## for Palatino and other serif fonts use:
mpl.rc('font', **{'family': 'serif'})
mpl.rc('text', usetex=True)
# Define labels
labels = [r"$m_{\star}$", r"$f_{sat}$", r"$t_{sat}$", r"age", r"$\beta_{XUV}$"]
# Containers
nIters = 7
zscores = np.zeros((nIters - 1, 5))
for ii in range(1, nIters):
# Load ii-1th approxposterior output
approxFilenamePrev = "../../Data/apRun%d.h5" % (ii - 1)
approxChainPrev = extractMCMCResults(approxFilenamePrev,
blobsExist=False,
burn=500,
verbose=False)
# Load iith approxposterior output
approxFilename = "../../Data/apRun%d.h5" % ii
approxChain = extractMCMCResults(approxFilename,
blobsExist=False,
burn=500,
verbose=False)
# Loop over variables
for jj in range(len(labels)):
# Compute relative difference between marginal distribution medians
zscores[ii - 1, jj] = np.fabs(
(np.mean(approxChain[:, jj]) -
np.mean(approxChainPrev[:, jj]))) / np.std(approxChainPrev[:, jj])
#Typical plot parameters that make for pretty plots
mpl.rcParams['font.size'] = 12.0
## for Palatino and other serif fonts use:
mpl.rc('font', **{'family': 'serif'})
mpl.rc('text', usetex=True)
# CGS constants
MSUN = 1.988435e33 # mass of Sun in grams
RSUN = 6.957e10 # radius of Sun incm
RHOSUN = MSUN / (4. / 3. * np.pi * RSUN**3) # density of sun in g/cm^3
# Read in evolutionary tracks
chains = mcmcUtils.extractMCMCResults("../../Data/trappist1Fiducial.h5",
verbose=False,
applyBurnin=True,
thinChains=True,
blobsExist=False)
# Draw num samples
num = int(1.0e5) # Number of samples
# Draw mass samples with replacement in grams
masses = np.random.choice(chains[:, 0], size=(num, ), replace=True) * MSUN
# Draw density samples in g/cm^3 by approximating constraint as wide gaussian
rhos = norm.rvs(loc=51.1, scale=2.4, size=(num, )) * RHOSUN
# Compute radius via density equation: rho = M/V = M/(4/3 * pi * r^3)
# -> (rho/m * (4/3) * pi)^(1/3) = r, but convert to Rsun
rads = np.power(masses / (rhos * (4. / 3.) * np.pi), 1. / 3.) / RSUN
# Get the input files, save them as strings
with open(os.path.join(PATH, "star.in"), 'r') as f:
star_in = f.read()
kwargs["STARIN"] = star_in
with open(os.path.join(PATH, "vpl.in"), 'r') as f:
vpl_in = f.read()
kwargs["VPLIN"] = vpl_in
# Check for output dir, make it if it doesn't already exist
if not os.path.exists(os.path.join(PATH, "output")):
os.makedirs(os.path.join(PATH, "output"))
# Draw nsmaples from the posterior distributions
samples = mcmcUtils.extractMCMCResults(dataDir,
blobsExist=False,
burn=500,
removeRogueChains=True)
# Get random initial conditions from posterior
sampleInds = np.random.choice(np.arange(len(samples)),
size=nsamples,
replace=True)
# Containers
lum = []
lumXUV = []
radius = []
temp = []
time = []
ii = 0
#Typical plot parameters that make for pretty plots
mpl.rcParams['figure.figsize'] = (9, 8)
mpl.rcParams['font.size'] = 22.0
## for Palatino and other serif fonts use:
mpl.rc('font', **{'family': 'serif'})
mpl.rc('text', usetex=True)
# Read in evolutionary tracks
data = np.load("../../Data/trappist1StarEvol.npz")
nsamples = len(data["Luminosity"])
chains, blobs = mcmcUtils.extractMCMCResults("../../Data/trappist1Fiducial.h5",
verbose=True,
burn=500,
thinChains=True,
blobsExist=True)
### Plot Lum, LumXUV, radius evolution and compare to observations ###
fig, axes = plt.subplots(ncols=3, figsize=(21, 6))
for ii in range(nsamples):
# Left: lum
axes[0].plot(data["time"][ii],
data["Luminosity"][ii],
alpha=0.1,
color="k",
lw=2,
#Typical plot parameters that make for pretty plots
mpl.rcParams['font.size'] = 17
## for Palatino and other serif fonts use:
mpl.rc('font',**{'family':'serif'})
mpl.rc('text', usetex=True)
# Plot points selected by approxposterior?
plotAPPoints = False
# Path to data
filename = "../../Data/convergedAP.h5"
# Extract data
samples = extractMCMCResults(filename, blobsExist=False, burn=500,
thinChains=True, removeRogueChains=False)
labels = [r"$m_{\star}$ [M$_{\odot}$]", r"$f_{sat}$",
r"$t_{sat}$ [Gyr]", r"Age [Gyr]", r"$\beta_{XUV}$"]
# Output constraints
for ii in range(samples.shape[-1]):
med = np.median(samples[:,ii])
plus = np.percentile(samples[:,ii], 84) - med
minus = med - np.percentile(samples[:,ii], 16)
print("%s = %e + %e - %e" % (labels[ii], med, plus, minus))
print()
# Scale Mass for readability
samples[:,0] = samples[:,0] * 1.0e2
#Typical plot parameters that make for pretty plots
mpl.rcParams['font.size'] = 17.5
## for Palatino and other serif fonts use:
mpl.rc('font',**{'family':'serif'})
mpl.rc('text', usetex=True)
# Path to data
filename = "../../Data/trappist1FiducialRatio.h5"
approxFilename = "../../Data/convergedAP.h5"
# Whether or not to plot blobs
# Extract true MCMC results
print("Loading true MCMC chain...")
trueChain = extractMCMCResults(filename, blobsExist=False, burn=500,
verbose=False, thinChains=False)
# Extract approxposterior MCMC results
print("Loading approxposterior MCMC chain...")
approxChain = extractMCMCResults(approxFilename, blobsExist=False, burn=500,
verbose=False, thinChains=False)
# Define labels
labels = [r"$m_{\star}$ [M$_{\odot}$]", r"$f_{sat}$",
r"$t_{sat}$ [Gyr]", r"Age [Gyr]", r"$\beta_{XUV}$"]
# Scale Mass for readability
trueChain[:,0] = trueChain[:,0] * 1.0e2
approxChain[:,0] = approxChain[:,0] * 1.0e2
# Estimate probability that TRAPPIST-1 is still saturated at the age of the
mpl.rcParams['font.size'] = 17
## for Palatino and other serif fonts use:
mpl.rc('font', **{'family': 'serif'})
mpl.rc('text', usetex=True)
# Path to data
filename = "../../Data/trappist1FiducialRatio.h5"
# Whether or not to plot blobs
plotBlobs = False
# Extract results
if plotBlobs:
chain, blobs = extractMCMCResults(filename,
blobsExist=plotBlobs,
burn=500,
removeRogueChains=False)
else:
chain = extractMCMCResults(filename,
blobsExist=plotBlobs,
burn=500,
removeRogueChains=False)
if plotBlobs:
samples = np.hstack([chain, blobs])
# Define Axis Labels
labels = [
"Mass", "SatXUVFrac", "SatXUVTime", "Age", "XUVBeta", "Lum",
"logLumXUV", "Radius"
]