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@pingud98
Created September 21, 2021 21:54
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Cosmic Rays and Earthquakes?
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{
"cells": [
{
"cell_type": "markdown",
"id": "1a1ebc14",
"metadata": {},
"source": [
"#Cosmic Ray and Earthquake analysis\n",
"Last updated 21/9/21 J. Devine\n",
"\n",
"##This is what I was planning to do - I didn't get very far.\n",
"\n",
"Stage 1: Collect the data\n",
"datasets - nmdb data (all stations, corrected rates) (done!)\n",
"USGS Earthquake db (done!)\n",
"Sunspot data - cross ref with cosmics and earthquakes.\n",
"Weather data - nearest neighbour for each NMDB location (not done - would be nice in the future)\n",
"\n",
"\n",
"Stage 2: Back-calc the pressure correction - not done!\n",
" a - cross ref. air pressure with nearest neighbour\n",
" b - compare raw and corrected counts\n",
" c - compare delta with pressure data sets\n",
" d - compute correction constant\n",
" e - compute pressure /cosmic rate correlation\n",
"\n",
"Then repeat for sunspot data. sunspot correlation with cosmics (expected -ve and strong)\n",
"\n",
"Stage 3: Earthquake data\n",
"structure 10 year data (2010-2020), inc. 6 hourly averages of seismic energy. \n",
"plot all earthquake locations (lat/long) to see fault lines\n",
"Find the nearest nmdb sensor for each (actually find nearest earthquakes for each nmdb..).\n",
"Compute for each earthquake the distances to NMDB sites (triangulation)\n",
"\n",
"\n",
"Stage 4:\n",
"Windows. \n",
"Window variables - averages from 1m to 4 weeks (compute for cosmic and seismic from raw)\n",
"Window variable - W\n",
"Offset variable - look at all offsets from 1m to 365 days (+ and -)\n",
"In each case perform a regression across the dataset and select for highest correlations.\n",
"\n",
"\n",
"Stage 5: Random variable\n",
"Pick a random variable from the weather data and do a null analysis.\n",
"\n",
"##What I actually did (so far)\n",
"Import data from NMDB monitors, for basically all the sites, all date ranges and build arrays (pandas), and rescale per period.\n",
"Import data from USGS and compute average seismic activity per period\n",
"Import sunspot data and compute average sunsport data per period\n",
"\n",
"Correlation between USGS and sunspot data, with p values, across a range of offsets up to +/-10k days- interesting patterns!\n",
"\n",
"##What is left to do to make this useful\n",
"Wrangle the NMDB data properly to do a similar variable offset calc with USGS data. \n",
"If the correlations and p values are reasonable at specific offsets then - \n",
"Compare this analysis with c(P,t0,d,m,𝚫t) = A*B = (Sm(ti+𝚫t)/M(Sm(ti+𝚫t))-1))*(|𝚫ncr(ti,i-1)|/M(|𝚫ncr(ti,i-1)|)-1) \n",
"Build a PDF for agreement etc.\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "0beec68a",
"metadata": {},
"outputs": [],
"source": [
"import argparse, csv, urllib.request, time\n",
"import pandas as pd\n",
"import numpy as np\n",
"from pathlib import Path\n",
"from datetime import datetime\n",
"from pandas.tseries.offsets import DateOffset\n",
"import matplotlib.pyplot as plot"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "587e52ff",
"metadata": {},
"outputs": [],
"source": [
"from scipy.stats import kendalltau, pearsonr, spearmanr\n",
"\n",
"def kendall_pval(x,y):\n",
" return kendalltau(x,y)[1]\n",
" \n",
"def pearsonr_pval(x,y):\n",
" return pearsonr(x,y)[1]\n",
" \n",
"def spearmanr_pval(x,y):\n",
" return spearmanr(x,y)[1]"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "a487bffb",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"3.9.5\n"
]
}
],
"source": [
"from platform import python_version\n",
"print(python_version())"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "666c0823",
"metadata": {},
"outputs": [],
"source": [
"def log_avg(spl_arraylike):\n",
" return 10*np.log10(np.mean(np.power(10, spl_arraylike/10)))"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "0e58cadf",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Start with the interval 1D\n"
]
}
],
"source": [
"average_interval = \"1D\"\n",
"print (\"Start with the interval \", average_interval)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "3c6f0960",
"metadata": {},
"outputs": [],
"source": [
"station_names = [\n",
" \"AATA\",\"AATB\",\"APTY\",\"ARNM\",\"ATHN\",\"BKSN\",\n",
" \"CALM\",\"DJON\",\"DOMB\",\"DOMC\",\"DRBS\",\"FSMT\",\n",
" \"HRMS\",\"INVK\",\"IRK2\",\"IRK3\",\"IRKT\",\"JBGO\",\n",
" \"JUNG\",\"JUNG1\",\"KERG\",\"KIEL\",\"KIEL2\",\"LMKS\",\n",
" \"MCRL\",\"MGDN\",\"MOSC\",\"MRNY\",\"MXCO\",\"NAIN\",\n",
" \"NANM\",\"NEWK\",\"NRLK\",\"OULU\",\"PSNM\",\"PTFM\",\n",
" \"PWNK\",\"ROME\",\"SNAE\",\"SOPB\",\"SOPO\",\"TERA\",\n",
" \"THUL\",\"TSMB\"\n",
"]"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "d2cf6c10",
"metadata": {},
"outputs": [],
"source": [
"start_date = [ \"1\", \"1\", \"1960\", \"0\", \"0\"]\n",
"end_date = [\"31\", \"12\", \"2019\", \"23\", \"59\"]"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "fd0c14a5",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"AATAfully completed\n",
"AATBfully completed\n",
"APTYfully completed\n",
"ARNMfully completed\n",
"ATHNfully completed\n",
"BKSNfully completed\n",
"CALMfully completed\n",
"DJONfully completed\n",
"DOMBfully completed\n",
"DOMCfully completed\n",
"DRBSfully completed\n",
"FSMTfully completed\n",
"HRMSfully completed\n",
"INVKfully completed\n",
"http://nest.nmdb.eu/draw_graph.php?wget=1&stations[]=IRK2&tabchoice=1h&dtype=corr_for_pressure&output=ascii&date_choice=bydate&last_label=days_label&tresolution=60&force=0&start_day=1&start_month=1&start_year=2015&start_hour=0&start_min=0&end_day=31&end_month=12&end_year=2015&end_hour=23&end_min=59&yunits=0\n",
"An exception occurred with IRK22015.csv\n",
"IRK2fully completed\n",
"http://nest.nmdb.eu/draw_graph.php?wget=1&stations[]=IRK3&tabchoice=1h&dtype=corr_for_pressure&output=ascii&date_choice=bydate&last_label=days_label&tresolution=60&force=0&start_day=1&start_month=1&start_year=2015&start_hour=0&start_min=0&end_day=31&end_month=12&end_year=2015&end_hour=23&end_min=59&yunits=0\n",
"An exception occurred with IRK32015.csv\n",
"IRK3fully completed\n",
"IRKTfully completed\n",
"JBGOfully completed\n",
"JUNGfully completed\n",
"JUNG1fully completed\n",
"KERGfully completed\n",
"KIELfully completed\n",
"KIEL2fully completed\n",
"LMKSfully completed\n",
"MCRLfully completed\n",
"MGDNfully completed\n",
"MOSCfully completed\n",
"MRNYfully completed\n",
"MXCOfully completed\n",
"NAINfully completed\n",
"NANMfully completed\n",
"NEWKfully completed\n",
"http://nest.nmdb.eu/draw_graph.php?wget=1&stations[]=NRLK&tabchoice=1h&dtype=corr_for_pressure&output=ascii&date_choice=bydate&last_label=days_label&tresolution=60&force=0&start_day=1&start_month=1&start_year=2015&start_hour=0&start_min=0&end_day=31&end_month=12&end_year=2015&end_hour=23&end_min=59&yunits=0\n",
"An exception occurred with NRLK2015.csv\n",
"NRLKfully completed\n",
"OULUfully completed\n",
"PSNMfully completed\n",
"PTFMfully completed\n",
"PWNKfully completed\n",
"ROMEfully completed\n",
"SNAEfully completed\n",
"SOPBfully completed\n",
"SOPOfully completed\n",
"TERAfully completed\n",
"THULfully completed\n",
"TSMBfully completed\n",
"finished\n"
]
}
],
"source": [
"# load all the stations\n",
"for current_station in station_names:\n",
" for i in range(int(start_date[2]), int(end_date[2])+1):\n",
" station_file = Path(current_station+str(i)+'.csv')\n",
" if not station_file.exists():\n",
" URL = \"http://nest.nmdb.eu/draw_graph.php?wget=1&stations[]=\"+current_station+\"&tabchoice=1h&dtype=corr_for_pressure&output=ascii&date_choice=bydate&last_label=days_label&tresolution=60&force=0&start_day=\"+start_date[0]+\"&start_month=\"+start_date[1]+\"&start_year=\"+str(i)+\"&start_hour=\"+start_date[3]+\"&start_min=\"+start_date[4]+\"&end_day=\"+end_date[0]+\"&end_month=\"+end_date[1]+\"&end_year=\"+str(i)+\"&end_hour=\"+end_date[3]+\"&end_min=\"+end_date[4]+\"&yunits=0\"\n",
" print(URL)\n",
" try:\n",
" req = urllib.request.Request(URL)\n",
" #req.add_header('User-Agent', 'urllib/0.1')\n",
" with urllib.request.urlopen(req) as f:\n",
" content = f.readlines()\n",
" fromhere = False\n",
" content_p = \"\"\n",
" for line in content:\n",
" if \"start_date_time\" in line.decode(\"utf-8\", \"strict\"):\n",
" fromhere = True\n",
" if fromhere:\n",
" content_p = content_p+ line.decode()\n",
" with station_file.open('wt') as fh:\n",
" fh.write(content_p)\n",
" fh.close\n",
" time.sleep(1)\n",
" #print(current_station+'completed ' + str(i))\n",
" except:\n",
" print(\"An exception occurred with \"+str(station_file))\n",
" #time.sleep(6)\n",
" print(current_station+'fully completed')\n",
"print(\"finished\")\n"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "2db1f566",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"An exception occurred, IRK22015.csv\n",
"An exception occurred, IRK32015.csv\n",
"An exception occurred, NRLK2015.csv\n",
"finished\n"
]
}
],
"source": [
"# Populate data structures\n",
"start_date = [ \"1\", \"1\", \"1960\", \"0\", \"0\"]\n",
"end_date = [\"31\", \"12\", \"2019\", \"23\", \"59\"]\n",
"combineddata = []\n",
"for current_station in station_names:\n",
" listofcosmics = []\n",
" for i in range(int(start_date[2]), int(end_date[2])+1):\n",
" station_file = Path(current_station+str(i)+'.csv')\n",
" try:\n",
" readframe = (pd.read_csv(station_file,sep=';',skiprows=1,names = ['start_date_time', current_station],parse_dates=['start_date_time'], index_col=['start_date_time']))\n",
" #print(\"Opened \"+str(station_file))\n",
" except:\n",
" print(\"An exception occurred, \"+str(station_file))\n",
" listofcosmics.append(readframe)\n",
" listofcosmics[0] = pd.merge(listofcosmics[0],listofcosmics[1], how='outer', left_index=True, right_index=True)\n",
" listofcosmics[0] = listofcosmics[0].fillna(0)\n",
" listofcosmics[0][current_station] = listofcosmics[0][str(current_station+\"_x\")] + listofcosmics[0][str(current_station+\"_y\")]\n",
" listofcosmics[0] = listofcosmics[0].drop(columns=[str(current_station+'_x'), str(current_station+'_y')])\n",
" howmanyitems = len(listofcosmics)\n",
" for i in range(2, howmanyitems):\n",
" listofcosmics[0] = pd.merge(listofcosmics[0],listofcosmics[i], how='outer', left_index=True, right_index=True)\n",
" listofcosmics[0] = listofcosmics[0].fillna(0)\n",
" listofcosmics[0][current_station] = listofcosmics[0][str(current_station+\"_x\")] + listofcosmics[0][str(current_station+\"_y\")]\n",
" listofcosmics[0] = listofcosmics[0].drop(columns=[str(current_station+\"_x\"), str(current_station+\"_y\")])\n",
" combineddata.append(listofcosmics[0])\n",
"print(\"finished\")"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "dab6b38c",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['AATA', 'AATB', 'APTY', 'ARNM', 'ATHN', 'BKSN', 'CALM', 'DJON', 'DOMB', 'DOMC', 'DRBS', 'FSMT', 'HRMS', 'INVK', 'IRK2', 'IRK3', 'IRKT', 'JBGO', 'JUNG', 'JUNG1', 'KERG', 'KIEL', 'KIEL2', 'LMKS', 'MCRL', 'MGDN', 'MOSC', 'MRNY', 'MXCO', 'NAIN', 'NANM', 'NEWK', 'NRLK', 'OULU', 'PSNM', 'PTFM', 'PWNK', 'ROME', 'SNAE', 'SOPB', 'SOPO', 'TERA', 'THUL', 'TSMB']\n",
" AATA\n",
"start_date_time \n",
"2019-01-04 06:59:00 3775.33\n",
"2019-01-04 07:59:00 3781.68\n",
"2019-01-04 08:59:00 3773.55\n",
"2019-01-04 09:59:00 3831.31\n",
"2019-01-04 10:59:00 3784.70\n",
"... ...\n",
"2019-12-31 19:59:00 3756.13\n",
"2019-12-31 20:59:00 3774.63\n",
"2019-12-31 21:59:00 3747.15\n",
"2019-12-31 22:59:00 3781.48\n",
"2019-12-31 23:59:00 3761.70\n",
"\n",
"[8105 rows x 1 columns]\n"
]
}
],
"source": [
"#check that thte sequences match\n",
"print(station_names)\n",
"print(combineddata[0])"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "e0a38083",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" TSMB\n",
"start_date_time \n",
"1976-12-04 00:00:00 330.556\n",
"1976-12-04 01:00:00 330.972\n",
"1976-12-04 02:00:00 330.694\n",
"1976-12-04 03:00:00 331.139\n",
"1976-12-04 04:00:00 330.500\n",
"... ...\n",
"2019-11-01 19:00:00 332.000\n",
"2019-11-01 20:00:00 332.139\n",
"2019-11-01 21:00:00 331.583\n",
"2019-11-01 22:00:00 331.639\n",
"2019-11-01 23:00:00 332.000\n",
"\n",
"[335841 rows x 1 columns]\n"
]
}
],
"source": [
"# random sample test of one\n",
"print(combineddata[43])"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "746c7442",
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# plot several stations to check it makes sense\n",
"for station in range (0, 3):\n",
" \n",
" combineddata[station].plot()"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "9e20af18",
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" latitude longitude depth mag\n",
"time \n",
"1960-01-02 12:21:58+00:00 -55.877 -1.89 15 6.3\n",
"1960-01-02 22:51:46.080000+00:00 35.5563333 -121.351 6 4.04\n",
"1960-01-03 11:24:05+00:00 43.7 84.542 15 5.7\n",
"1960-01-04 06:16:35+00:00 11.374 42.609 15 6.1\n",
"1960-01-04 12:52:00+00:00 45.069 26.829 40 5.4\n",
"... ... ... ... ...\n",
"2019-12-31 19:02:55.645000+00:00 44.0786 150.2151 10 4.8\n",
"2019-12-31 19:10:10.306000+00:00 24.074 121.6908 12.21 4.6\n",
"2019-12-31 23:07:42.730000+00:00 17.9226 -66.8408 5 4.2\n",
"2019-12-31 23:09:44.616000+00:00 9.9422 -84.4593 59.75 4\n",
"2019-12-31 23:56:59.933000+00:00 -20.5382 168.9571 21.46 4.3\n",
"\n",
"[427535 rows x 4 columns]\n"
]
}
],
"source": [
"# seismic data read in\n",
"sfs = []\n",
"start_year = 1960\n",
"end_year = 2019\n",
"types_dict = {'time':float, 'latitude':\"string\", 'longitude':\"string\", 'depth':\"string\", 'mag':\"string\"}\n",
"for i in range(start_year, end_year+1):\n",
" sfs.append(pd.read_csv('siesmic-'+str(i)+'.csv',sep=',',skiprows=1,names = ['time', 'latitude', 'longitude', 'depth', 'mag'],parse_dates=['time'],index_col=['time'],usecols = [i for i in range(5)],dtype=types_dict))\n",
"sframe= pd.concat(sfs)\n",
"print(sframe)"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "5fead4ec",
"metadata": {
"scrolled": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Index(['latitude', 'longitude', 'depth', 'mag'], dtype='object')\n"
]
}
],
"source": [
"# manipulation with seismic data\n",
"cols = sframe.columns\n",
"print(cols)\n",
"#cols.remove('time')\n",
"sframe['latitude'] = pd.to_numeric(sframe['latitude'], errors='coerce')\n",
"sframe['longitude'] = pd.to_numeric(sframe['longitude'], errors='coerce')\n",
"sframe['depth'] = pd.to_numeric(sframe['depth'], errors='coerce')\n",
"sframe['mag'] = pd.to_numeric(sframe['mag'], errors='coerce')\n",
"#print(sframe.dtypes)\n",
"#sframe=pd.convert_objects(convert_numeric=True)\n",
"#for col in cols:\n",
"# sframe[col] = sframe[col].astype(float)\n",
"#sframe.index.tz_convert(None)\n",
"#sframe.tz_localize(None)\n",
"sframe_notz = sframe.tz_convert(None)\n",
"daily_quakes = sframe_notz.resample(average_interval, origin='1960-01-01').apply(lambda spl: 10*np.log10(np.mean(np.power(10, spl/10))))\n",
"daily_quakes = daily_quakes.fillna(0)"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "2bdfb7a2",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<AxesSubplot:xlabel='time'>"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# plot the quake data\n",
"sframe['mag'].plot()\n",
"daily_quakes['mag'].plot()\n"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "3cc505e8",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Start Sunspots!\n"
]
}
],
"source": [
"print (\"Start Sunspots!\")\n",
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "4a418246",
"metadata": {},
"outputs": [],
"source": [
"# load the sunspot data\n",
"sun_file = Path('sunspots.csv')\n",
"content_p = \"\"\n",
"if not sun_file.exists():\n",
" URL = \"http://cesar.kso.ac.at/sunspot_numbers/daily_sn.csv\"\n",
" print(URL)\n",
" req = urllib.request.Request(URL)\n",
" req.add_header('User-Agent', 'urllib/0.1')\n",
" with urllib.request.urlopen(req) as f:\n",
" content = f.readlines()\n",
" for line in content:\n",
" content_p = content_p+ line.decode()\n",
" with sun_file.open('wt') as fh:\n",
" fh.write(content_p)\n",
" fh.close"
]
},
{
"cell_type": "code",
"execution_count": 23,
"id": "79bbe9b8",
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" tot sn ss diff\n",
"time \n",
"1944-06-05 23 0 -23 -23 \n",
"1944-06-13 0 0 0 0 \n",
"1944-06-14 0 0 0 0 \n",
"1944-06-16 0 0 0 0 \n",
"1944-06-21 0 0 0 0 \n",
"... ... ... ... ...\n",
"2021-06-29 61 10 -51 -41\n",
"2021-06-30 69 21 -48 -26\n",
"2021-07-01 53 11 -42 -30\n",
"2021-07-02 67 21 -46 -25\n",
"2021-07-03 76 23 -53 -29\n",
"\n",
"[21022 rows x 4 columns]\n",
" tot sn ss diff\n",
"time \n",
"1944-06-05 23 0 -23 -23 \n",
"1944-06-13 0 0 0 0 \n",
"1944-06-14 0 0 0 0 \n",
"1944-06-16 0 0 0 0 \n",
"1944-06-21 0 0 0 0 \n",
"... ... ... ... ...\n",
"2021-06-29 61 10 -51 -41\n",
"2021-06-30 69 21 -48 -26\n",
"2021-07-01 53 11 -42 -30\n",
"2021-07-02 67 21 -46 -25\n",
"2021-07-03 76 23 -53 -29\n",
"\n",
"[21022 rows x 4 columns]\n",
"tot int64\n",
"sn string\n",
"ss string\n",
"diff string\n",
"dtype: object\n",
"tot int64\n",
"sn float64\n",
"ss float64\n",
"diff float64\n",
"dtype: object\n",
" tot sn ss diff\n",
"time \n",
"1944-06-05 23.0 0.0 -23.0 -23.0\n",
"1944-06-06 NaN NaN NaN NaN\n",
"1944-06-07 NaN NaN NaN NaN\n",
"1944-06-08 NaN NaN NaN NaN\n",
"1944-06-09 NaN NaN NaN NaN\n",
"... ... ... ... ...\n",
"2021-06-29 61.0 10.0 -51.0 -41.0\n",
"2021-06-30 69.0 21.0 -48.0 -26.0\n",
"2021-07-01 53.0 11.0 -42.0 -30.0\n",
"2021-07-02 67.0 21.0 -46.0 -25.0\n",
"2021-07-03 76.0 23.0 -53.0 -29.0\n",
"\n",
"[28153 rows x 4 columns]\n"
]
}
],
"source": [
"# data manipulations with sunspots\n",
"sunframe = []\n",
"sun_types_dict = {'time':float, 'total':\"string\", 'sn':\"string\", 'ss':\"string\", 'diff':\"string\"}\n",
"sunframe.append(pd.read_csv(sun_file,sep=';',skiprows=0,names = ['time', 'tot', 'sn', 'ss', 'diff'],parse_dates=['time'],index_col=['time'],dtype=sun_types_dict))\n",
"sundf= (pd.read_csv(sun_file,sep=';',skiprows=0,names = ['time', 'tot', 'sn', 'ss', 'diff'],parse_dates=['time'],index_col=['time'],dtype=sun_types_dict))\n",
"\n",
"print(sunframe[0])\n",
"print(sundf)\n",
"print(sundf.dtypes)\n",
"sundf['sn'] = pd.to_numeric(sundf['sn'], errors='coerce')\n",
"sundf['ss'] = pd.to_numeric(sundf['ss'], errors='coerce')\n",
"sundf['diff'] = pd.to_numeric(sundf['diff'], errors='coerce')\n",
"print(sundf.dtypes)\n",
"\n",
"daily_sunspots = sundf.resample(average_interval, origin='1960-01-01').mean()\n",
"\n",
"print(daily_sunspots)"
]
},
{
"cell_type": "code",
"execution_count": 24,
"id": "fd304ce1",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<AxesSubplot:xlabel='time'>"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# plot the sunspot progress\n",
"daily_sunspots['tot'].plot()\n",
"daily_sunspots['sn'].plot()\n",
"daily_sunspots['ss'].plot()\n",
"daily_sunspots['diff'].plot()"
]
},
{
"cell_type": "code",
"execution_count": 25,
"id": "15486960",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<AxesSubplot:xlabel='time'>"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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avdhzoKLWsha0JvXElFpZKTUHmGNOFwBjLZapAa5yQDbHsLp9vG5xBG56L7wj2ZLBYwf0pEHdKNhfScds65Gtqc68GgkrSTx2OC2xeoF/4JN1AGx7ZGKL9gc/WcfqojIe+/7JKZFNE542NyK3reCVm95PI1uDOXlQdwA6ZlvbNZH+1v6KWm5/axkLLSzWZGClPNfttl+EZ8XOUgeliY1YLo/g/+nPq6pt4Dul71Q0i3fsvDCYd0WTF0x9m+Tvq0hiaovUUVXXyNRVu13vT7FLTX2j2yJYEnzlhj4c/HNVtz18p/TjIW97CTPXWtcd9SoZHrWwQ59Bf/h0XfP0fe+v5H8/WpNiifxPfWNiKtDLdkHoZezNqzq9aLPlEoO5+vkFQEs/o18uPi8EPgVkWLq9pDlVrkefSbbxwGFt5s1F3oomShYKbeF7gbRQ+n6iVRoG90RpRUllHXnbSyzn3fXOCk/JGo12meGfWqnOz1OdoHvGCwP4DlTUsqoofKnH0KPtc5vB16SFeycSXrL4gsnwSPTOoq0HbSUAC05l7SWUUs3J9YIJzlYZylQziZjf32ZSyYqdpdz06pIWbeU1Dbw6fxsllcaxdvta1hikrdL3+g3tlXKJ64PLTrooR6wEXFJvLtrBDS8vbjX/mhcWplokS+ZuKqagOLHOb7dqL9hV4lc+902rKDA/XUttjbRV+l7HK1k2w2GlaLwo644D3kulHMzkV1o/kGLFLcPgvaWFVNU1Ru13CjzU3DZgNAZa6XsW072Twj3++J9LeHFege3lq+pau338GteviZ1AQZomFf2Br3363sF3HblOv8o6aX0UllRx1XMLEtpGQB43LP0VO0sZ2L2D7eV//Z/VSZTGfXzz/HLZgLYbYebFN8F0xHeWvlNKOhl+0MYm5UiGTQjy6XvoTgmVZYcHq1BpPIrH3ZXphO8sfadIhn/RiQv6Vx+sRinlaSvz4hP6cVpuD2auazngzUv389uLdwDwTt5OlyVp+9iNv9cK3xv4ztJ3Gq9diGuKytgZNPw/1fLZeRjecf5wxuT2bCXbyp2lVFv4+VPNhj2H2JJgRIzGPvWN0Ws+BN6svWzMpAtpq/TdCnOLxtb9lazcWeqKfLHu8bgBXVu1LdlmPXgrlVzy5FeObMer14jX+MOn690WQRMDaav0k4GTRnnAInI74dqQ3p2ap48b0JU/TDqBAd3aA3BKHEU0NM7j9svqhj3RM4J6PQQ5nUhbpV9n45XUTZpH5Losx6lH9eAIU8kP7tmRG87IpVfnHJelSg0vzCtIeUoGP6IUVNZGd+u1SK3cRl6iVhWWkjtlKqsLw6eg8Bppq/STQXKKrDu+yZipqG3gfz9aw+KtB1u0e71kYiJceFw/1u0+xLYDum8gGkWl1dz5zoqIy4TqeC9c107wxXoj/cisDXtdlsQ+Wul7nFSPYrS6GWvqm3h9wXY27W1Z+3fR1tQUGXGDn5071G0RfENxefRi8+8tLeRAZV1YC7+pSdHkoWpmbZm0Uvp2ogwSwclLNiNwZlJ4H8T6yj2oR8fkCOIBtPpxnoYm1eptMcCVz33D0F9PS7FEiVFWXU+FjWSEXsM3Sl8pRVlVPbX18Svu33zonxGkgciRSg+EQAYIVYSDe7ZdpR/ADxE8fnGVNDYpHp+xEWhtYCzfUZp6gRJk5IMzeWX+VrfFiJmoSl9E2ovIYhFZKSJrReRBs32IiCwSkXwReUdEss32HPN3vjk/N17hZq7dw3efmc+BilrKaxsY+dBMXk7gIM9c19rv5tUbJnBTzFjrAV+h9/We4xyoiO6y0MRPXYO3AynaMnYs/VrgfKXUSGAUcImIjAMeBZ5QSh0NlAA3m8vfDJSY7U+Yy8XF/oo6lu8opSHI11daVR/v5pKOkw8Qt/RsLH9hpUVB7m4d2jkmSzw4Vcz8Z/9a5sh2NNas9FG0S1sjqtJXBhXmz3bmRwHnA++b7a8BV5jTk8zfmPMvEI+kXvSEEJ4mtiPkxdw7XsmTr9F4FVs+fRHJFJEVwD7gc2ALUKqUCjicC4GB5vRAYCeAOb8M6OWgzI7ibHSMc9vyyHOyJTZeZa45bXAKBEkdXjwNoeg89c5y25tLeX9podtiJA1bSl8p1aiUGgUMAsYCxya6YxG5RUTyRCSvuNg63ttvF/MnK3c7tq2t+70RH65UbPZ/7zQZuKVpu0xbvYd73lvpthhJI6boHaVUKTAbOAPoLiKBLJ2DgCJzuggYDGDO7wa0crQqpV5QSo1RSo3p06dPxP36wNgC4KlZm90WwXE+WFZIbQydbgerwteeDaWmvrG5EIdG4yeW7XA/x1S82Ine6SMi3c3pDsBFwHoM5f99c7HJwEfm9Mfmb8z5XyovJYUPQY8HaUmiZ+rZOVtsj0ye+PRXjHxwZmI7TDJ+MTj8yMgHZ3Koxp8P/e89843bIsSNHUt/ADBbRFYBS4DPlVKfAr8C7hKRfAyf/cvm8i8Dvcz2u4ApzovtHLGUB2zrRPNf230e2H1w6PTHzrBlXwVrirwVDVNmI8qurLoepSM3U07UIipKqVXAKRbtBRj+/dD2GuAqJ4QLKI8L/jaXWXefm/D2rDpHN+4pt1hSY8WBisOum0hx1qE6v2WiLW07O80Dn6wDYNsjE12W5DAjH/L2G1w644sRueU1DbwwN3GL/GBla39zhi+OgDcI7rOoiJBVMdS9M3PdXobcP411u6On4PUc+hmVVPwWrNEW8I3Ke/WbbUnZrh+G2aeWyDfhqzZGRAdvYcGWA9z6xtIEZXKP615cRGVtAx8sLeS+99tuRIcmffCN0vdwX3Cbwc7jz+ptKZTgUzVj7Z7wC/qEBVsOcPd7K3k3r+3GbruFvq1Tj6eVvgozrfE2wa/sH60oirCkRqNJNZ5W+qlA9ysml5KgKA6/WnXV9Y1ui9Bm8ekl4Wt8o/T9qjD8xL7yWrYfSDyfTvC5ys7yzSUWFrfrFGs0TuLtO1LfbCnnmy2JZ6kMPm1t4UWqLReLcRvdV5d6vK30U4Bf4sbnbNxH7pSp7PdAnvdFBQf4yWtLws4P9umn0tJ/fcG2pGy3NknunfUOhrAeN6CrY9tKNbpMYmrRSt9tAWzy8tdGqOTaXe7Guguw51ANyyJUOgo23i46vl/SZQrwp6nrk7LdfTZqwMbD5X//Oinb9ROfrdnjuzKJfiftlb7fSJbVqUk99Y3awp2+xn8hvXbClr2Mp5V+Km4Jn3h3mq3n55OUK2jOxn22l5270ToVdgA3VNmnq3bFlA00FvxwjSilWF1YRu6UqSzd7p8MkF4bkWvH1eT3aC5PK/1kcLCyjpe+Oqw4c3t1SniblbUNfG5Rf9dJrEoTOkks1svHK3dFnO9G59y+Q+73dbjN3E3Gg/vLDR6oq2wTr/XjPtkG06OHknZK/573VvLHIN/vi18VUFiSWJjivvJafvp6XqKiRaTczHWTLKNzQQxROw1RrCGP3ccaD+M1pT9t9eFCSL/77xrqG1u/PVrdg09+sdlyWS+Sdkr/yw0t3RhVdY38zzsr3BEmDpLlanjPwfJw4W5kr93gmvjYXVbN/Pz9bouRFILfUt9YuJ2Hp21g0157mXj3lNUkSyxH8bTST5WS8FPEmNsJ4hZuPRh9IQX5+yriugmmrd7NwoLYxwqUxlCxK1b8ENa7YU85f5m5Ken7+WhFEb//aC3Xv7TIke15zac/pHdLd+8r87fy7JwtLdrCXQ5nPzY7WWI5StR8+ulAoj7odBpgstiG0t+4t5yrn18AwPdGD4xp+49O38Apg7szbmivmNZ7+sv8mJaPhSV2HnRpwi//vcLR7S0s8NaxPXdEH75Y3zqo4ZWvt9KkFD85e6gLUjmLpy19jcGo4IIU3jc6WRSHpe5lykNK+tU1NLF2l7cqVWmcoS5MGO1Dn65r7guM9La9q7Q6KXI5iVb6eL/jsTQoaZkPdD5//TzIzWAe3E7ZmfTsnG1rfa+dj/+uaBmt9NCna5n49NfsPJh4niKNt9hX3tolGXrPdcjODLv+TB+kEve00s/wg4YjtUrKB+5lSx6cdCJXP7egeWRxOPzw95ZtLwWMGq9eZMdB71ubVngilYSNm7lbh3bJlyOJeFrpd+9ozzJMFD+55JPVkZuVgidsUWl1K1eJFX46H15khg9HuYKRi8hOQfWUE8Ot8fBnGzj2d58lTxYHiKr0RWSwiMwWkXUislZEfmm29xSRz0Vks/ndw2wXEXlaRPJFZJWIjE72n0iUIh/44QIky9KPFnsfL/9ZbhRRsdvZ7YdIGc8/k8xDuGHPIR7+bL2ly8Kr7K9sPcju83V7mfDE3NT4yxO8/Dx/bWDP0m8A7lZKHQ+MA24XkeOBKcAspdRwYJb5G+BSYLj5uQV41nGpHaY4SQm1koEPdGJEIiVq8wNFpdXND7AMj5+MguJKnp9bQEmlB63nGCirrmfT3goaUpCryCoNw3+WxVD9TbkfVh2NqEpfKbVbKbXMnC4H1gMDgUnAa+ZirwFXmNOTgNeVwUKgu4gMiEc4j99TzWh3RHQCh2jepuKoKSW8fDi/9ciXzefbq9dng09GhlphdUgDD9lUHO8Xv4rc53Sopp6Hp4XP5tqklGeviwAxxemLSC5wCrAI6KeUCoxZ3gMEcugOBHYGrVZotu0mRjbtrYh1lTaP162IcATnuo/0ZuWnf+fVm9tPgw3tEPg7Xjjet7+5jK82Rx6N7AExI2K7I1dEOgMfAHcqpVokdVfGozimS01EbhGRPBHJKy62ztroZ4slWdQ2+DPD35qiw5dMpJu3d5ccunXw9pjBjTaH5buJUsqXb6BWfTqHLX331Wk0hd/QpJLWP+YUtpS+iLTDUPhvKqX+YzbvDbhtzO/AMLYiYHDQ6oPMthYopV5QSo1RSo3p06dPmP3a+g8eIHUnef1u7yucaEQ6r+/eegZ/vOIkAPL3lfPgJ2s9Gw+fyFtXsv/TnUH5pJy6j9waed7sTnNl77GTrBTfTmEnekeAl4H1Sqm/Bc36GJhsTk8GPgpqv9GM4hkHlAW5gWLCj5ZKsvHLhR8Ju8qysKSaV+dvo9gDJSKtSESZbt1f6ZwgFny0InL661i56rlv+MVbyx3dphXLdxi1AJZuL+Gnr+dRWFLFkT07Mm5oT0/39fgJO+/R3wJuAFaLyAqz7dfAI8C7InIzsB242pw3DbgMyAeqgJucFDjdSeXbT0mSKgTtOVTjq0If4UjkVPhNgS3ZlprzFTD09h2q4fN1e7l7wggOVNaxsOAg1XUNKZGhrRNV6Sulvib89X2BxfIKuD1Bufh01S5byb3SjZqGJqrqGuiYnXy/966y5MRFf7isiMXbop9bryvGRB7AqXCVeC2DZTpRXlNPl/beHLnr2RG5v3hrOXk+sQar6lLXuVrX0MT3nvmG3ClTeTrJVX6SppdiVJbedWnFL1kqXZfePX7R8auL9/EZG90WISyeVfp+wioVqxXXnDY4+kI2CFTo+cfs5KUTdoM3F21nd5LeLpJBQpa+tsLDMnvjPn773zVui5EQtfXe7czVSt8B5sZQVNw/EUnJw+oQ7K+o5TcfrmHyK4ub26rNN6iKWm/6cpcnMLrYrxZsKlhTWMYBi/4kPx2zhiZlq8i6G2ilD/TtkpPYBmxqcqWcuXC3FBuRH8kODevdOcHjEgOBG6QkKOFWYEBXaOUir5DIOJJUKDA/KclwbNxTnhJDqay63tHqax8sK+QnSa6bHS9a6WMUNk8kmsSrceTxEggnbJeZ+teSYEUVMJSaPKq9Esm9o9Nxhyf42Nz5zgry9yV/ZP7IB2cy6qHPHd1maD1ur6CVvsmVz34DGE/8WEe9HrQZ2uiXmy/ZeeIt31Ask64EZnn0wHk8esevhB4aP1SjipUl2w5y3/srXbkOtNIPYeSDM7n+RWeKPodyzdgjk7Jdv2H5ZmRx7Xu9szORR9HyKEnnnMDbRy+9ufaFhbybV+hKygat9C1wOlT06L6dAcjJ8tfhTlWuk6YmxQvzClKyLydJpA7DjgOpdAkmdh43pzjXULiHvd8eYl3bezOHlCe1UEFx28quGahKFelNrl/X1HWauk27zJaXnQJesiij6PUUxhsSyIM0dXVcmUlcIdX1JkLvE8+696Lw7ZFHuC2CJZ5U+n+aGj5ftZ+J5K7okaLSkF5gz6HwlZz2ezTPjhXTPV4E27GQwRTr3I9XOps3yIu4+dbiSaU/y6Ve70UFB1zZbyJ8uLwwadtO1b1eFyX01KuWvtcJZNrMs5HyIhKprhCW7GR06Y4nlb5b3PqvpTGvE0sh58Br650XDuexK0+OeV9W/M87K1u4wzbvLY8p3riguKKVdR2IKKhLQT2DTtmZYUMym4tnhHn8NDUpyqrqqan3Z42BVLEjwZDi9u0yHZIkOn7z20firUU7uOIf8y3nuWnHaKWfIGt2lUVdxqpDdHi/zo7JEBwCedET85j49Ne21z3/r3M58+EvLedVpyCnUFV9Iyf8fkbEZcK5xcqq6xn50Ez+vXhHMkRznJlr95A7ZSo7DlTRu3Pq3HmJKtLuHVKXOOxfC7enbF+pINw9pN07cfLUNaMc3V48IbN2ntiBZYK3f8qRPVosc/EJ/WPfeRhijSoJZ9FnZiTfHrE65qsKS1v8jtaR5xfr8L8rjFpCq4pK2V+RnLTVTlJR28Azc/JpTGEs+QqLUNbxx/Rh9j3jOapXx5TJ4RTRPGNuWPy+VvrdfdL5GTjxATeGlRI7fWjPhPaxYc8hx9IVpMLCj8T/fWkkkotWENsLvv5YBtcEzns8UT+5CSi8LmboYG1DI9e8sIBv/99XttZ79LMNPDZ9I5+5HGnUMSeLIb07kZOVOjeTU6TCRRorvlb6wcm5nOTSE52zuiE1yumNBdt5dPoGR7Y1f0vkOqDJJqBH7arT2RutayyngniM4HgCFR6/amTsOzLp0zmH9/J2csxvp7Ow4GCLesWRCCS683r5Py9TUFwZcYS/G2+pvlb6ThPXkGgbCv2ui0aQnZnBkD6dLOffeeHw2PcbwpuLnPNrpzpaozX2zsOhakMpzdvkotI3v3eXVZM7ZaqtSBkrr9nLk8dE3k8C2mF3WQ33vr8q7vW3p3QgWdujvtFbDsg2o/THJegegfgsGjsDV84/th+b/nQpncxqV6E69c4LRzA6xMcfCysdHtKfqpG44bCr4GLNkZQMAobCgi1GuG/Eh695WK0eqst2RB4FnkiOlr0RxkVE4sPlRh+E23Hzk19ZzJXPftNcR8JvpKBrLCbajNJ3goDS37S3nLveWWFrZPAv/73CkX0nEhY35T+rY17nmTn5PPnFJst5XskDPqR3pxbfobj+QhIjAXEzLLRASZTQ30ROiZNvgW6xdHtJc1JEv+H+m3NLPKP0D9XUs3FPuSdirovLa/nP8qKkRFgM7tnBEzk5vt68nye/sC63OMMcaerWtXrVmEEA9O/aHoB+5rcXcerx2NMnQQlusqoweni0F7EqAuRmllVPKP2Kmgae+HwTFz85L+7c9LtK43uFtSLg3nD6xGRmCF/ddz4/+tYQR7frNAFl75abx233UiwEFFG0S2Xz3nL2lBnXqJU7bsIJ/SKun6qMo8t2lCRUW0LTmvKa1kp/YI8OLkhiEFXpi8grIrJPRNYEtfUUkc9FZLP53cNsFxF5WkTyRWSViIy2I8TWA5W8On9b3H8CoMRmTns7BPLJe8PJkRwi6VW3E1w1esS9ZAe7Loe3F++MmL016jG3OCSTRjmf0Oux6RsciwLThOe7owYi0jr5YCqws8d/ApeEtE0BZimlhgOzzN8AlwLDzc8twLOxChTNtxmOYCV2uUPZ7RYWHEioUPdfrxoZU2TO9acnN9/+pr3lrNhZyp6ymogRBRvNVLodUjj8Ppjb3lzmu0yr0eKxo3XmRXu5CT5bPzt3GHPvHc85w/vYE84DfHXfeY5ta9+hGk904tvFSlZPj8hVSs0DQuPQJgGvmdOvAVcEtb+uDBYC3UVkQCwCxZtALNQlcPbw3nFtJ5gnv9jMtNXxZ1K88tRB3HnhiLDzzz+2b9zbDuacEfZu/qe+2MzP/7WUcQ/PYvHW6KGFPTqmbvh9KBv2OJ/D/U/fPdHxbQa4P0xn+sqdpXy0oijh/pFg91Gn7EyO6tWJXgmkcvBC31k83PXOCsb+eRb/7+3lbotim8pa62Pt1vt0vO8W/ZRSgWF6e4CAQ3IgsDNouUKzrRUicouI5IlIi+rBx/bvGnHH4UYmJssNnMwT88z1o1l4/wXNv887Jr6HgJWMVhE4CkW1T252O90psY7Q7No+OQ+xAxHSQX+0Yhe/+XAN159+VMRC8yJw3jHhH97BPv3AtX5M/y6xC2tSXtNAbUMj5TUt36yT1b/o1P352RrDCJuxdq8zG0wBXuuiStihpIzezpgvFaXUC0qpMUqpFqNSusWZ3ClZYVGJZiiMRPt2mfTvdjgy5cLj+8WViGuLhSvEqgybUpDptSswApEuqn/Mzuemfy6JaXuhf/2B7xzP7759fOyChXDqH78IO0+hEIGO2ZkRawX06JjNy5NPY/OfLrWc36TglR+1HMCVSN+LQnH1cws46YGZreZ5+Qrxi9ESTGVQ9M6qwlJOeWgmBxzsg4yVeJX+3oDbxvwOjCsvAgYHLTfIbLNNNJ10dN/o1o2Txsp7eTv5aEVMfyEh4unYKSyx1+/QpFTYyBgr14ebUTTRohsen7GR/H3R/f7v3npG83QqOqhnrN3Toh9IKUOJFkcpDnNE9w5kZEjE83+2wz78lSkMgfRqRNayHSXkTpma1H0sDKrT8dzcLZRU1bNwywHXjkm8Sv9jYLI5PRn4KKj9RjOKZxxQFuQGssX8/Mh5X7qH8TMn6/BV1jVaDsB6ds4Wfv1h7IOionG5QxEZVteTUuE7FI8fENmtlmo657Qcy3CgojbqqFUrxg7pSbcO7cL28VzhcARMVV0j5z4+p/n3z8cP4/2fn8k1zy9MaLtW4cOJ+PT/bia1SxVuxqVHYt0ue3mIEuEfs7c0h6IHDkNhSTWNTYqGGEcZ7zxYxdxNxTGvF4ydkM23gQXAMSJSKCI3A48AF4nIZuBC8zfANKAAyAdeBG6LVaB38yJ35L6/1Jj/5++exIignPTBT81UXGCPTt/AW0kY6RgYpNOrU2KDdax0uyK8Gyw7jqLtTqS+sMupf/yC7z0T34jMlb+fwBs3n86s9S39wNeefiS9IvjZnaBf1/aM6NeFcosBOtH4+fhhzdMds1sP6Esk3O/1BdZ56wN3TmBMQax0yvZXJsw5G1NTpW/bAaMaWJZ5zgLRXrGmfpm+Zg+TX1mckJvLTvTOtUqpAUqpdkqpQUqpl5VSB5RSFyilhiulLlRKHTSXVUqp25VSw5RSJyml8qJtP16uO/1IOgVZg8f0ty5K0t/DozmTidVFoZQKa+kf0S32wSJ3Tzimxe/gTulEEYEv1hlK+vEZGx3ZZmiFrtCO4FvPHerIfq4cPah5+urnFyTsPhjapxOn5fZIWidrKCIw7uFZca3703Osj6GI8MHPz0xErFYkGoG0pqiML9anRumv3228UVyQYMReoEM/EdeQJ0bkxktWkAYb2L0Ds+8Zz8hB3bhu7OF49zsuONoN0RLGKj9LLCwqONiiAwmMQWfhipL3sPFmceawXpw8qFvz76ueW9BifnCndKJU1zWy2cJnn8hbXLQggZMHdo9728HUNzZxqKaexiZlKzQ2GleOHtTiJveqfzwapx7VgxvGHQXQ4i09Xo793XQ27Y0/tDdSx7rT/HnaBp74fFMrwyPWqzmweoYYldjiwddK/72ftbQchvTuxEe/OIszjz7sv3XLlfiDMYOjL2RB4H6ec8/4hPb/k9fzuO3NZS3almwrSSxx109ODzvw7a2fnh7/hi0IWzdXEbfl/KtLj+X330k8Wican6/by8kPzOSxGYmNbD1jaC8AxhwVfwbWWFm89SALCxJ/UIXj/suMczDjznMc2V7A3RsPiaqGWMcCPTVrM3e9uzKhfQbuX0F48JN1cW3D10rfq2z4wyU8/L2T3BbDVm73aASU5LH9u6AU3BQmb9CZwxIfDBdMuFxKdm/Um88awuJft3Q3dczOCiu/kwTSeLyzZGeUJSNzzog+rHvoYk43lX9bIHAOkvm2MmPtHn773/BBFp+u2sVpf/qCV77emtB+whkmsRDrm+th9078+/ed0p948gDLCJ7QmzkQ/ZFIL3e8tG+XmbB7xskXlILiCv45P/oFbjUCd+wQo7NWRPjXou0M+/W0iNsYFqZQTKzc+561RWT3JsnMEPrG2J+Tk5WR0oLl4fjHdaP5+BffAqw7cJPJ6z8ey4TjIyd/s8PlI4+Ie8xNLLwwr6BFBb3PVu/msekb+Pfi8A/c6rpGistr+WpzYhXi5ucfiL6QwwQu/y837GN3nJ3tvlP6WRlCTlCkyZd3n8t7PzuD40JCDv/fBUbOGy/WqIxEMmLJ1+46xAM2XgUzMyJfDnb0rVN1i8NFu9h1T9VG6OT76r7zeOsnrd1RFx7fj7zfXsRPz3Y3C+rEkwdw8qDuruz7nBF94goF/dm5w5h37+H8Orm9OrLy9xMY4GA/TzjmBlVOe3X+NrYUV0Yc7+PN4NHYeHtx/JGD7id2j5H//fbxZAUpp6F9OjPUYsxK4KR7NDw4Zfxz/lb22qjuZWA9ihfsj4NItnUX6bU9mFkb9vHgJOt5g3t2ZHDP8IXG/dRR2qFdpuOjVAPuqVg4fWhPjgxOkSLCi/MKmq3RdpnJPab7K2rp0C6T0mpjpGukhIL3JVA6MpjvjR7If5YlNnAzVvUUSK9SZHNAphW+s/Q7ZmfRLYZEYE7p/MraBt5fWkhdQ1Nz+JXXqaxr5IFP1vHsnC0Jb0vEGwNsoo3jCGB3lDLArLvP5dUfndb82yn1ZHc7/braGytglVN/8pm59gUKQ+j1sX537BExVtfGisJSunVox5M/GEXfLsm1+E/70xc8P3cLm/Yejviqqktu8ZJ7Lz4m+kIOE5A+nnEfAXyn9N0ywn748iLueW8lT8/azMYIGSCzEvTln3l0L/4w6QSyXcizbZdTI0ST+MdGPsywPp05Lyh+2ilLv6Sqnt9OPM6RbYWja4fEX9afn9dS6W/dXxnzNqyU+g/GDOahSSdwxSmWORcdJUOklevPaiBiuEFp8eCEKzbWZ1BgeTu1ucPhXc2SIIN6dOTVH53mWLjb9gPGMOoDlbURO2lvPCM3of2ccEQ3bjgjN64RsokS7QIMzA70l1gRHC7rVwK6YsxRPRJ+iP9x6vqI8+MN7XWSuoYmXvqqgNwpU3k3L7aIo19dciwAuRZ1jM8Z0YdJo5Kv8MEovGPHLTV9Tfyp0kNx0gCtrG2wVZvaiQpqbVbpd87J4rxj+9KnizPD7OvN4dLdOmRHzNfhRBiXW4TL1xOY179re04f0rNFR/oTPxjJH644nKzttNzUxZRH4scJhGYGDsP4Y/pwVJhU3k7idqWyqrrG5odTrP7uRB+KTvLGwpZWfOitWNfQxIKC1EfcREQZCv+E38/gUXNcx5JtB1lTZJ0Mz4micr5Q+nZ9nlYETnyixcjPGGbESo8a3J3n5ob3kfuoD7AVVs+r5rhghEtPGsA7t55Bz6DRuxNPOqJ5lCUQNurEqWpmdjl7RPxvHAG3QCqe3x1zMhPq/Hbbxjj/uL78/bpTWhgCXiHUAHM6ks+pWz1QQ/dDs1P4d/9dw/99ubnVcr/+cDVPz2rdHiveO1MWLPr1hc2dJvEqVTtpBiJxODVu5LvMS5aPXexEVgQf9xH9ujT/T6vz8e2TWxdLS/VhSaRgSkDWYKvqh+OSU8ry9985gRn/k/jo1O+fOojvnzoo+oIOM6xPZ7598hGu1HqNRuid6tVbM/QeyhCxrBO9cIszbyneO1NhGNanE5ec0D9pxVKisXxHKRDZsrp27JFMPDm1Fq0TBNwLVn8t3P+9yBzAY3U+rGKzUxUGecqR3RPexgkDjfxCxw3o0nxMvntK6hVqKFkZGTx25cktKqwFUmKPj1B1K1mMDMrD5EVCI3WcdqN1ad8u4brW7bMz2HfIMCgDej4zw1rpO4VvlP4lJw7guRtOjdmicPrQPT+vIOy87586kFGDuzu8x+RjZyBL6CJPXjOKb6acT6aF+dSzU0t3XN8uOb6K6rn4hP7MvXc8E07o3xwP7QUrMTNDuPq0wRx/xOGBiOcd25c594zn2y4YG14fzxB67z/0aXy5asA6PLNDdiZXJ9gRn5OVyd3vrQAOJ4DLyBAiDDNIGN8o/XgJuCG6OzRoKJnlE92iR4RRtAHXT9eQ45eTlckR3a3TMf98/DDOMqN4Xv/xWM46undC9Vzd4KheRjRKrPnO3SAQOXPCEakthFNS1brkX0czn36Hdu7n1VdBp66hsSmmUayhbtrbxg9j2yMTW+8jbukMHvxkLSVVh6OOmpoUVbUNzNtUzL6QjLgFcYTSWtHmlf7gnh158PITeOHGMdEXtsHBiLUtvW35hONF89hYDVw5fkBXfjvxOJ78waiYtjnUzMHTKSeTv/1gFLeeOyzKGolz0sDkuRsijc3wCj9yYKBWNI7uezglciCMuaUMQ7j34mP48VnJlyUaX+fvZ+OecgqKK3jii00xrdsvKG/TyMHdk/ZW8+r8bS1i7r/O39+cUnxVYRlNTYqa+kZHSzq2eaUPxqjFfl3buxL77gcC0VHXn25E4QwMsuBFhJ+cPTTmClOBAVxO5eKxgxMxzOEIRFh4GRFJKNItGn275LSwgEdb9J9kZ2Vw+3lHtypQE4lkvaHc/tYyLn5yHuf/dS7LtpfGtO5PEsy/NNRi3IIdgsdJZGYKD3yylmN/Nz0hWUJJKy049Y6zkrp9j7s4o3L3hBHce/ExvP/zM6IvHIVYc/Y4RbJCGFORMdIJnEjLEA4FLUYuhyY5jJcbzzgq+kIJEmt8fnDW3kjXcPt21irUqq/LDp+uOlxSvLa+ydERxAE8r/QDKWadYHg/f/mVA/TpksMjyczPb16fIsLt5x3NgDhKJ4bddAqfhFed6vzo1m8dbYzPcCMcMh5Oy01e3WKlFPdMOIZXbzLyFF1wXGKl/wJV2JIYqJJ0ju3flb9eNbJVuxOXfbJuHc8rfadTzI5MYnRNstTbkt9c6Fqq3XgRaW3tJLNo9sY/XsLkM3ObC8o7lbto4klHMGnUEQnXR0gVoWlHnOznUMo4p+cd05ctf76M849NLO/+CUcElL63tX7wYMTg0ecBrgwxCE4c2JVxQ3tx3yWJJWS79Y2lCa0fjqQofRG5REQ2iki+iExJxj7i5f5Lj22evmHcUbxx81iuOc0ZC/GUIx1IQVBdCmWFUJjHWz8Zy5cXFEHlfjKr9zNMiuhLCd0p5/KMbxguhXSimiwa+H7mXHpRxijJ53+y3qMfBxktmzgzYw09OMS1mbP4Yebn/DLzA/pxEFCMkQ10oYrM0u0w73FY8rJxZ9dVQsFc47NlNhzaDXvXQekOOLAF6qqgqQn2rDbm1VXB0n9CxT4o3ggHtzJpaAZbpoxiSPtKWPMBbP+Gawcb+71ilPPhhQEf8l+vHskfJp3AiQOdcT1cd/qRPHXNKQAtSi3efl7yO6bjIfTN6q6LRji27WDVHK/7IphzRxhjC04a2I3JQS6eiRaD+1LBcz88tcXvp64ZxU/PHtLCkr9h3FH8+5ZxvHurtQt02yMT+fSOs3lo0oncNt6b9bnF6XS5IpIJbAIuAgqBJcC1SqmwQbI5A4arAZOfbNX+/84/mrsmOJu+dFHBAX7wwkJeunEM5x/bl4wM4Z0lO/jVB/bytEfCKqQrJpSCB7snLIdG4zQP11/Lz8d2o/vy51K+72VNRzM6I79V+6sNF3NT1gzLdVY0DWVURvgxNVbUdOhH++q9hxuGjof+J0PBbMPAAeh3IuxdA71HQPcjIf8LAJ5t+A7DZBcTMpfCEafAruWQmUPT0Rcydd0BvpO5kP2qK72ldd6u6Y2nsV915YdZs6hSOfy9YRKKDJqQ5s+bjRdSQ+tO+u2PfnupUiqm0MRkFFEZC+QrpQoAROTfwCQg5pERHXOcFy9gCQWXNHRqpF5dQ1NiEUK1/sjTr0k/7m/3Nix3Z99WCh8Iq/CBmBU+0FLhAxTMMT7B7F1jfO/fZHxMfp71yeFldpkHqrGWjI1T+Y7p1bRS+ACXZC5pnu4otdzX7t1Wy3zYeLal0o+HZCj9gUBwftZCoHVtOhskw9fXXFEr6GXVqVDOLcUViUU0tPf2sHZH+c0ejvnddJpMi0YhKODCET2YtamEHOqoIRsBMmiigUwEhWp+QAugyKaBejLZ+sh3DJeTUe0l6EQ3Gb9VI2RmQ0MNSAZIplldugEysoy2ugrIzDHWkQzjk2HesUqxdMdBrnxuIQDbHp5I7v1TyTAlb0cDNWSTSRONQV7TLBppIJMsGsk2l1FANg2MPqo3b996prFgUyM01kJWe0OmrPaGmy0jM0gmU94A9dWG7JntjPlNDcZ/rK9ixINzAbj/suN5ZNpaFEKjKe1AKaZOtaOBTDJportU0J46KujAPtWdTtSgEHrJIQ6pjpTQhYwMYc3/XgiVxZDd2dhfu/bGMc/KgcY6Y/+SYRzvjEzju/YQdOhuyFtRbPzHLgMM2TPbNR9bJINxf1sM1SUsvP8Cnp69hfeXFrK/PocO1NJAJvVkGe5Imqghmzqymo97B+rIpIlyOtCVKmppRw71zevV0o56Msmhnjra0Y4Gcqin1pyuJ4u3f3o61764CEGx4aGLjWtMNRrfgf/TWGd82nU0vpWC+irOfmoJldW1LPvthZCVbZw781iM/PM8MmiiniwyTBs+h3oyUJTQmSzzzNSRRZN5jgJ3RWD5SpwrQuNauUQRuQW4BSC7/2Hf1+CeHbjouP6s332oRY4Rp8jt1YnHv38yI4IiecYO6cmIfp3ZtLeC1348lqmrdtmu0BTglnOGOlMP9PL/g4/vMG7mJu/HhsdD04Q/k9GuA/dOHNmc0veGcUeRnZXBJSf25/NNC6g2L/LO7bOaY+RVqzcyoY52hweOBcpoBvu1JdB5bF7q7UIikzKCOpdzIkR3iZDbuwu3jT+ai0/oDyL06JjdPJqykcwW3wEazP02kEUDWZw9vDd/vWokU1fvNkbSBvafkWkoCzisDHM6B20po7W8WWEsv6wc/nrtWHYcrOKsY/oxfOVejurVictOHMDtby1jp2rZAbtPteyLqqBjc/vxA7ry2rWnGMVa2reH9jEaNZ16HZ7uELnPa+rdEzhQWQfdujB+TCcGHzWU9lmZlFbXs6u0mtVFZczZWGy5bnWQUoxkEQfm1ZJNLcbx7tmtK5ec2J/Rw45g+j0TjNHE2eHuZatU27347919Ddk7m9dQkAH3rZOOZtrqlnn8A7ZJIvzmsuO45dHY10uGT/8M4AGl1MXm7/sBlFIPh1tnzJgxKi8vz1E5NBqNpq0jIjH79JMRvbMEGC4iQ0QkG7gG+DgJ+9FoNBpNjDju3lFKNYjIL4AZQCbwilJqrdP70Wg0Gk3sJMWnr5SaBkxLxrY1Go1GEz+eH5Gr0Wg0GufQSl+j0WjSCK30NRqNJo3QSl+j0WjSCK30NRqNJo1wfHBWXEKIlAMbzZ/dgDKHd9Eb2O/wNiE5skJy5PWTrOAvef0kK+h7DPwlbyRZj1FKxVYoRCnl+gfIC5p+IZnbd3i7jsuaLHn9JKvf5PWTrMmS10+y+k3eSLLG8z+86N75JPoinkHLmjz8JK+fZAV/yesnWcEH8npO6SulPH/QAmhZk4ef5PWTrOAvef0kK/hDXq8o/Rd8vn2n8ZO8fpIV/CWvljV5+EneSLLG/D880ZGr0Wg0mtTgFUtfo9FoNCnAt0pfRF4RkX0isiaobaSILBCR1SLyiYh0NdtzRaRaRFaYn+eC1jnVXD5fRJ6W0MrSKZbVnHeyOW+tOb99qmSNVV4RuT7ouK4QkSYRGZUqeWOUtZ2IvGa2rw/UejDnXSIiG01ZpzgtZxyyZovIq2b7ShEZH7ROqq6DwSIyW0TWmdfiL832niLyuYhsNr97mO1iypMvIqtEZHTQtiaby28WkckekPVY87jXisg9IdtK6rUQh6zXm8dztYh8IyIjg7YVu6zJCFtKxQc4BxgNrAlqWwKca07/GPiDOZ0bvFzIdhYD4zDq730GXOqyrFnAKmCk+bsXkJkqWWOVN2S9k4AtHj621wH/Nqc7AtvMayMT2AIMBbKBlcDxLst6O/CqOd0XWApkpPg6GACMNqe7AJuA44HHgClm+xTgUXP6MlMeMeVbZLb3BArM7x7mdA+XZe0LnAb8CbgnaDtJvxbikPXMwPECLg06rnHJ6viFksoPIcocY1BEoJ9iMLDOarmQg78h6Pe1wPMuy3oZ8C83ZY1F3pB1/gz8ycPH9lqMkLosjIfpJlMRnQHMCFr/fuB+l2X9B3BD0HKzgLGpvg5CZP8IuAhjIOWAoPO80Zx+Hrg2aPmN5vwWMoYu54asQcs9QEuln7JrIVZZzfYeQFEisvrWvROGtcAkc/oqjJsowBARWS4ic0XkbLNtIEbh9gCFZlsqCCfrCECJyAwRWSYi95ntbsoKkY9tgB8Ab5vTXjy27wOVwG5gB/AXpdRBU66dQet7QdaVwOUikiUiQ4BTzXmuHFcRyQVOARYB/ZRSu81Ze4BA0d1wxzGlx9emrOHwuqw3Y7xNQZyytjWl/2PgNhFZivHaVGe27waOVEqdAtwFvCVBPnSXCCdrFnAWcL35/V0RucAdEVsQTl4AROR0oEoptcZq5RQTTtaxQCNwBDAEuFtEhrojYjPhZH0F4ybOA54EvsGQPeWISGfgA+BOpdSh4HnKMDE9EwLYlmUVkfMwlP6vEtlvUipnuYVSagMwAUBERgATzfZaoNacXioiWzAs6iJgUNAmBpltrsmKcaPPU0rtN+dNw/AD/8stWaPIG+AaDlv54M1jex0wXSlVD+wTkfnAGAxrKfjNxXVZlVINwP8ElhORbzDcUSWk8LiKSDsMxfSmUuo/ZvNeERmglNotIgOAfWZ7EdbHsQgYH9I+x2VZwxHuP7gqq4icDLyE0X9zIBFZ25SlLyJ9ze8M4LfAc+bvPiKSaU4PBYYDBear1CERGWdGQNyI4V9zTVaM2sIniUhHEckCzsXw87omaxR5A21XA/8OtHn02O4AzjfndcLobNyA0Zk6XESGiEg2xgPsYzdlNc9/J3P6IqBBKZXS68Dc/svAeqXU34JmfQwEInAmB+3/Y+BGMRgHlJnyzgAmiEgPMyJlgtnmpqzhSPq1EKusInIk8B+MPp5NCcuazA6KJHd+vI3htqnHsI5vBn6JYQ1tAh7hcAfZlRi+0xXAMuA7QdsZA6zB6AX/e2Adt2Q1l/+hKe8a4LFUyhqnvOOBhRbb8dSxBToD75nHdh1wb9B2LjOX3wL8xu3jitHhuxFYD3wBHOXCdXAWhothlXnvrDCPUy+MjuXNpmw9zeUFowN6C7AaGBO0rR8D+ebnJg/I2t88B4eAUnO6ayquhThkfQnjDS+wbHCCyphl1SNyNRqNJo1oU+4djUaj0URGK32NRqNJI7TS12g0mjRCK32NRqNJI7TS12g0mjRCK31N2iEi3UXkNnP6CBF5322ZNJpUoUM2NWmHme/kU6XUiW7LotGkmjaVhkGjsckjwDARWYExEOY4pdSJIvIj4AqgE8ao7b9gpKy9ASONx2VKqYMiMgxjEFIfoAr4qTLSKWg0nke7dzTpyBSMvP+jgHtD5p0IfI/DudarlJGobwFGygMw6pLeoZQ6FbgHeCYVQms0TqAtfY2mJbOVUuVAuYiUYeTfByOtwMlmZsQzgffkcMGqnNSLqdHEh1b6Gk1LaoOmm4J+N2HcLxlAqfmWoNH4Du3e0aQj5Ri562NGGXnPt4rIVdBcF3akk8JpNMlEK31N2qGMfOTzxShQ/ngcm7geuFlEVtKy8pVG43l0yKZGo9GkEdrS12g0mjRCK32NRqNJI7TS12g0mjRCK32NRqNJI7TS12g0mjRCK32NRqNJI7TS12g0mjRCK32NRqNJI/4/nU7XgXE+sZEAAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# show sunspot cycle\n",
"daily_sunspots['tot'].plot()\n",
"daily_quakes['mag'].plot()\n"
]
},
{
"cell_type": "markdown",
"id": "e3ee8722",
"metadata": {},
"source": [
"If we wanted to add geomagnetic data we could get it from here: \n",
"https://www.swpc.noaa.gov/products/goes-magnetometer#:~:text=GOES%20magnetometer%20data%20have%20been,during%20geomagnetic%20storms%20and%20substorms.&text=The%20data%20have%20often%20been,decisions%20for%20research%20sounding%20rockets. \n",
"The GOES sats have info from 1996 onwards, but I don't understand the meaning of it!"
]
},
{
"cell_type": "markdown",
"id": "757a9bc6",
"metadata": {},
"source": [
"next stage:\n",
"Build a variable average filter for each/all data sets\n",
"average from 1 hour data to n hours\n",
"correlation function (i.e. dataset a to dataset b)\n",
"variable window + offset function (i.e. compare dataset a, offset 1 week, with dataset b, no offset)\n"
]
},
{
"cell_type": "code",
"execution_count": 26,
"id": "2393d3dc",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x7fe2faa25eb0>]"
]
},
"execution_count": 26,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"#daily_sunspots[\"tot\"][\"1980-01-01\":\"2019-01-01\"].plot()\n",
"#daily_quakes['mag'] = 50 * daily_quakes['mag']\n",
"#daily_quakes['mag'][\"1980-01-01\":\"2019-01-01\"].plot()\n",
"#print(sframe.corrwith(sundf))\n",
"#print(sunframe[0].corrwith(sframe['mag']))\n",
"\n",
"ax = daily_quakes['mag'][\"1975-01-01\":\"2019-01-01\"].plot(title='Sunspots (number) vs Earthquakes (average daily magnitude)')\n",
"#daily_raycount[\"1975\":\"2019\"].plot(ax=ax1)\n",
"\n",
"#ax.plot(daily_quakes['mag'][\"1975\":\"2019\"])\n",
"ax1 = ax.twinx()\n",
"ax1.plot(daily_sunspots[\"tot\"][\"1975-01-01\":\"2019-01-01\"], color='red')"
]
},
{
"cell_type": "code",
"execution_count": 27,
"id": "3606fbb9",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.12402736865827761"
]
},
"execution_count": 27,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# do statistical correlation of sunspots and earthquakes (zero offset)\n",
"daily_sunspots[\"tot\"][\"1975-01-01\":\"2018-01-01\"].corr(daily_quakes['mag'][\"1975-01-01\":\"2018-01-01\"], method='pearson')"
]
},
{
"cell_type": "code",
"execution_count": 28,
"id": "dc1a5805",
"metadata": {},
"outputs": [],
"source": [
"# offset hunter 1 year - we look +/- 180 days either side of the 'day' to see how it changes correlation\n",
"# e.g. if earthquakes happened more frequently 7 days after a sunspot peak, we should see it\n",
"# and if sunspots happen more frequently 15 days after an earthquake, this would show up too\n",
"correl_matrix=[]\n",
"for var_offset in range (-180, 180):\n",
" offset_ds = daily_sunspots[\"tot\"][\"1975-01-01\":\"2018-01-01\"].shift(periods=var_offset)\n",
" #correl_matrix[monthoffset,dayoffset] = daily_quakes['mag'][\"1980-01-01\":\"2019-01-01\"].corr(offset_ds, method='pearson')\n",
" correl_matrix = correl_matrix + [(daily_quakes['mag'][\"1975-01-01\":\"2019-01-01\"].corr(offset_ds, method='pearson'))]\n",
" \n",
" "
]
},
{
"cell_type": "code",
"execution_count": 29,
"id": "d1ea606a",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# Here we plot the general correlation vs offset shift (0 is same day)\n",
"#print(correl_matrix)\n",
"#data = np.array([\n",
"#correl_matrix\n",
"#])\n",
"#x, y = data.T\n",
"offset_range = []\n",
"offset_range.extend(range(-180,180))\n",
"#print(offset_range)\n",
"plot.title(\"Sunspot vs Earthquake Correlation, offset from -180 to +180 days, 1975-2019\")\n",
"plot.xlabel(\"Offset (days)\")\n",
"plot.ylabel(\"Correlation Coef\")\n",
"plot.scatter(offset_range,correl_matrix[:])\n",
"plot.show()"
]
},
{
"cell_type": "code",
"execution_count": 30,
"id": "86f484cd",
"metadata": {},
"outputs": [],
"source": [
"#offset hunter 1985-2010\n",
"# looking for the same thing in a different part of the dataset\n",
"correl_matrix_sm=[]\n",
"for var_offset in range (-180, 180):\n",
" offset_ds = daily_sunspots[\"tot\"][\"1985-01-01\":\"2010-01-01\"].shift(periods=var_offset)\n",
" #correl_matrix[monthoffset,dayoffset] = daily_quakes['mag'][\"1980-01-01\":\"2019-01-01\"].corr(offset_ds, method='pearson')\n",
" correl_matrix_sm = correl_matrix_sm + [(daily_quakes['mag'][\"1985-01-01\":\"2010-01-01\"].corr(offset_ds, method='pearson'))]\n",
" \n",
" "
]
},
{
"cell_type": "code",
"execution_count": 37,
"id": "90901f46",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# plot the different range\n",
"offset_range = []\n",
"offset_range.extend(range(-180,180))\n",
"#print(offset_range)\n",
"plot.title(\"Sunspot vs Earthquake Correlation, offset from -180 to +180 days, 1985-2010\")\n",
"plot.xlabel(\"Offset (days)\")\n",
"plot.ylabel(\"Correlation Coef\")\n",
"plot.scatter(offset_range,correl_matrix_sm[:])\n",
"plot.show()"
]
},
{
"cell_type": "code",
"execution_count": 31,
"id": "b835434d",
"metadata": {},
"outputs": [],
"source": [
"# offset hunter 10k days (takes a long time to run)\n",
"# we also calculate p values, a large p = low statistical/confidence significance\n",
"# a very low p = high confidence interval\n",
"# (we want a high correlation and a low p for something 'useful')\n",
"correl_matrix_smt = []\n",
"corr_p = []\n",
"for var_offset in range (-10000, 10000):\n",
" offset_ds = daily_sunspots[\"tot\"][\"1975\":\"2019\"].shift(periods=var_offset)\n",
" #correl_matrix[monthoffset,dayoffset] = daily_quakes['mag'][\"1980-01-01\":\"2019-01-01\"].corr(offset_ds, method='pearson')\n",
" correl_matrix_smt = correl_matrix_smt + [(daily_quakes['mag'][\"1975\":\"2019\"].corr(offset_ds, method='pearson'))]\n",
" corr_p = corr_p + [(daily_quakes['mag'][\"1975\":\"2019\"].corr(offset_ds, method=pearsonr_pval))] "
]
},
{
"cell_type": "code",
"execution_count": 32,
"id": "78aecb32",
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# plot large scale offsets (correlation and p values)\n",
"offset_range = []\n",
"offset_range.extend(range(-10000,10000))\n",
"#print(offset_range)\n",
"plot.title(\"Sunspot vs Earthquake Correlation, offset from -10000 to +10000 days, 1975-2019\")\n",
"plot.xlabel(\"Offset (days)\")\n",
"plot.ylabel(\"Correlation Coef/p value\")\n",
"plot.scatter(offset_range,correl_matrix_smt[:])\n",
"plot.scatter(offset_range,corr_p[:])\n",
"\n",
"plot.show()"
]
},
{
"cell_type": "code",
"execution_count": 33,
"id": "11548c3d",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Maximum correlation coef = 0.3318872530602409\n",
"Lowest P value = 1.9197353657904475e-235\n",
"Offset for maximum correlation = -5267\n",
"Offset for lowest P value = 5267\n",
"Offset in years = 14.420260095824778\n"
]
}
],
"source": [
"# print a text summary of th emost significant values...\n",
"print(\"Maximum correlation coef =\", max(correl_matrix_smt[:]))\n",
"print(\"Lowest P value = \", min(corr_p[:]))\n",
"print(\"Offset for maximum correlation = \", -correl_matrix_smt.index(max(correl_matrix_smt[:])))\n",
"print(\"Offset for lowest P value = \", corr_p.index(min(corr_p[:])))\n",
"print(\"Offset in years =\", (correl_matrix_smt.index(max(correl_matrix_smt[:]))/365.25))\n",
"#years ago - max historical correlation\n",
"#sunspots from 9 years ago = 35% correlation with high confidence earthquake intensity today..."
]
},
{
"cell_type": "code",
"execution_count": 34,
"id": "ad5d54a7",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"44"
]
},
"execution_count": 34,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# how many stations in the dataset?\n",
"#print(combineddata[21].columns.values)\n",
"#columhead = combineddata[21].columns.values\n",
"len(combineddata)"
]
},
{
"cell_type": "code",
"execution_count": 35,
"id": "e1447ee0",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" AATA\n",
"start_date_time \n",
"2019-01-04 NaN\n",
"2019-01-05 NaN\n",
"2019-01-06 NaN\n",
"2019-01-07 NaN\n",
"2019-01-08 NaN\n",
"... ...\n",
"2019-12-27 3767.550000\n",
"2019-12-28 3763.804167\n",
"2019-12-29 3764.147500\n",
"2019-12-30 3751.696250\n",
"2019-12-31 3769.609583\n",
"\n",
"[362 rows x 1 columns]\n"
]
}
],
"source": [
"# megarayhunter - all stations; run the same thing across them to see if we see differences\n",
"# doesn't work yet! - This is about where I'm at in development.\n",
"correl_matrix_smt=[]\n",
"corr_p =[]\n",
"daily_raycount = []\n",
" \n",
"for station in range(0,43):\n",
" combineddata[station] = combineddata[station].resample(average_interval, origin='1960-01-01').mean()\n",
" #print(combineddata[station])\n",
" daily_raycount.append(combineddata[station])\n",
"print(daily_raycount[0][\"1975\":\"2019\"].shift(periods=10))"
]
},
{
"cell_type": "code",
"execution_count": 37,
"id": "368ce9cc",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" BKSN\n",
"start_date_time \n",
"2009-05-18 NaN\n",
"2009-05-19 NaN\n",
"2009-05-20 NaN\n",
"2009-05-21 NaN\n",
"2009-05-22 NaN\n",
"... ...\n",
"2019-12-27 123.888208\n",
"2019-12-28 123.903042\n",
"2019-12-29 123.562125\n",
"2019-12-30 123.711542\n",
"2019-12-31 123.954917\n",
"\n",
"[3880 rows x 1 columns]\n"
]
}
],
"source": [
"print(daily_raycount[5][\"1975\":\"2019\"].shift(periods=10))"
]
},
{
"cell_type": "code",
"execution_count": 83,
"id": "76526954",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"AATA\n",
"AATB\n",
"APTY\n",
"ARNM\n",
"ATHN\n",
"BKSN\n",
"CALM\n",
"DJON\n",
"DOMB\n",
"DOMC\n",
"DRBS\n",
"FSMT\n",
"HRMS\n",
"INVK\n",
"IRK2\n",
"IRK3\n",
"IRKT\n",
"JBGO\n",
"JUNG\n",
"JUNG1\n",
"KERG\n",
"KIEL\n",
"KIEL2\n",
"LMKS\n",
"MCRL\n",
"MGDN\n",
"MOSC\n",
"MRNY\n",
"MXCO\n",
"NAIN\n",
"NANM\n",
"NEWK\n",
"NRLK\n",
"OULU\n",
"PSNM\n",
"PTFM\n",
"PWNK\n",
"ROME\n",
"SNAE\n",
"SOPB\n",
"SOPO\n",
"TERA\n"
]
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"del offset_ds\n",
"del correl_matrix_smf\n",
"del corr_pf\n",
"dayrange = 30\n",
"day_set_range = []\n",
"day_set_range.extend(range(-dayrange,dayrange))\n",
"\n",
"correl_matrix_smf = [[]]\n",
"corr_pf = [[]]\n",
"offset_ds = []\n",
"cosmic_quake = [[0 for x in range (0,42)] for y in range (-dayrange, dayrange)]\n",
"\n",
"for station in range(0,42): \n",
" print(station_names[station])\n",
" for var_offset in range (-dayrange, dayrange):\n",
" local_offset = []\n",
" local_offset = daily_raycount[station][\"1975\":\"2019\"].shift(periods=var_offset)\n",
" fs = pd.Series(local_offset[station_names[station]])\n",
" #correl_matrix_smf = correl_matrix_smf + \n",
" #print(var_offset, daily_quakes['mag'][\"1975\":\"2019\"].corr(fs, method='pearson'))\n",
" cosmic_quake[station][var_offset] = daily_quakes['mag'][\"1975\":\"2019\"].corr(fs, method='pearson')\n",
" #print(len(cosmic_quake)) \n",
" flagplot = pd.to_numeric(cosmic_quake[station][:], errors='coerce')\n",
" #flagplot.plot()\n",
" #print(len(flagplot[station]))\n",
" #plot.scatter(day_set_range,flagplot)\n",
" plot.plot(flagplot)\n",
" #plot.show()\n",
" #correl_matrix_smf[station] = correl_matrix_smf[station] + daily_quakes['mag'][\"1975\":\"2019\"].corr(fs, method='pearson')\n",
" #print(correl_matrix_smf) \n",
" #correl_matrix_smf[station] = correl_matrix_smf[station]+daily_quakes['mag'][\"1980\":\"2018\"].corr(fs, method='pearson')\n",
" #corr_pf[station] = corr_pf[station] + [daily_quakes['mag'][\"1975\":\"2019\"].corr(fs, method=pearsonr_pval)] \n",
"\n",
"#print('offset', offset_ds[:]) \n",
"#print('daily quakes', daily_quakes['mag'][:])\n",
"#sporkquake = daily_quakes['mag'].to_frame()\n",
"#print(sporkquake)\n",
"#ts = pd.Series(sporkquake['mag'])\n",
"#fs = pd.Series(offset_ds[station_names[1]])\n",
"#print(type(sporkquake.to_series()))\n",
"#print(type(offset_ds.to_series()))\n",
"#print(sporkquake[\"1975\":\"2019\"])\n",
"#print('offset again', offset_ds)\n",
"#print('print ts',ts)\n",
"#print('print fs', fs)\n",
"#print(sporkquake.corr(offset_ds, method='pearson'))\n",
"#correl_matrix_smf = ts[\"1975\":\"2019\"].corr(fs, method='pearson')\n",
"#print(correl_matrix_smf) \n",
"\n",
"#offset_range = []\n",
"#offset_range.extend(range(-10000,10000))\n",
"#print(offset_range)\n",
"\n",
"#plot.scatter(range (-30, 30),cosmic_quake[0][range (-30, 30)])\n",
"#plot.scatter(offset_range,corr_p[:])\n",
"\n",
"#flagplot = pd.to_numeric(cosmic_quake[station], errors='coerce')\n",
"#flagplot.plot()\n",
"#plot.plot(flagplot)\n",
"#plot.show()"
]
},
{
"cell_type": "code",
"execution_count": 146,
"id": "9ad53a96",
"metadata": {},
"outputs": [
{
"ename": "ValueError",
"evalue": "x and y must be the same size",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-146-09681caf96b8>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mplot\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mscatter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0moffset_range\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mcorrel_matrix_smf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"Daily cosmics (THUL) correlated with average daily earthquake score (log-average/24h)\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0mplot\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mscatter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0moffset_range\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mcorr_pf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabel\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\"p value for correlation, (pearson)\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0mplot\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlegend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0mplot\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtitle\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Time shifted correlation between cosmic rays [THUL] and earthquakes'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/matplotlib/pyplot.py\u001b[0m in \u001b[0;36mscatter\u001b[0;34m(x, y, s, c, marker, cmap, norm, vmin, vmax, alpha, linewidths, verts, edgecolors, plotnonfinite, data, **kwargs)\u001b[0m\n\u001b[1;32m 2893\u001b[0m \u001b[0mverts\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mverts\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0medgecolors\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0medgecolors\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2894\u001b[0m \u001b[0mplotnonfinite\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mplotnonfinite\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2895\u001b[0;31m **({\"data\": data} if data is not None else {}), **kwargs)\n\u001b[0m\u001b[1;32m 2896\u001b[0m \u001b[0msci\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0m__ret\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2897\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0m__ret\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/matplotlib/__init__.py\u001b[0m in \u001b[0;36minner\u001b[0;34m(ax, data, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1445\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0minner\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0max\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1446\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mdata\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1447\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0max\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0mmap\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msanitize_sequence\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1448\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1449\u001b[0m \u001b[0mbound\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnew_sig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbind\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0max\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/matplotlib/cbook/deprecation.py\u001b[0m in \u001b[0;36mwrapper\u001b[0;34m(*inner_args, **inner_kwargs)\u001b[0m\n\u001b[1;32m 409\u001b[0m \u001b[0;32melse\u001b[0m \u001b[0mdeprecation_addendum\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 410\u001b[0m **kwargs)\n\u001b[0;32m--> 411\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0minner_args\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0minner_kwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 412\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 413\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mwrapper\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/matplotlib/axes/_axes.py\u001b[0m in \u001b[0;36mscatter\u001b[0;34m(self, x, y, s, c, marker, cmap, norm, vmin, vmax, alpha, linewidths, verts, edgecolors, plotnonfinite, **kwargs)\u001b[0m\n\u001b[1;32m 4439\u001b[0m \u001b[0my\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mma\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mravel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4440\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msize\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msize\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 4441\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"x and y must be the same size\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 4442\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4443\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0ms\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mValueError\u001b[0m: x and y must be the same size"
]
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plot.scatter(offset_range,correl_matrix_smf[:], label=\"Daily cosmics (THUL) correlated with average daily earthquake score (log-average/24h)\")\n",
"plot.scatter(offset_range,corr_pf[:], label = \"p value for correlation, (pearson)\")\n",
"\n",
"plot.legend()\n",
"plot.title('Time shifted correlation between cosmic rays [THUL] and earthquakes')\n",
"plot.xlabel(\"Timeshift (days)\")\n",
"plot.ylabel(\"Correlation and p-value\")\n",
"plot.show()"
]
},
{
"cell_type": "code",
"execution_count": 63,
"id": "552f2fc1",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"-0.356109919072931\n",
"1.9058301817431175e-204\n",
"3993\n",
"3993\n",
"0.21851890422627762\n",
"-5209\n"
]
}
],
"source": [
"print(min(correl_matrix_smf[:]))\n",
"print(min(corr_pf[:]))\n",
"print(10000-correl_matrix_smf.index(min(correl_matrix_smf[:])))\n",
"print(10000-corr_pf.index(min(corr_pf[:])))\n",
"print(max(correl_matrix_smf[:]))\n",
"print(10000-correl_matrix_smf.index(max(correl_matrix_smf[:])))\n"
]
},
{
"cell_type": "code",
"execution_count": 65,
"id": "23024181",
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"correl_matrix_smf = []\n",
"corr_pf = []\n",
"for var_offset in range (-5000, 5000):\n",
" offset_ds = daily_raycount[\"1999\":\"2019\"].shift(periods=var_offset)\n",
" correl_matrix_smf = correl_matrix_smf + [daily_quakes['mag'][\"1999\":\"2019\"].corr(offset_ds['MXCO'], method='pearson')]\n",
" corr_pf = corr_pf + [daily_quakes['mag'][\"1999\":\"2019\"].corr(offset_ds['MXCO'], method=pearsonr_pval)] \n",
"#print(correl_matrix_smt) \n",
"\n",
"offset_range = []\n",
"offset_range.extend(range(-5000,5000))\n",
"#print(offset_range)\n",
"\n",
"plot.scatter(offset_range,correl_matrix_smf[:])\n",
"plot.scatter(offset_range,corr_pf[:])\n",
"\n",
"plot.show()"
]
},
{
"cell_type": "code",
"execution_count": 66,
"id": "9fd372df",
"metadata": {},
"outputs": [],
"source": [
"correl_matrix_smft = []\n",
"corr_pft = []\n",
"for var_offset in range (-10000, 10000):\n",
" offset_ds = daily_raycount[\"1975\":\"2019\"].shift(periods=var_offset)\n",
" correl_matrix_smft = correl_matrix_smft + [sundf[\"tot\"][\"1975\":\"2019\"].corr(offset_ds['MXCO'], method='pearson')]\n",
" corr_pft = corr_pft + [sundf[\"tot\"][\"1975\":\"2019\"].corr(offset_ds['MXCO'], method=pearsonr_pval)] \n",
"#print(correl_matrix_smt) \n",
"\n",
"offset_range = []\n",
"offset_range.extend(range(-10000,10000))\n",
"#print(offset_range)\n"
]
},
{
"cell_type": "code",
"execution_count": 68,
"id": "d247e560",
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"-0.7123943441942397\n",
"8707\n"
]
}
],
"source": [
"\n",
"plot.scatter(offset_range,correl_matrix_smft[:],marker='.', label=\"Daily cosmics (THUL) correlated with daily sunspot count\")\n",
"plot.scatter(offset_range,corr_pft[:], marker='.', label = \"p value for correlation, (pearson)\")\n",
"plot.legend()\n",
"plot.title('Time shifted correlation between cosmic rays and sunspots')\n",
"plot.xlabel(\"Timeshift (days)\")\n",
"plot.ylabel(\"Correlation and p-value\")\n",
"plot.show()\n",
"\n",
"print(min(correl_matrix_smft[:]))\n",
"print(10000-correl_matrix_smft.index(min(correl_matrix_smft[:])))"
]
},
{
"cell_type": "code",
"execution_count": 69,
"id": "a6913936",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<AxesSubplot:title={'center':'Daily earthquakes'}, xlabel='time'>"
]
},
"execution_count": 69,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"daily_quakes['mag'][\"1975\":\"2019\"].plot(title='Daily earthquakes')\n"
]
},
{
"cell_type": "code",
"execution_count": 70,
"id": "e20cd960",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<AxesSubplot:xlabel='time'>"
]
},
"execution_count": 70,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"hour_quakes = sframe_notz.resample('1H', origin='1975-01-01').apply(lambda spl: 10*np.log10(np.mean(np.power(10, spl/10))))\n",
"hour_quakes['mag'][\"1975\":\"2019\"].plot()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "35181e89",
"metadata": {},
"outputs": [],
"source": [
"#morning to do\n",
"#add labels to all plots\n",
"#run for all cosmic ray stations\n",
"#extend seismic data to all events (not just cut off at 4)\n",
"#conduct dimensionless analysis (same thing with delta variable in time from frame-frame)\n",
"#change the timebase for analysis - 1h, 3h, 6h, 12h, 24h, 5d, 7d, 1m\n",
"#quality score for each cosmic ray station (period on, amount of data collected - as a rank)\n",
"#random series test correlation\n"
]
},
{
"cell_type": "code",
"execution_count": 71,
"id": "924ba397",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x12742eaf0>]"
]
},
"execution_count": 71,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"#daily_quakes['mag'] = 1/2 * daily_quakes['mag']\n",
"ax = daily_quakes['mag'][\"1975\":\"2019\"].plot(title='Daily earthquakes')\n",
"#daily_raycount[\"1975\":\"2019\"].plot(ax=ax1)\n",
"\n",
"#ax.plot(daily_quakes['mag'][\"1975\":\"2019\"])\n",
"ax1 = ax.twinx()\n",
"ax1.plot(daily_raycount[\"1975\":\"2019\"], color='red')\n"
]
},
{
"cell_type": "code",
"execution_count": 90,
"id": "e7013e5d",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.collections.PathCollection at 0x17740e0a0>"
]
},
"execution_count": 90,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"#plot at 0 intersection (day/day)\n",
"plot.scatter(daily_quakes['mag'][\"1990\":\"2019\"],daily_raycount[\"1990\":\"2019\"], marker='.',s=0.1, label=\"Daily cosmics (THUL) vs Earthquake magnitude\")\n"
]
},
{
"cell_type": "code",
"execution_count": 89,
"id": "db2de0da",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.collections.PathCollection at 0x16a475cd0>"
]
},
"execution_count": 89,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"#plot at -5000 days intersection\n",
"offset_ds_plot = daily_raycount[\"1990\":\"2019\"].shift(periods=-4913)\n",
"plot.scatter(daily_quakes['mag'][\"1990\":\"2019\"],offset_ds_plot, marker='.', s=0.1,label=\"Daily cosmics (THUL) vs Earthquake magnitude\")\n"
]
},
{
"cell_type": "code",
"execution_count": 87,
"id": "1c56885f",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" MXCO\n",
"start_date_time \n",
"1990-01-01 NaN\n",
"1990-01-02 NaN\n",
"1990-01-03 NaN\n",
"1990-01-04 NaN\n",
"1990-01-05 NaN\n",
"... ...\n",
"2018-12-27 216.433909\n",
"2018-12-28 216.217667\n",
"2018-12-29 215.789875\n",
"2018-12-30 215.544792\n",
"2018-12-31 216.536957\n",
"\n",
"[10592 rows x 1 columns]\n",
"time\n",
"1990-01-01 4.993210\n",
"1990-01-02 4.835273\n",
"1990-01-03 4.509206\n",
"1990-01-04 4.700446\n",
"1990-01-05 4.823279\n",
" ... \n",
"2018-12-27 4.570452\n",
"2018-12-28 4.559079\n",
"2018-12-29 4.673080\n",
"2018-12-30 4.510135\n",
"2018-12-31 4.512682\n",
"Freq: D, Name: mag, Length: 10592, dtype: float64\n"
]
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"#plot at -5000 days intersection (positive correlation - max future)\n",
"offset_ds_plot = daily_raycount[\"1990\":\"2018\"].shift(periods=8882)\n",
"plot.scatter(daily_quakes['mag'][\"1990\":\"2018\"],offset_ds_plot, marker='.',s=0.1, label=\"Daily cosmics (THUL) vs Earthquake magnitude\")\n",
"\n",
"print(offset_ds_plot)\n",
"print(daily_quakes['mag'][\"1990\":\"2018\"])\n"
]
},
{
"cell_type": "code",
"execution_count": 86,
"id": "bfbaf35b",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" MXCO\n",
"start_date_time \n",
"1992-01-01 NaN\n",
"1992-01-02 NaN\n",
"1992-01-03 NaN\n",
"1992-01-04 NaN\n",
"1992-01-05 NaN\n",
"... ...\n",
"2016-12-27 224.173625\n",
"2016-12-28 225.840208\n",
"2016-12-29 226.912375\n",
"2016-12-30 225.899125\n",
"2016-12-31 222.014833\n",
"\n",
"[9132 rows x 1 columns]\n",
" tot sn ss diff\n",
"time \n",
"1992-01-01 240.0 0.0 -240.0 -240.0\n",
"1992-01-02 241.0 39.0 -203.0 -164.0\n",
"1992-01-03 301.0 25.0 -277.0 -251.0\n",
"1992-01-04 310.0 69.0 -241.0 -171.0\n",
"1992-01-05 338.0 85.0 -253.0 -167.0\n",
"... ... ... ... ...\n",
"2016-12-27 27.0 27.0 0.0 27.0\n",
"2016-12-28 11.0 11.0 0.0 11.0\n",
"2016-12-29 11.0 11.0 0.0 11.0\n",
"2016-12-30 11.0 11.0 0.0 11.0\n",
"2016-12-31 41.0 21.0 -21.0 0.0\n",
"\n",
"[9132 rows x 4 columns]\n"
]
},
{
"data": {
"text/plain": [
"<matplotlib.collections.PathCollection at 0x1771fbd60>"
]
},
"execution_count": 86,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"#plot at -5000 days intersection (positive correlation - max future)\n",
"offset_ds_plotf = daily_raycount[\"1992\":\"2016\"].shift(periods=2000)\n",
"print(offset_ds_plotf)\n",
"print(daily_sunspots[\"1992\":\"2016\"])\n",
"plot.scatter(daily_sunspots['tot'][\"1992\":\"2016\"],offset_ds_plotf, marker='.',s=0.1, label=\"Daily cosmics (THUL) vs Earthquake magnitude\")\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "6aceb4dc",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.5"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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