def targetGrid(gridParam, minimizedVisitParams, plot=True):
'''
The grid tests against ranging effective temperatures for both stars and the flux ratio of the
secondary component. This is done by target.
:param gridParam: [in/out] The GridParam of the target
:param gridRes: [out] The visits that have the same paramters as the minimized chi2 visit
:param plot: [in] If true makes plots to see intermediate steps (default=True)
'''
locationID = gridParam.locationID
apogeeID = gridParam.apogeeID
badheader, header = apread.apStar(locationID, apogeeID, ext=0, header=True)
specs = apread.apStar(locationID, apogeeID, ext=1, header=False)
specerrs = apread.apStar(locationID, apogeeID, ext=2, header=False)
nvisits = header['NVISITS']
# chi2 = np.full((nvisits, nrangeTeffA, nrangeTeffB, nrangeFluxRatio), -1.)
#chi2 = np.full((nvisits, nrangeTeffA, nrangeTeffB, nrangeFluxRatio, nrangeRVA, nrangeRVB), -1.)
ipg = ferre.Interpolator(lib='GK')
ipf = ferre.Interpolator(lib='F')
# Create file to store all the chi2 values
path = 'lists/all_chi2/' + str(locationID) + '/'
if not os.path.exists(path):
os.makedirs(path)
fn = open(path + apogeeID + '.lis', 'w')
fn.write(gridParam.toStringHeader())
timer = Timer()
timeSum = 0.0
allChi2 = []
visitGridParamsBuffer = []
for visit in range(1, nvisits + 1):
timer.start()
if (nvisits != 1):
spec = specs[1+visit]
specerr = specerrs[1+visit]
else:
spec = specs
specerr = specerrs
if (len(minimizedVisitParams) == 0):
gridParam = GridParam(locationID, apogeeID)
gridParam.constructParams()
gridParam.getRVs(visit)
else:
gridParam = minimizedVisitParams[visit - 1]
visitGridParamsBuffer.append(gridParam)
# Prepare grid ranges
rangeTeffA = np.arange(gridParam.minTeffA, gridParam.maxTeffA, gridParam.teffStepA)
rangeTeffB = np.arange(gridParam.minTeffB, gridParam.maxTeffB, gridParam.teffStepB)
rangeFluxRatio = np.arange(gridParam.minFluxRatio, gridParam.maxFluxRatio, gridParam.fluxStep)
rangeRVA = np.arange(gridParam.minRVA, gridParam.maxRVA, gridParam.rvAStep)
rangeRVB = np.arange(gridParam.minRVB, gridParam.maxRVB, gridParam.rvBStep)
nrangeTeffA = len(rangeTeffA)
nrangeTeffB = len(rangeTeffB)
nrangeFluxRatio = len(rangeFluxRatio)
nrangeRVA =len(rangeRVA)
nrangeRVB =len(rangeRVB)
chi2 = np.full((nrangeTeffA, nrangeTeffB, nrangeFluxRatio, nrangeRVA, nrangeRVB), -1.)
print('Visit: ' + str(visit) ,'Grid dimensions: ' + str(chi2.shape))
# Prep Spectra
aspec= np.reshape(spec,(1, len(spec)))
aspecerr= np.reshape(specerr,(1, len(specerr)))
cont= spec / continuum.fit(aspec, aspecerr, type='aspcap')[0]
conterr = specerr / continuum.fit(aspec, aspecerr, type='aspcap')[0]
shiftedSpec = bm.shiftFlux(cont, header['VHELIO' + str(visit)])
# Run grid
for i in range(nrangeTeffA):
gridParam.modelParamA.teff = rangeTeffA[i]
componentA = bm.genComponent(gridParam.modelParamA, ipf, ipg)
for j in range(nrangeTeffB):
gridParam.modelParamB.teff = rangeTeffB[j]
componentB = bm.genComponent(gridParam.modelParamB, ipf, ipg)
for k in range(nrangeFluxRatio):
gridParam.modelParamB.fluxRatio = rangeFluxRatio[k]
componentBR = componentB * rangeFluxRatio[k]
for l in range(nrangeRVA):
gridParam.modelParamA.rv = rangeRVA[l]
componentAS = bm.shiftFlux(componentA, rangeRVA[l])
for m in range(nrangeRVB):
gridParam.modelParamB.rv = rangeRVB[m]
componentBS = bm.shiftFlux(componentBR, rangeRVB[m])
binaryFlux = bm.combineFlux(componentAS, componentBS)
chi2[i][j][k][l][m] = calcChi2(binaryFlux, shiftedSpec, conterr) / (len(binaryFlux) - 5.0)
gridParam.chi2 = chi2[i][j][k][l][m]
fn.write(gridParam.toString())
if (plot is True):
restLambda = splot.apStarWavegrid()
BinPlot.plotDeltaVCheck(locationID, apogeeID, visit,
[ [ restLambda, binaryFlux, 'blue', 'model' ],
[ restLambda, cont, 'orange', 'unshifted' ],
[ restLambda, shiftedSpec, 'green', 'shifted' ]],
[gridParam.modelParamA.teff,gridParam.modelParamB.teff, gridParam.modelParamB.fluxRatio],
'Delta V Shift', folder='grid_deltaVCheck')
timeSum+=timer.end()
allChi2.append(chi2)
fn.close()
print('Average visit time: ' + str(round(timeSum/nvisits, 2)) + str('s'))
# Get minized values for each visit
indices = None
for i in range(nvisits):
inds = getMinIndicies(allChi2[i])
rangeTeffA = np.arange(visitGridParamsBuffer[i].minTeffA, visitGridParamsBuffer[i].maxTeffA, visitGridParamsBuffer[i].teffStepA)
rangeTeffB = np.arange(visitGridParamsBuffer[i].minTeffB, visitGridParamsBuffer[i].maxTeffB, visitGridParamsBuffer[i].teffStepB)
rangeFluxRatio = np.arange(visitGridParamsBuffer[i].minFluxRatio, visitGridParamsBuffer[i].maxFluxRatio, visitGridParamsBuffer[i].fluxStep)
rangeRVA = np.arange(visitGridParamsBuffer[i].minRVA, visitGridParamsBuffer[i].maxRVA, visitGridParamsBuffer[i].rvAStep)
rangeRVB = np.arange(visitGridParamsBuffer[i].minRVB, visitGridParamsBuffer[i].maxRVB, visitGridParamsBuffer[i].rvBStep)
nrangeTeffA = len(rangeTeffA)
nrangeTeffB = len(rangeTeffB)
nrangeFluxRatio = len(rangeFluxRatio)
nrangeRVA =len(rangeRVA)
nrangeRVB =len(rangeRVB)
visitGridParamsBuffer[i].setParams(i + 1, rangeTeffA[inds[0]], rangeTeffB[inds[1]], rangeFluxRatio[inds[2]],
rangeRVA[inds[3]], rangeRVB[inds[4]], allChi2[i][inds[0]][inds[1]][inds[2]][inds[3]][inds[4]])
if (indices is None):
indices = [i + 1, inds, allChi2[i][inds[0]][inds[1]][inds[2]][inds[3]][inds[4]]]
if (allChi2[i][inds[0]][inds[1]][inds[2]][inds[3]][inds[4]] < indices[2]):
indices = [i + 1, inds, allChi2[i][inds[0]][inds[1]][inds[2]][inds[3]][inds[4]]]
inds = getMinIndicies(allChi2)
gridParam = visitGridParamsBuffer[inds[0]]
return gridParam, visitGridParamsBuffer
def runTarget(gridParam):
locationID = gridParam.locationID
apogeeID = gridParam.apogeeID
badheader, header = apread.apStar(locationID, apogeeID, ext=0, header=True, dr='13')
specs = apread.apStar(locationID, apogeeID, ext=1, header=False, dr='13')
specerrs = apread.apStar(locationID, apogeeID, ext=2, header=False, dr='13')
nvisits = header['NVISITS']
gridParamVists = []
for visit in range(1, nvisits + 1):
print('Visit ' + str(visit) + '/' + str(nvisits))
if nvisits is 1:
spec = specs
specerr = specerrs
else:
spec = specs[1 + nvisits]
specerr = specerrs[ 1+ nvisits]
aspec= np.reshape(spec,(1, len(spec)))
aspecerr= np.reshape(specerr,(1, len(specerr)))
cont= spec / continuum.fit(aspec, aspecerr, type='aspcap')[0]
conterr = specerr / continuum.fit(aspec, aspecerr, type='aspcap')[0]
gridParam = GridParam(locationID, apogeeID)
gridParam.constructParams()
gridParam.spec = bm.shiftFlux(cont, header['VHELIO' + str(visit)])
gridParam.specErr = bm.shiftFlux(conterr, header['VHELIO' + str(visit)])
gridParam.getRVs(visit)
gridParam.visit = visit
nSteps = 200
sampler = MCMC(gridParam, nSteps=nSteps)
circular_samples = sampler.chain[:, :, :].reshape((-1, 5))
results = np.asarray(list(map(lambda v: (v[1], v[2]-v[1], v[1]-v[0]),
zip(*np.percentile(circular_samples, [16, 50, 84], axis=0)))))
fig, ax = plt.subplots(5, 1, sharex='col')
for i in range(5):
for j in range(len(sampler.chain[:, 0, i])):
ax[i].plot(np.linspace(0, nSteps, num=nSteps), sampler.chain[j, :, i], 'k', alpha=0.2)
ax[i].plot(np.linspace(0, nSteps, num=nSteps) , np.ones(nSteps)*results[i][0], 'b', lw=2)
fig.set_figheight(20)
fig.set_figwidth(15)
if not os.path.exists('plots/walker/' + str(locationID) + '/' + str(apogeeID) + '/'):
os.makedirs('plots/walker/' + str(locationID) + '/' + str(apogeeID) + '/')
plt.savefig('plots/walker/' + str(locationID) + '/' + str(apogeeID) + '/' + str(visit) + '.png')
plt.close('all')
gridParam.modelParamA.teff = results[0][0]
gridParam.modelParamB.teff = results[1][0]
gridParam.modelParamB.fluxRatio = results[2][0]
gridParam.modelParamA.rv = results[3][0]
gridParam.modelParamB.rv = results[4][0]
gridParam.chi2 = -1.0 * fitModel(None, gridParam, plot=True)
gridParamVists.append(gridParam)
if not os.path.exists('lists/chi2/' + str(locationID) + '/'):
os.makedirs('lists/chi2/' + str(locationID) + '/')
filename = 'lists/chi2/' + str(locationID) + '/' + str(apogeeID) + '.tbl'
writeGridToFile(gridParamVists, filename=filename)
import matplotlib.pyplot as plt
import BinModelGen as bm
import BinPlot
from BinaryGrid import calcChi2
from GridParam import GridParam
from Timer import Timer
locationID = 4586
apogeeID = "2M03441568+3231282"
restLambda = splot.apStarWavegrid()
visit = 1
badheader, header = apread.apStar(locationID, apogeeID, ext=0, header=True)
gridParam = GridParam(locationID, apogeeID)
gridParam.constructParams()
spec = apread.apStar(locationID, apogeeID, ext=1, header=False)[1 + visit]
specerr = apread.apStar(locationID, apogeeID, ext=2, header=False)[1 + visit]
# plt.plot(restLambda, spec)
aspec = np.reshape(spec, (1, len(spec)))
aspecerr = np.reshape(specerr, (1, len(specerr)))
cont = spec / continuum.fit(aspec, aspecerr, type="aspcap")[0]
conterr = specerr / continuum.fit(aspec, aspecerr, type="aspcap")[0]
shiftedSpec = bm.shiftFlux(cont, header["VHELIO" + str(visit)])
conterr = bm.shiftFlux(cont, header["VHELIO" + str(visit)])
BinPlot.plotDeltaVCheck(
locationID,
apogeeID,
