/
DataGraph.py
347 lines (270 loc) · 15.9 KB
/
DataGraph.py
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#!/usr/bin/env python3
from spacedataclasses import *
from mpl_toolkits.mplot3d import Axes3D
from mpl_toolkits.axes_grid1.inset_locator import inset_axes
import spiceypy as spice
from matplotlib.ticker import (MultipleLocator, FormatStrFormatter,
AutoMinorLocator)
def getPosLabels(dataDict,num):
stamp = str(dataDict['DATETIME_ARRAY'][min(range(len(dataDict['TIME_ARRAY'])), key=lambda j: abs(dataDict['TIME_ARRAY'][j]-num))])
position, lighttime = spice.spkpos('JUNO',spice.utc2et(stamp),'IAU_JUPITER','NONE','JUPITER')
vectorPos = spice.vpack(position[0],position[1],position[2])
radii,longitude,latitude = spice.reclat(vectorPos)
lat = f'{round(latitude*spice.dpr(),2)}$^o$ Lat'
dist = f'{round(radii/69911,3)} $R_j$'
return lat,dist
def finalGraph(start_time, end_time, heating_rate_graph = True, save_loc = r'/data/Python/jupiter/figures/orbit'): #This is the final graph function I use
startTime = datetime.datetime.now()
timeStart = start_time
timeEnd = end_time
orbitsData = {1:'2016-07-31T19:46:02',
2:'2016-09-23T03:44:48',
3:'2016-11-15T05:36:45',
4:'2017-01-07T03:11:30',
5:'2017-02-28T22:55:48',
6:'2017-04-22T19:14:57',
7:'2017-06-14T15:58:35',
8:'2017-08-06T11:44:04',
9:'2017-09-28T07:51:01',
10:'2017-11-20T05:57:23',
11:'2018-01-12T03:52:42',
12:'2018-03-05T23:55:41'}
dataFolder = pathlib.Path('/data/Python/jupiter/data/jad')
DOY,ISO,datFiles = getFiles(timeStart,timeEnd,'.DAT',dataFolder,'JAD_L30_LRS_ION_ANY_CNT')
jadeIon = JadeData(datFiles,timeStart,timeEnd)
jadeIon.getIonData()
print(f'Ion Data Pulled')
if heating_rate_graph is False:
dataFolder = pathlib.Path('/data/Python/jupiter/data/fgm')
DOY,ISO,csvFiles = getFiles(timeStart,timeEnd,'.csv',dataFolder,'fgm_jno_l3')
q = FGMData(csvFiles,timeStart,timeEnd)
print('Mag Data Pulled')
elif heating_rate_graph is True:
dataFolder = pathlib.Path('/data/Python/jupiter/data/fgm')
DOY,ISO,csvFiles = getFiles(timeStart,timeEnd,'.csv',dataFolder,'fgm_jno_l3')
q = turbulence(ISO,csvFiles,timeStart,timeEnd,1,60,1800,'.')
print(f'Mag/Flux Data Pulled')
dataFolder = pathlib.Path('/data/Python/jupiter/data/jad')
DOY,ISO,datFiles = getFiles(timeStart,timeEnd,'.DAT',dataFolder,'JAD_L30_LRS_ELC_ANY_CNT')
jadeElec = JadeData(datFiles,timeStart,timeEnd)
jadeElec.getElecData()
print(f'Electron Data Pulled')
metaKernel = 'juno_2019_v03.tm'
spice.furnsh(metaKernel)
print(f'Spice Kernel loaded')
for date in ISO:
fgmStart = 0
jadIonStart = 0
jadElecStart = 0
qStart = 0
for i in range(1,5):
if heating_rate_graph is True:
fig, (ax1,ax2,ax3,ax4) = plt.subplots(4,1,sharex=True,figsize=(10,4))
elif heating_rate_graph is False:
fig, (ax1,ax2,ax4) = plt.subplots(3,1,sharex=True,figsize=(10,4))
latLabels, distLabels = [],[]
if date not in jadeIon.dataDict.keys() and date not in q.dataDict.keys():
continue
if date in jadeIon.dataDict.keys(): #Ion spectrogram portion
jadeIonData = jadeIon.dataDict[date]
jadIonIndex = min(range(len(jadeIonData['TIME_ARRAY'])), key=lambda j: abs(jadeIonData['TIME_ARRAY'][j]-i*6))
spec = ax1.imshow(np.transpose(jadeIonData['DATA_ARRAY'][jadIonStart:jadIonIndex+1]),origin='lower',aspect='auto',cmap='jet',extent=((i-1)*6,i*6,0,64))
axins = inset_axes(ax1,
width="2%", # width = 5% of parent_bbox width
height="100%", # height : 50%
loc='center right',
bbox_to_anchor=(0.04, 0, 1, 1),
bbox_transform=ax1.transAxes,
borderpad=0,
)
cbr = plt.colorbar(spec,cax=axins)
cbr.set_label('log(Counts/sec)',rotation=270, labelpad=10, size=9)
dimData = np.array(jadeIonData['DIM1_ARRAY'])/1000
ticks = [0.1,1,10]
tickList = []
dataTicks = []
for ticknum in ticks:
tick = min(range(len(dimData)), key=lambda j: abs(dimData[j]-ticknum))
tickList.append(tick)
dataTicks.append(dimData[tick])
ax1.set_yticks(tickList)
ax1.set_yticklabels(np.round(dataTicks,1),fontsize=9)
ax1.set_ylabel('Ion E (eV/q)',size=9)
ax1.yaxis.set_label_coords(-0.09,0.5)
jadIonStart = jadIonIndex
ax1.set_title(date)
if date in jadeElec.dataDict.keys(): #Electron spectrogram portion
jadeElecData = jadeElec.dataDict[date]
jadElecIndex = min(range(len(jadeElecData['TIME_ARRAY'])), key=lambda j: abs(jadeElecData['TIME_ARRAY'][j]-i*6))
elecspec = ax2.imshow(np.transpose(jadeElecData['DATA_ARRAY'][jadElecStart:jadElecIndex+1]),origin='lower',aspect='auto',cmap='jet',extent=((i-1)*6,i*6,0,64))
jadElecStart = jadElecIndex
axins = inset_axes(ax2,
width="2%", # width = 5% of parent_bbox width
height="100%", # height : 50%
loc='center right',
bbox_to_anchor=(0.04, 0, 1, 1),
bbox_transform=ax2.transAxes,
borderpad=0,
)
cbr = plt.colorbar(elecspec,cax=axins)
cbr.set_label('log(Counts/sec)',rotation=270, labelpad=10, size=9)
dimData = np.array(jadeElecData['DIM1_ARRAY'])/1000
ticks = [0.1,1,10]
tickList = []
dataTicks = []
for ticknum in ticks:
tick = min(range(len(dimData)), key=lambda j: abs(dimData[j]-ticknum))
tickList.append(tick)
dataTicks.append(dimData[tick])
ax2.set_yticks(tickList)
ax2.set_yticklabels(np.round(dataTicks,1),fontsize=9)
ax2.set_ylabel('Elec E (keV)',size=9)
ax2.yaxis.set_label_coords(-0.09,0.5)
if heating_rate_graph is True:
if date in q.dataDict.keys(): #Graphing heating rate Density
qData = q.dataDict[date]
qEndIndex = min(range(len(qData['QTIME_ARRAY'])), key=lambda j: abs(qData['QTIME_ARRAY'][j]-i*6))
timeloop = qData['QTIME_ARRAY'][qStart:qEndIndex+1] #extracts time from time array to fit within 6 hr window
timeplot = np.linspace((i-1)*6,i*6,len(timeloop))
qloop = qData['Q_ARRAY'][qStart:qEndIndex+1] #extracts q from q array to correspond to the time
#ax3.plot(timeplot,qloop,'b')
for k in range(len(qloop)-1):
ax3.plot((timeplot[k],timeplot[k+1]),(qloop[k],qloop[k]),'b') #loop used to produce seperate horizontal lines for each value q
ax3.set_yscale('log')
ax3.set_ylabel('Q [W/$m^2$]',size=9)
ax3.yaxis.set_label_coords(-0.09,0.5)
ax3.tick_params(axis='y',labelsize=9)
ax3.set_ylim(10e-18,10e-12)
qStart = qEndIndex
fgmEndIndex = min(range(len(qData['TIME_ARRAY'])), key=lambda j: abs(qData['TIME_ARRAY'][j]-i*6))
ax4.plot(qData['TIME_ARRAY'][fgmStart:fgmEndIndex+1],qData['BX'][fgmStart:fgmEndIndex+1],label='$B_x$',linewidth=1)
ax4.plot(qData['TIME_ARRAY'][fgmStart:fgmEndIndex+1],qData['BY'][fgmStart:fgmEndIndex+1],label='$B_y$',linewidth=1)
ax4.plot(qData['TIME_ARRAY'][fgmStart:fgmEndIndex+1],qData['BZ'][fgmStart:fgmEndIndex+1],label='$B_z$',linewidth=1)
ax4.plot(qData['TIME_ARRAY'][fgmStart:fgmEndIndex+1],qData['B'][fgmStart:fgmEndIndex+1],'black',label='$^+_-|B|$',linewidth=0.5)
ax4.plot(qData['TIME_ARRAY'][fgmStart:fgmEndIndex+1],-np.array(qData['B'][fgmStart:fgmEndIndex+1]),'black',linewidth=0.5)
ax4.legend(loc=(1.01,0.07),prop={'size': 9})
ax4.set_xlabel('Hrs')
ax4.xaxis.set_label_coords(1.04,-0.07)
ax4.set_ylabel('|B| (nT)',size=9)
ax4.yaxis.set_label_coords(-0.09,0.5)
ax4.tick_params(axis='y',labelsize=9)
fgmStart = fgmEndIndex
if heating_rate_graph is False:
if date in q.dataDict.keys(): #Graphing heating rate Density
qData = q.dataDict[date]
fgmEndIndex = min(range(len(qData['TIME_ARRAY'])), key=lambda j: abs(qData['TIME_ARRAY'][j]-i*6))
ax4.plot(qData['TIME_ARRAY'][fgmStart:fgmEndIndex+1],qData['BX'][fgmStart:fgmEndIndex+1],label='$B_x$',linewidth=1)
ax4.plot(qData['TIME_ARRAY'][fgmStart:fgmEndIndex+1],qData['BY'][fgmStart:fgmEndIndex+1],label='$B_y$',linewidth=1)
ax4.plot(qData['TIME_ARRAY'][fgmStart:fgmEndIndex+1],qData['BZ'][fgmStart:fgmEndIndex+1],label='$B_z$',linewidth=1)
ax4.plot(qData['TIME_ARRAY'][fgmStart:fgmEndIndex+1],qData['B'][fgmStart:fgmEndIndex+1],'black',label='$^+_-|B|$',linewidth=0.5)
ax4.plot(qData['TIME_ARRAY'][fgmStart:fgmEndIndex+1],-np.array(qData['B'][fgmStart:fgmEndIndex+1]),'black',linewidth=0.5)
ax4.legend(loc=(1.01,0.07),prop={'size': 9})
ax4.set_xlabel('Hrs')
ax4.xaxis.set_label_coords(1.04,-0.07)
ax4.set_ylabel('|B| (nT)',size=9)
ax4.yaxis.set_label_coords(-0.09,0.5)
ax4.tick_params(axis='y',labelsize=9)
fgmStart = fgmEndIndex
if date in q.dataDict.keys(): #Positional labels portion
if i == 1:
for num in range(0,7):
lat, dist = getPosLabels(q.dataDict[date],num)
latLabels.append(lat)
distLabels.append(dist)
elif i == 2:
for num in range(6,13):
lat, dist = getPosLabels(q.dataDict[date],num)
latLabels.append(lat)
distLabels.append(dist)
elif i == 3:
for num in range(12,19):
lat, dist = getPosLabels(q.dataDict[date],num)
latLabels.append(lat)
distLabels.append(dist)
elif i == 4:
for num in range(18,25):
lat, dist = getPosLabels(q.dataDict[date],num)
latLabels.append(lat)
distLabels.append(dist)
elif date in jadeIon.dataDict[date]:
if i == 1:
for num in range(0,7):
lat, dist = getPosLabels(jadeIon.dataDict[date],num)
latLabels.append(lat)
distLabels.append(dist)
elif i == 2:
for num in range(6,13):
lat, dist = getPosLabels(jadeIon.dataDict[date],num)
latLabels.append(lat)
distLabels.append(dist)
elif i == 3:
for num in range(12,19):
lat, dist = getPosLabels(jadeIon.dataDict[date],num)
latLabels.append(lat)
distLabels.append(dist)
elif i == 4:
for num in range(18,25):
lat, dist = getPosLabels(jadeIon.dataDict[date],num)
latLabels.append(lat)
distLabels.append(dist)
ax5 = ax4.twiny()
ax6 = ax5.twiny()
ax5.set_xticks([0,1,2,3,4,5,6])
ax5.set_xticklabels(latLabels)
ax5.xaxis.set_ticks_position('bottom')
ax5.tick_params(axis='both',which='both',length=0,pad = 20)
ax6.set_xticks([0,1,2,3,4,5,6])
ax6.set_xticklabels(distLabels)
ax6.xaxis.set_ticks_position('bottom')
ax6.tick_params(axis='both',which='both',length=0,pad = 33)
for orbit in range(1,len(orbitsData)+1):
orbitStart = datetime.datetime.fromisoformat(orbitsData[orbit]).date()
orbitEnd = datetime.datetime.fromisoformat(orbitsData[orbit+1]).date()
currDate = datetime.datetime.fromisoformat(date).date()
if orbitStart <= currDate and orbitEnd > currDate:
orbitNum = orbit
break
YDOY = datetime.date.fromisoformat(date).strftime('%Y%j')
timeFormatDict = {1:'0000',2:'0600',3:'1200',4:'1800'}
fileSaveName = f'jad_fgm_{YDOY}_{timeFormatDict[i]}.png'
is_dir = os.path.isdir(f'{save_loc}/orbit{orbitNum}')
if not is_dir:
os.makedirs(f'{save_loc}/orbit{orbitNum}')
plt.savefig(pathlib.Path(f'{save_loc}/orbit{orbitNum}/{fileSaveName}'),bbox_inches='tight',pad_inches=0.02,dpi=150)
plt.close(fig)
print(f'Graphs for {date} created to {save_loc}/orbit{orbitNum}/{fileSaveName}')
endTime = datetime.datetime.now()
print(f"Time passed = {endTime-startTime}")
def testFunc():
timeStart = '2017-03-09T00:00:00'
timeEnd = '2017-03-09T23:59:59'
orbitsData = {1:'2016-07-31T19:46:02',
2:'2016-09-23T03:44:48',
3:'2016-11-15T05:36:45',
4:'2017-01-07T03:11:30',
5:'2017-02-28T22:55:48',
6:'2017-04-22T19:14:57'}
dataFolder = pathlib.Path('../data/fgm')
DOY,ISO,csvFiles = getFiles(timeStart,timeEnd,'.csv',dataFolder,'fgm_jno_l3')
q = turbulence(ISO,csvFiles,timeStart,timeEnd,1,60,1800,'.')
for date in ISO:
qStart = 0
for i in range(1,5):
fig,ax3=plt.subplots()
qData = q.dataDict[date]
qEndIndex = min(range(len(qData['QTIME_ARRAY'])), key=lambda j: abs(qData['QTIME_ARRAY'][j]-i*6))
timeloop = qData['QTIME_ARRAY'][qStart:qEndIndex+1] #extracts time from time array to fit within 6 hr window
timeplot = np.linspace((i-1)*6,i*6,len(timeloop))
qloop = qData['Q_ARRAY'][qStart:qEndIndex+1] #extracts q from q array to correspond to the time
#ax3.plot(test,qloop,'b')
for k in range(len(qloop)-1):
ax3.plot((timeplot[k],timeplot[k+1]),(qloop[k],qloop[k]),'b') #loop used to produce seperate horizontal lines for each value q
ax3.set_yscale('log')
ax3.set_ylabel('mean heating rate density [W/$m^2$]')
qStart = qEndIndex
plt.show()
if __name__ == '__main__':
timeStart = '2017-06-01T00:00:00'
timeEnd = '2017-06-02T03:52:42'
save_location = r'/home/aschok/Documents/testfigures'
finalGraph(timeStart,timeEnd,heating_rate_graph=False,save_loc=save_location)