update_yaxes(title=dict(text='Q (mL s⁻¹)', font=dict(size=20)),tickfont=dict(size=18),tickvals=[0, 500, 1000] )\n", "figa.update_layout(legend=dict(orientation=\"h\",x=0,y=4,xanchor=\"left\",yanchor=\"top\",font=dict(size=18)),template='none')\n", "\n", "figa.show()\n", "#figa.write_image('cdq_time_series.pdf',width=800,height=250)" ] }, { "cell_type": "code", "execution_count": null, "id": "0d727f47", 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sampling','Q_mLs'], y=stratsample.loc[stratsample.Group=='Top sampling','Cd_mgL'], mode='markers', marker_symbol='cross', marker_color='black', name='Top'))\n", "fig.add_trace(go.Scatter(x=stratsample.loc[stratsample.Group=='Bottom sampling','Q_mLs'], y=stratsample.loc[stratsample.Group=='Bottom sampling','Cd_mgL'], mode='markers', marker_symbol='x', marker_color='darkmagenta', name='Bottom'))\n", "\n", "fig.update_xaxes(type=\"log\",title=dict(text='Q (mL s⁻¹)') )\n", "fig.update_yaxes(type=\"log\", title=dict(text='Cd (mg L⁻¹)') )\n", "fig.update_layout(legend=dict(orientation=\"h\",x=0,y=4,xanchor=\"left\",yanchor=\"top\",font=dict(size=18)),template='none')\n", "\n", "#dont need to show spec daily points if i am showing hourly points, just want the color scale here\n", "fig.add_trace(go.Scatter(x=spec['Q_mLs'],y=spec['Cd_pred'],mode='markers',name='Spectrolyzer daily',marker=dict(color=spec['dss'],colorscale=cmapx,colorbar=dict(title=dict(text='Days'))),marker_symbol='cross', opacity = 0, showlegend=False))\n", "fig.add_trace(go.Scatter(x=spechourly['Q_mLs'],y=spechourly['Cd_pred'],mode='markers',name='Spectrolyzer',marker=dict(color=spechourly['time_index'],colorscale=cmapx,showscale=False)))\n", "fig.add_trace(go.Scatter(x=autosampler.Q_mLs, y=autosampler.Cd_mgL, mode='markers', marker_symbol='circle-open', marker_color='black', name='Autosampler', opacity=0.6))\n", "\n", "fig.update_xaxes(range=[0.9,3])\n", "fig.show()\n", "#fig.write_image('autosampler_cq.pdf',width=600,height=600)" ] }, { "cell_type": "code", "execution_count": null, "id": "9fdd4bea", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/var/folders/89/fb19llwd13zf7jxq9r7t2c3h0000gn/T/ipykernel_54439/716012427.py:4: SettingWithCopyWarning:\n", "\n", "\n", "A value is trying to be set on a copy of a slice from a DataFrame.\n", "Try using .loc[row_indexer,col_indexer] = value instead\n", "\n", "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", "\n", "/var/folders/89/fb19llwd13zf7jxq9r7t2c3h0000gn/T/ipykernel_54439/716012427.py:34: SettingWithCopyWarning:\n", "\n", "\n", "A value is trying to be set on a copy of a slice from a DataFrame.\n", "Try using .loc[row_indexer,col_indexer] = value instead\n", "\n", "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", "\n" ] }, { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plot.ly" }, "data": [ { "marker": { "color": "lightgray" }, "mode": "markers", "name": "Other Dates", "type": "scatter", "x": [ "2022-03-14T10:00:00+00:00", "2022-03-14T11:00:00+00:00", "2022-03-14T12:00:00+00:00", "2022-03-14T13:00:00+00:00", "2022-03-14T14:00:00+00:00", "2022-03-14T15:00:00+00:00", "2022-03-14T16:00:00+00:00", "2022-03-14T17:00:00+00:00", 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'orange',\n", " '2022-12-29': 'green',\n", " '2022-12-30': 'blue',\n", " '2022-12-31': 'purple',\n", " '2023-01-07': 'red',\n", " '2023-01-08': 'orange',\n", " '2023-01-09': 'green',\n", " '2023-01-10': 'blue',\n", " '2023-01-11': 'purple',\n", " '2023-01-14': 'red',\n", " '2023-01-15': 'orange',\n", " '2023-01-16': 'green',\n", " '2023-01-17': 'blue',\n", " '2023-01-18': 'purple',\n", " '2023-02-01': 'red',\n", " '2023-02-02': 'orange',\n", " '2023-02-03': 'green',\n", " '2023-02-04': 'blue',\n", " '2023-02-05': 'purple',\n", "}\n", "\n", "# Convert dates to string for matching\n", "spch['date_str'] = spch['date'].astype(str)\n", "\n", "# Split gray vs. colored points\n", "df_gray = spch[~spch['date_str'].isin(highlight_colors.keys())]\n", "df_color = spch[spch['date_str'].isin(highlight_colors.keys())]\n", "\n", "# Create figure\n", "fig = go.Figure()\n", "\n", "# Add gray (background) points\n", "fig.add_trace(go.Scatter(x=df_gray.index,y=df_gray['Q_mLs'],mode='markers',marker=dict(color='lightgray'),name='Other Dates'))\n", "\n", "# Add one trace per highlighted date with its fixed color\n", "for date_str, color in highlight_colors.items():\n", " sub_df = df_color[df_color['date_str'] == date_str]\n", " fig.add_trace(go.Scatter(x=sub_df.index,y=sub_df['Q_mLs'],mode='markers',marker=dict(color=color),name=f'Highlighted {date_str}'))\n", "\n", "fig.update_xaxes(range=['2022-12-25', '2023-02-08'],title=dict(text='Date', font=dict(size=20)),tickfont=dict(size=18),tickformat=\"%b %d %Y\")\n", "fig.update_yaxes(title=dict(text='Q (mL s⁻¹)', font=dict(size=20)), tickfont=dict(size=18) )\n", "\n", "# Optional layout tweaks\n", "fig.update_layout(template='none',showlegend=False)\n", "\n", "fig.show()\n", "#fig.write_image('autosampler_q_col.pdf',width=1450,height=280)" ] }, { "cell_type": "code", "execution_count": null, "id": "0d2d4724", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/var/folders/89/fb19llwd13zf7jxq9r7t2c3h0000gn/T/ipykernel_54439/3656844726.py:10: SettingWithCopyWarning:\n", "\n", "\n", "A value is trying to be set on a copy of a slice from a DataFrame.\n", "Try using .loc[row_indexer,col_indexer] = value instead\n", "\n", "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", "\n" ] }, { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plot.ly" }, "data": [ { "marker": { "color": "lightgray" }, "mode": "markers", "name": "Other Dates", "type": "scatter", "x": [ 261.558441665585, 248.389343031699, 231.927969739341, 215.553158077025, 190.811612944877, 188.128479633546, 188.38966192364, 188.699706935806, 188.835861970753, 188.971282046018, 188.958599577338, 188.896299964108, 188.799090562913, 188.646477698015, 188.426508552759, 188.258489070635, 187.967940924357, 187.679421114208, 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"display_data" } ], "source": [ "\n", "#C-Q 5 day time window plots \n", "\n", "# Dates to highlight and their custom colors (select one of these at a time)\n", "highlight_colors = {'2022-12-27': 'red','2022-12-28': 'orange','2022-12-29': 'green','2022-12-30': 'blue','2022-12-31': 'purple'} #chemostatic\n", "#highlight_colors = {'2023-01-07': 'red','2023-01-08': 'orange','2023-01-09': 'green','2023-01-10': 'blue','2023-01-11': 'purple'} #chemostatic\n", "#highlight_colors = {'2023-01-14': 'red','2023-01-15': 'orange','2023-01-16': 'green','2023-01-17': 'blue','2023-01-18': 'purple'} #connecting pools\n", "#highlight_colors = {'2023-02-01': 'red','2023-02-02': 'orange','2023-02-03': 'green','2023-02-04': 'blue','2023-02-05': 'purple'} #Flushing \n", "\n", "# Convert dates to string for matching\n", "spch['date_str'] = spch['date'].astype(str)\n", "\n", "# Split gray vs. colored points\n", "df_gray = spch[~spch['date_str'].isin(highlight_colors.keys())]\n", "df_color = spch[spch['date_str'].isin(highlight_colors.keys())]\n", "\n", "# Create figure\n", "fig = go.Figure()\n", "\n", "# Add gray (background) points\n", "fig.add_trace(go.Scatter(x=df_gray['Q_mLs'],y=df_gray['Cd_pred'], mode='markers',marker=dict(color='lightgray'),name='Other Dates'))\n", "\n", "# Add one trace per highlighted date with its fixed color\n", "for date_str, color in highlight_colors.items():\n", " sub_df = df_color[df_color['date_str'] == date_str]\n", " fig.add_trace(go.Scatter(x=sub_df['Q_mLs'],y=sub_df['Cd_pred'],mode='markers',marker=dict(color=color),name=f'Highlighted {date_str}'))\n", "\n", "# Axis formatting\n", "fig.update_xaxes(title=dict(text='Q (mL s⁻¹)', font=dict(size=20)), tickfont=dict(size=18), type=\"log\")\n", "fig.update_yaxes(title=dict(text='Cd (mg L⁻¹)', font=dict(size=24)),tickfont=dict(size=18),type=\"log\")\n", "\n", "# Layout\n", "fig.update_xaxes(range=[0.9,3])\n", "fig.update_layout(template='none',showlegend=False)\n", "fig.show()\n", "#fig.write_image('autosampler_qcd4.pdf',width=400,height=400)\n" ] }, { "cell_type": "markdown", "id": "f00e4330", "metadata": {}, "source": [ "## Hysteresis Analysis" ] }, { "cell_type": "code", "execution_count": 22, "id": "2d1dee8b", "metadata": {}, "outputs": [ { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plot.ly" }, "data": [ { "hovertemplate": "chemostatic
HI: 0.215
Duration: 24 days", "line": { "color": "#009e73", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-03-28T00:00:00", "2022-04-21T00:00:00" ], "y": [ "C4", "C4" ] }, { "hovertemplate": "chemostatic
HI: 0.045
Duration: 21 days", "line": { "color": "#009e73", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-04-21T00:00:00", "2022-05-12T00:00:00" ], "y": [ "C4", "C4" ] }, { "hovertemplate": "concentration
HI: 0.096
Duration: 26 days", "line": { "color": "#e69f00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-05-12T00:00:00", "2022-06-07T00:00:00" ], "y": [ "C4", "C4" ] }, { "hovertemplate": "recession
HI: 0.020
Duration: 21 days", "line": { "color": "#56b4e9", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-06-07T00:00:00", "2022-06-28T00:00:00" ], "y": [ "C4", "C4" ] }, { "hovertemplate": "static
HI: -0.004
Duration: 21 days", "line": { "color": "#999999", "dash": "1px 1px", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-06-28T00:00:00", "2022-07-19T00:00:00" ], "y": [ "C4", "C4" ] }, { "hovertemplate": "chemostatic
HI: 0.037
Duration: 24 days", "line": { "color": "#009e73", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-07-19T00:00:00", "2022-08-12T00:00:00" ], "y": [ "C4", "C4" ] }, { "hovertemplate": "chemostatic
HI: 0.013
Duration: 17 days", "line": { "color": "#009e73", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-08-12T00:00:00", "2022-08-29T00:00:00" ], "y": [ "C4", "C4" ] }, { "hovertemplate": "source_variation
HI: 0.015
Duration: 3 days", "line": { "color": "#cc79a7", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-08-29T00:00:00", "2022-09-01T00:00:00" ], "y": [ "C4", "C4" ] }, { "hovertemplate": "source_variation
HI: -0.009
Duration: 21 days", "line": { "color": "#cc79a7", "dash": "1px 1px", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-09-01T00:00:00", "2022-09-22T00:00:00" ], "y": [ "C4", "C4" ] }, { "hovertemplate": "chemostatic
HI: 0.030
Duration: 21 days", "line": { "color": "#009e73", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-09-22T00:00:00", "2022-10-13T00:00:00" ], "y": [ "C4", "C4" ] }, { "hovertemplate": "chemostatic
HI: 0.020
Duration: 20 days", "line": { "color": "#009e73", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-10-13T00:00:00", "2022-11-02T00:00:00" ], "y": [ "C4", "C4" ] }, { "hovertemplate": "chemostatic
HI: 0.029
Duration: 27 days", "line": { "color": "#009e73", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-11-02T00:00:00", "2022-11-29T00:00:00" ], "y": [ "C4", "C4" ] }, { "hovertemplate": "chemostatic
HI: -0.152
Duration: 57 days", "line": { "color": "#009e73", "dash": "2px 1px", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-11-29T00:00:00", "2023-01-25T00:00:00" ], "y": [ "C4", "C4" ] }, { "hovertemplate": "chemostatic
HI: -0.413
Duration: 15 days", "line": { "color": "#009e73", "dash": "2px 1px", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-01-25T00:00:00", "2023-02-09T00:00:00" ], "y": [ "C4", "C4" ] }, { "hovertemplate": "chemostatic
HI: -0.104
Duration: 12 days", "line": { "color": "#009e73", "dash": "2px 1px", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-02-09T00:00:00", "2023-02-21T00:00:00" ], "y": [ "C4", "C4" ] }, { "hovertemplate": "chemostatic
HI: -0.283
Duration: 28 days", "line": { "color": "#009e73", "dash": "2px 1px", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-02-21T00:00:00", "2023-03-21T00:00:00" ], "y": [ "C4", "C4" ] }, { "hovertemplate": "chemostatic
HI: 0.396
Duration: 23 days", "line": { "color": "#009e73", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-03-21T00:00:00", "2023-04-13T00:00:00" ], "y": [ "C4", "C4" ] }, { "hovertemplate": "chemostatic
HI: -0.085
Duration: 22 days", "line": { "color": "#009e73", "dash": "2px 1px", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-04-13T00:00:00", "2023-05-05T00:00:00" ], "y": [ "C4", "C4" ] }, { "hovertemplate": "chemostatic
HI: 0.203
Duration: 21 days", "line": { "color": "#009e73", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-05-05T00:00:00", "2023-05-26T00:00:00" ], "y": [ "C4", "C4" ] }, { "hovertemplate": "chemostatic
HI: 0.148
Duration: 24 days", "line": { "color": "#009e73", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-05-26T00:00:00", "2023-06-19T00:00:00" ], "y": [ "C4", "C4" ] }, { "hovertemplate": "chemostatic
HI: 0.073
Duration: 23 days", "line": { "color": "#009e73", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-06-19T00:00:00", "2023-07-12T00:00:00" ], "y": [ "C4", "C4" ] }, { "hovertemplate": "chemostatic
HI: 0.102
Duration: 22 days", "line": { "color": "#009e73", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-07-12T00:00:00", "2023-08-03T00:00:00" ], "y": [ "C4", "C4" ] }, { "hovertemplate": "chemostatic
HI: 0.071
Duration: 76 days", "line": { "color": "#009e73", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-08-03T00:00:00", "2023-10-18T00:00:00" ], "y": [ "C4", "C4" ] }, { "hovertemplate": "chemostatic
HI: 0.031
Duration: 22 days", "line": { "color": "#009e73", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-10-18T00:00:00", "2023-11-09T00:00:00" ], "y": [ "C4", "C4" ] }, { "hovertemplate": "concentration
HI: 0.034
Duration: 24 days", "line": { "color": "#e69f00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-03-28T00:00:00", "2022-04-21T00:00:00" ], "y": [ "A12", "A12" ] }, { "hovertemplate": "source_variation
HI: 0.023
Duration: 21 days", "line": { "color": "#cc79a7", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-04-21T00:00:00", "2022-05-12T00:00:00" ], "y": [ "A12", "A12" ] }, { "hovertemplate": "concentration
HI: 0.081
Duration: 26 days", "line": { "color": "#e69f00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-05-12T00:00:00", "2022-06-07T00:00:00" ], "y": [ "A12", "A12" ] }, { "hovertemplate": "concentration
HI: 0.076
Duration: 21 days", "line": { "color": "#e69f00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-06-07T00:00:00", "2022-06-28T00:00:00" ], "y": [ "A12", "A12" ] }, { "hovertemplate": "dilution
HI: -0.031
Duration: 2 days", "line": { "color": "#0072b2", "dash": "2px 1px", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-06-28T00:00:00", "2022-06-30T00:00:00" ], "y": [ "A12", "A12" ] }, { "hovertemplate": "recession
HI: -0.015
Duration: 19 days", "line": { "color": "#56b4e9", "dash": "2px 1px", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-06-30T00:00:00", "2022-07-19T00:00:00" ], "y": [ "A12", "A12" ] }, { "hovertemplate": "concentration
HI: 0.069
Duration: 24 days", "line": { "color": "#e69f00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-07-19T00:00:00", "2022-08-12T00:00:00" ], "y": [ "A12", "A12" ] }, { "hovertemplate": "source_variation
HI: 0.026
Duration: 17 days", "line": { "color": "#cc79a7", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-08-12T00:00:00", "2022-08-29T00:00:00" ], "y": [ "A12", "A12" ] }, { "hovertemplate": "static
HI: -0.004
Duration: 3 days", "line": { "color": "#999999", "dash": "1px 1px", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-08-29T00:00:00", "2022-09-01T00:00:00" ], "y": [ "A12", "A12" ] }, { "hovertemplate": "static
HI: -0.018
Duration: 21 days", "line": { "color": "#999999", "dash": "2px 1px", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-09-01T00:00:00", "2022-09-22T00:00:00" ], "y": [ "A12", "A12" ] }, { "hovertemplate": "concentration
HI: 0.198
Duration: 21 days", "line": { "color": "#e69f00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-09-22T00:00:00", "2022-10-13T00:00:00" ], "y": [ "A12", "A12" ] }, { "hovertemplate": "recession
HI: -0.091
Duration: 20 days", "line": { "color": "#56b4e9", "dash": "2px 1px", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-10-13T00:00:00", "2022-11-02T00:00:00" ], "y": [ "A12", "A12" ] }, { "hovertemplate": "source_variation
HI: 0.180
Duration: 27 days", "line": { "color": "#cc79a7", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-11-02T00:00:00", "2022-11-29T00:00:00" ], "y": [ "A12", "A12" ] }, { "hovertemplate": "source_variation
HI: -0.040
Duration: 21 days", "line": { "color": "#cc79a7", "dash": "2px 1px", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-11-29T00:00:00", "2022-12-20T00:00:00" ], "y": [ "A12", "A12" ] }, { "hovertemplate": "dilution
HI: -0.275
Duration: 36 days", "line": { "color": "#0072b2", "dash": "2px 1px", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-12-20T00:00:00", "2023-01-25T00:00:00" ], "y": [ "A12", "A12" ] }, { "hovertemplate": "dilution
HI: -0.771
Duration: 15 days", "line": { "color": "#0072b2", "dash": "2px 1px", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-01-25T00:00:00", "2023-02-09T00:00:00" ], "y": [ "A12", "A12" ] }, { "hovertemplate": "chemostatic
HI: 0.158
Duration: 12 days", "line": { "color": "#009e73", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-02-09T00:00:00", "2023-02-21T00:00:00" ], "y": [ "A12", "A12" ] }, { "hovertemplate": "dilution
HI: -0.210
Duration: 28 days", "line": { "color": "#0072b2", "dash": "2px 1px", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-02-21T00:00:00", "2023-03-21T00:00:00" ], "y": [ "A12", "A12" ] }, { "hovertemplate": "concentration
HI: 0.230
Duration: 23 days", "line": { "color": "#e69f00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-03-21T00:00:00", "2023-04-13T00:00:00" ], "y": [ "A12", "A12" ] }, { "hovertemplate": "chemostatic
HI: 0.079
Duration: 22 days", "line": { "color": "#009e73", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-04-13T00:00:00", "2023-05-05T00:00:00" ], "y": [ "A12", "A12" ] }, { "hovertemplate": "concentration
HI: 0.199
Duration: 21 days", "line": { "color": "#e69f00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-05-05T00:00:00", "2023-05-26T00:00:00" ], "y": [ "A12", "A12" ] }, { "hovertemplate": "concentration
HI: 0.148
Duration: 24 days", "line": { "color": "#e69f00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-05-26T00:00:00", "2023-06-19T00:00:00" ], "y": [ "A12", "A12" ] }, { "hovertemplate": "concentration
HI: 0.059
Duration: 23 days", "line": { "color": "#e69f00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-06-19T00:00:00", "2023-07-12T00:00:00" ], "y": [ "A12", "A12" ] }, { "hovertemplate": "concentration
HI: 0.079
Duration: 57 days", "line": { "color": "#e69f00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-07-12T00:00:00", "2023-09-07T00:00:00" ], "y": [ "A12", "A12" ] }, { "hovertemplate": "concentration
HI: 0.151
Duration: 41 days", "line": { "color": "#e69f00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-09-07T00:00:00", "2023-10-18T00:00:00" ], "y": [ "A12", "A12" ] }, { "hovertemplate": "chemostatic
HI: 0.023
Duration: 22 days", "line": { "color": "#009e73", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-10-18T00:00:00", "2023-11-09T00:00:00" ], "y": [ "A12", "A12" ] }, { "hovertemplate": "dilution
HI: -0.459
Duration: 33 days", "line": { "color": "#0072b2", "dash": "2px 1px", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-11-09T00:00:00", "2023-12-12T00:00:00" ], "y": [ "A12", "A12" ] }, { "hovertemplate": "static
HI: 0.009
Duration: 27 days", "line": { "color": "#999999", "dash": "1px 1px", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-02-02T00:00:00", "2022-03-01T00:00:00" ], "y": [ "B3", "B3" ] }, { "hovertemplate": "concentration
HI: 0.070
Duration: 13 days", "line": { "color": "#e69f00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-03-01T00:00:00", "2022-03-14T00:00:00" ], "y": [ "B3", "B3" ] }, { "hovertemplate": "concentration
HI: 0.093
Duration: 14 days", "line": { "color": "#e69f00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-03-14T00:00:00", "2022-03-28T00:00:00" ], "y": [ "B3", "B3" ] }, { "hovertemplate": "concentration
HI: 0.081
Duration: 24 days", "line": { "color": "#e69f00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-03-28T00:00:00", "2022-04-21T00:00:00" ], "y": [ "B3", "B3" ] }, { "hovertemplate": "source_variation
HI: 0.034
Duration: 21 days", "line": { "color": "#cc79a7", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-04-21T00:00:00", "2022-05-12T00:00:00" ], "y": [ "B3", "B3" ] }, { "hovertemplate": "concentration
HI: 0.139
Duration: 26 days", "line": { "color": "#e69f00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-05-12T00:00:00", "2022-06-07T00:00:00" ], "y": [ "B3", "B3" ] }, { "hovertemplate": "source_variation
HI: 0.033
Duration: 21 days", "line": { "color": "#cc79a7", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-06-07T00:00:00", "2022-06-28T00:00:00" ], "y": [ "B3", "B3" ] }, { "hovertemplate": "concentration
HI: 0.031
Duration: 2 days", "line": { "color": "#e69f00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-06-28T00:00:00", "2022-06-30T00:00:00" ], "y": [ "B3", "B3" ] }, { "hovertemplate": "dilution
HI: -0.036
Duration: 19 days", "line": { "color": "#0072b2", "dash": "2px 1px", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-06-30T00:00:00", "2022-07-19T00:00:00" ], "y": [ "B3", "B3" ] }, { "hovertemplate": "source_variation
HI: 0.027
Duration: 24 days", "line": { "color": "#cc79a7", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-07-19T00:00:00", "2022-08-12T00:00:00" ], "y": [ "B3", "B3" ] }, { "hovertemplate": "concentration
HI: 0.035
Duration: 17 days", "line": { "color": "#e69f00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-08-12T00:00:00", "2022-08-29T00:00:00" ], "y": [ "B3", "B3" ] }, { "hovertemplate": "chemostatic
HI: 0.014
Duration: 3 days", "line": { "color": "#009e73", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-08-29T00:00:00", "2022-09-01T00:00:00" ], "y": [ "B3", "B3" ] }, { "hovertemplate": "chemostatic
HI: -0.020
Duration: 21 days", "line": { "color": "#009e73", "dash": "2px 1px", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-09-01T00:00:00", "2022-09-22T00:00:00" ], "y": [ "B3", "B3" ] }, { "hovertemplate": "concentration
HI: 0.041
Duration: 21 days", "line": { "color": "#e69f00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-09-22T00:00:00", "2022-10-13T00:00:00" ], "y": [ "B3", "B3" ] }, { "hovertemplate": "source_variation
HI: 0.029
Duration: 20 days", "line": { "color": "#cc79a7", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-10-13T00:00:00", "2022-11-02T00:00:00" ], "y": [ "B3", "B3" ] }, { "hovertemplate": "concentration
HI: 0.067
Duration: 27 days", "line": { "color": "#e69f00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-11-02T00:00:00", "2022-11-29T00:00:00" ], "y": [ "B3", "B3" ] }, { "hovertemplate": "flushing
HI: 0.095
Duration: 21 days", "line": { "color": "#d55e00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-11-29T00:00:00", "2022-12-20T00:00:00" ], "y": [ "B3", "B3" ] }, { "hovertemplate": "dilution
HI: -0.329
Duration: 36 days", "line": { "color": "#0072b2", "dash": "2px 1px", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-12-20T00:00:00", "2023-01-25T00:00:00" ], "y": [ "B3", "B3" ] }, { "hovertemplate": "dilution
HI: -0.378
Duration: 15 days", "line": { "color": "#0072b2", "dash": "2px 1px", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-01-25T00:00:00", "2023-02-09T00:00:00" ], "y": [ "B3", "B3" ] }, { "hovertemplate": "chemostatic
HI: -0.133
Duration: 12 days", "line": { "color": "#009e73", "dash": "2px 1px", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-02-09T00:00:00", "2023-02-21T00:00:00" ], "y": [ "B3", "B3" ] }, { "hovertemplate": "dilution
HI: -0.268
Duration: 28 days", "line": { "color": "#0072b2", "dash": "2px 1px", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-02-21T00:00:00", "2023-03-21T00:00:00" ], "y": [ "B3", "B3" ] }, { "hovertemplate": "concentration
HI: 0.305
Duration: 23 days", "line": { "color": "#e69f00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-03-21T00:00:00", "2023-04-13T00:00:00" ], "y": [ "B3", "B3" ] }, { "hovertemplate": "chemostatic
HI: 0.034
Duration: 22 days", "line": { "color": "#009e73", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-04-13T00:00:00", "2023-05-05T00:00:00" ], "y": [ "B3", "B3" ] }, { "hovertemplate": "concentration
HI: 0.163
Duration: 21 days", "line": { "color": "#e69f00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-05-05T00:00:00", "2023-05-26T00:00:00" ], "y": [ "B3", "B3" ] }, { "hovertemplate": "concentration
HI: 0.105
Duration: 24 days", "line": { "color": "#e69f00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-05-26T00:00:00", "2023-06-19T00:00:00" ], "y": [ "B3", "B3" ] }, { "hovertemplate": "concentration
HI: 0.077
Duration: 23 days", "line": { "color": "#e69f00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-06-19T00:00:00", "2023-07-12T00:00:00" ], "y": [ "B3", "B3" ] }, { "hovertemplate": "concentration
HI: 0.305
Duration: 120 days", "line": { "color": "#e69f00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-07-12T00:00:00", "2023-11-09T00:00:00" ], "y": [ "B3", "B3" ] }, { "hovertemplate": "dilution
HI: -0.419
Duration: 33 days", "line": { "color": "#0072b2", "dash": "2px 1px", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-11-09T00:00:00", "2023-12-12T00:00:00" ], "y": [ "B3", "B3" ] }, { "hovertemplate": "dilution
HI: -0.273
Duration: 35 days", "line": { "color": "#0072b2", "dash": "2px 1px", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-12-12T00:00:00", "2024-01-16T00:00:00" ], "y": [ "B3", "B3" ] }, { "hovertemplate": "dilution
HI: -0.324
Duration: 27 days", "line": { "color": "#0072b2", "dash": "2px 1px", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2024-01-16T00:00:00", "2024-02-12T00:00:00" ], "y": [ "B3", "B3" ] }, { "hovertemplate": "concentration
HI: 0.396
Duration: 23 days", "line": { "color": "#e69f00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2024-02-12T00:00:00", "2024-03-06T00:00:00" ], "y": [ "B3", "B3" ] }, { "hovertemplate": "concentration
HI: 0.348
Duration: 68 days", "line": { "color": "#e69f00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2024-03-06T00:00:00", "2024-05-13T00:00:00" ], "y": [ "B3", "B3" ] }, { "hovertemplate": "chemostatic
HI: -0.019
Duration: 27 days", "line": { "color": "#009e73", "dash": "2px 1px", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-02-02T00:00:00", "2022-03-01T00:00:00" ], "y": [ "B4", "B4" ] }, { "hovertemplate": "concentration
HI: 0.272
Duration: 27 days", "line": { "color": "#e69f00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-03-01T00:00:00", "2022-03-28T00:00:00" ], "y": [ "B4", "B4" ] }, { "hovertemplate": "concentration
HI: 0.196
Duration: 24 days", "line": { "color": "#e69f00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-03-28T00:00:00", "2022-04-21T00:00:00" ], "y": [ "B4", "B4" ] }, { "hovertemplate": "concentration
HI: 0.080
Duration: 21 days", "line": { "color": "#e69f00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-04-21T00:00:00", "2022-05-12T00:00:00" ], "y": [ "B4", "B4" ] }, { "hovertemplate": "dilution
HI: -0.080
Duration: 26 days", "line": { "color": "#0072b2", "dash": "2px 1px", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-05-12T00:00:00", "2022-06-07T00:00:00" ], "y": [ "B4", "B4" ] }, { "hovertemplate": "concentration
HI: 0.024
Duration: 21 days", "line": { "color": "#e69f00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-06-07T00:00:00", "2022-06-28T00:00:00" ], "y": [ "B4", "B4" ] }, { "hovertemplate": "concentration
HI: 0.070
Duration: 2 days", "line": { "color": "#e69f00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-06-28T00:00:00", "2022-06-30T00:00:00" ], "y": [ "B4", "B4" ] }, { "hovertemplate": "concentration
HI: 0.040
Duration: 19 days", "line": { "color": "#e69f00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-06-30T00:00:00", "2022-07-19T00:00:00" ], "y": [ "B4", "B4" ] }, { "hovertemplate": "recession
HI: 0.007
Duration: 24 days", "line": { "color": "#56b4e9", "dash": "1px 1px", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-07-19T00:00:00", "2022-08-12T00:00:00" ], "y": [ "B4", "B4" ] }, { "hovertemplate": "recession
HI: -0.005
Duration: 17 days", "line": { "color": "#56b4e9", "dash": "1px 1px", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-08-12T00:00:00", "2022-08-29T00:00:00" ], "y": [ "B4", "B4" ] }, { "hovertemplate": "chemostatic
HI: 0.022
Duration: 24 days", "line": { "color": "#009e73", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-08-29T00:00:00", "2022-09-22T00:00:00" ], "y": [ "B4", "B4" ] }, { "hovertemplate": "chemostatic
HI: 0.025
Duration: 21 days", "line": { "color": "#009e73", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-09-22T00:00:00", "2022-10-13T00:00:00" ], "y": [ "B4", "B4" ] }, { "hovertemplate": "source_variation
HI: 0.085
Duration: 20 days", "line": { "color": "#cc79a7", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-10-13T00:00:00", "2022-11-02T00:00:00" ], "y": [ "B4", "B4" ] }, { "hovertemplate": "concentration
HI: 0.149
Duration: 27 days", "line": { "color": "#e69f00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-11-02T00:00:00", "2022-11-29T00:00:00" ], "y": [ "B4", "B4" ] }, { "hovertemplate": "concentration
HI: 0.146
Duration: 21 days", "line": { "color": "#e69f00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-11-29T00:00:00", "2022-12-20T00:00:00" ], "y": [ "B4", "B4" ] }, { "hovertemplate": "flushing
HI: 0.217
Duration: 36 days", "line": { "color": "#d55e00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2022-12-20T00:00:00", "2023-01-25T00:00:00" ], "y": [ "B4", "B4" ] }, { "hovertemplate": "dilution
HI: -0.979
Duration: 15 days", "line": { "color": "#0072b2", "dash": "2px 1px", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-01-25T00:00:00", "2023-02-09T00:00:00" ], "y": [ "B4", "B4" ] }, { "hovertemplate": "chemostatic
HI: 0.097
Duration: 12 days", "line": { "color": "#009e73", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-02-09T00:00:00", "2023-02-21T00:00:00" ], "y": [ "B4", "B4" ] }, { "hovertemplate": "dilution
HI: -0.208
Duration: 28 days", "line": { "color": "#0072b2", "dash": "2px 1px", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-02-21T00:00:00", "2023-03-21T00:00:00" ], "y": [ "B4", "B4" ] }, { "hovertemplate": "concentration
HI: 0.203
Duration: 23 days", "line": { "color": "#e69f00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-03-21T00:00:00", "2023-04-13T00:00:00" ], "y": [ "B4", "B4" ] }, { "hovertemplate": "static
HI: -0.004
Duration: 22 days", "line": { "color": "#999999", "dash": "1px 1px", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-04-13T00:00:00", "2023-05-05T00:00:00" ], "y": [ "B4", "B4" ] }, { "hovertemplate": "concentration
HI: 0.230
Duration: 21 days", "line": { "color": "#e69f00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-05-05T00:00:00", "2023-05-26T00:00:00" ], "y": [ "B4", "B4" ] }, { "hovertemplate": "concentration
HI: 0.164
Duration: 24 days", "line": { "color": "#e69f00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-05-26T00:00:00", "2023-06-19T00:00:00" ], "y": [ "B4", "B4" ] }, { "hovertemplate": "concentration
HI: 0.034
Duration: 23 days", "line": { "color": "#e69f00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-06-19T00:00:00", "2023-07-12T00:00:00" ], "y": [ "B4", "B4" ] }, { "hovertemplate": "recession
HI: -0.012
Duration: 22 days", "line": { "color": "#56b4e9", "dash": "2px 1px", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-07-12T00:00:00", "2023-08-03T00:00:00" ], "y": [ "B4", "B4" ] }, { "hovertemplate": "flushing
HI: 0.027
Duration: 35 days", "line": { "color": "#d55e00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-08-03T00:00:00", "2023-09-07T00:00:00" ], "y": [ "B4", "B4" ] }, { "hovertemplate": "concentration
HI: 0.202
Duration: 41 days", "line": { "color": "#e69f00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-09-07T00:00:00", "2023-10-18T00:00:00" ], "y": [ "B4", "B4" ] }, { "hovertemplate": "concentration
HI: 0.189
Duration: 22 days", "line": { "color": "#e69f00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-10-18T00:00:00", "2023-11-09T00:00:00" ], "y": [ "B4", "B4" ] }, { "hovertemplate": "flushing
HI: 0.164
Duration: 33 days", "line": { "color": "#d55e00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-11-09T00:00:00", "2023-12-12T00:00:00" ], "y": [ "B4", "B4" ] }, { "hovertemplate": "dilution
HI: -0.852
Duration: 35 days", "line": { "color": "#0072b2", "dash": "2px 1px", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2023-12-12T00:00:00", "2024-01-16T00:00:00" ], "y": [ "B4", "B4" ] }, { "hovertemplate": "dilution
HI: -0.211
Duration: 27 days", "line": { "color": "#0072b2", "dash": "2px 1px", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2024-01-16T00:00:00", "2024-02-12T00:00:00" ], "y": [ "B4", "B4" ] }, { "hovertemplate": "concentration
HI: 0.271
Duration: 23 days", "line": { "color": "#e69f00", "dash": "solid", "width": 20 }, "mode": "lines", "showlegend": false, "type": "scatter", "x": [ "2024-02-12T00:00:00", "2024-03-06T00:00:00" ], "y": [ "B4", "B4" ] }, { "line": { "color": "#d55e00", "width": 10 }, "mode": "lines", "name": "Flushing", "type": "scatter", "x": [ null ], "y": [ null ] }, { "line": { "color": "#0072b2", "width": 10 }, "mode": "lines", "name": "Dilution", "type": "scatter", "x": [ null ], "y": [ null ] }, { "line": { "color": "#e69f00", "width": 10 }, "mode": "lines", "name": "Concentration", "type": "scatter", "x": [ null ], "y": [ null ] }, { "line": { "color": "#56b4e9", "width": 10 }, "mode": "lines", "name": "Recession", "type": "scatter", "x": [ null ], "y": [ null ] }, { "line": { "color": "#009e73", "width": 10 }, "mode": "lines", "name": "Chemostatic", "type": "scatter", "x": [ null ], "y": [ null ] }, { "line": { "color": "#cc79a7", "width": 10 }, "mode": "lines", "name": "Source_Variation", "type": "scatter", "x": [ null ], "y": [ null ] }, { "line": { "color": "#999999", "width": 10 }, "mode": "lines", "name": "Static", "type": "scatter", "x": [ null ], "y": [ null ] } ], "layout": { "height": 340, "legend": { "orientation": "h", "y": 1.1 }, "showlegend": true, "template": { "data": { "scatter": [ { "type": "scatter" } ] } }, "title": { "text": "PLI Hysteresis Behavior Timeline" }, "xaxis": { "range": [ "2022-02-02T09:00:00", "2024-03-06T09:00:00" ], "title": { "text": "Date" } }, "yaxis": { "categoryarray": [ "B4", "B3", "A12", "C4" ], "categoryorder": "array", "title": { "text": "Site" } } } } }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#hys.create_hysteresis_summary_stats(pcd, sites=['A12'], ccol='Cd_mgL', qcol='Q_mLs')\n", "figts = hys.create_hysteresis_timeline(pcd, sites=['C4','A12', 'B3','B4'], ccol='PLI', compound='PLI', qcol='Q_mLs') \n", "figts.update_xaxes(range=[Qx.index[0],Qx.index[-1]])\n", "figts.show()\n", "#figts.write_image('timeline_hysteresis.pdf',width=1200,height=260)" ] }, { "cell_type": "code", "execution_count": 23, "id": "02f9d797", "metadata": {}, "outputs": [], "source": [ "# get hysteresis analysis table\n", "analysis_df = hys.analyze_hysteresis(pcd, sites=['C4', 'A12', 'B4', 'B3'], ccol='Zn_mgL', qcol='Q_mLs')\n", "analysis_df = pd.concat([analysis_df, hys.analyze_hysteresis(pcd, sites=['C4', 'A12', 'B4', 'B3'], ccol='Cd_mgL', qcol='Q_mLs')])\n", "analysis_df = pd.concat([analysis_df, hys.analyze_hysteresis(pcd, sites=['C4', 'A12', 'B4', 'B3'], ccol='Fe_mgL', qcol='Q_mLs')])\n", "analysis_df = pd.concat([analysis_df, hys.analyze_hysteresis(pcd, sites=['C4', 'A12', 'B4', 'B3'], ccol='PLI', qcol='Q_mLs')])\n", "#analysis_df.to_csv('hysteresis_analysis.csv')\n" ] }, { "cell_type": "code", "execution_count": 24, "id": "89869720", "metadata": {}, "outputs": [ { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plot.ly" }, "data": [ { "hovertemplate": "Cd - declining
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"anchor": "x8", "domain": [ 0.5746249999999999, 0.7424999999999999 ], "range": [ 0, 2.7781512503836434 ], "title": { "text": "" }, "type": "log" }, "yaxis9": { "anchor": "x9", "domain": [ 0.5746249999999999, 0.7424999999999999 ], "range": [ 0, 2.7781512503836434 ], "title": { "text": "" }, "type": "log" } } } }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig = hys.create_multi_compound_hysteresis_plot(\n", " pcd, sites=['A12', 'B4', 'B3'],\n", " ccols=['Cd_mgL', 'Zn_mgL','Fe_mgL','PLI'],\n", " compounds=['Cd', 'Zn','Fe','PLI'],\n", " conc_units=['mg L⁻¹', 'mg L⁻¹','mg L⁻¹',''],\n", " qcol='Q_mLs', flow_unit='mL s⁻¹',\n", " cxmin=[0.02, 1.,0.01,0.1], cxmax=[4., 600.0, 30., 1600.],\n", " qxmin=4.,\n", " hi_method='lloyd' # Use Lloyd's HI for styling - or zuecco\n", ")\n", "fig.update_layout(template='none')\n", "fig.show()\n", "#fig.write_image('hysteresis_plot_lloyd.pdf', width=1200, height=1400)" ] }, { "cell_type": "code", "execution_count": null, "id": "0d475108", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "modelling_project", "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": "3.12.8" } }, "nbformat": 4, "nbformat_minor": 5 }