def sanity_ramirez2005(self):
"""
Check sanity Ramirez/Melendez 2005 conversions
"""
from PyAstronomy import pyasl
import numpy as np
from itertools import product
feh = 0.0
r = pyasl.Ramirez2005()
# Compare with numbers given in Allen (astrophysical quantities, 4th edition)
for teff, bv in zip([7000., 5950., 5310., 4410.],
[0.35, 0.58, 0.74, 1.15]):
self.assertAlmostEqual(bv,
r.teffToColor("B-V", teff, feh),
delta=0.03,
msg="B-V conversion (Teff " + str(teff) +
") out of sync with Allen")
for teff, bv in zip([6500., 6000., 5000.], [0.286, 0.36, 0.535]):
self.assertAlmostEqual(bv,
r.teffToColor("b-y", teff, feh),
delta=0.01,
msg="B-V conversion (Teff " + str(teff) +
") out of sync with Allen")
for teff, bv in zip([5000., 4500., 4000.], [0.433, 0.51, 0.735]):
self.assertAlmostEqual(bv,
r.teffToColor("R_C-I_C", teff, feh, 'g'),
delta=0.04,
msg="R_C-I_C conversion (Teff " +
str(teff) +
") out of sync with Allen (giants)")
for teff, bv in zip([5050., 4660., 4050.], [0.86, 1., 1.5]):
self.assertAlmostEqual(bv,
r.teffToColor("B-V", teff, feh, 'g'),
delta=0.1,
msg="B-V conversion (Teff " + str(teff) +
") out of sync with Allen (giants)")
# Check consistency
bv = np.arange(0.4, 1.01, 0.05)
feh = np.arange(-2., 0.3, 0.2)
for x in product(bv, feh):
teff = r.colorToTeff("B-V", x[0], x[1], 'ms')
col = r.teffToColor("B-V", teff, x[1], 'ms')
self.assertAlmostEqual(
x[0],
col,
delta=1e-2,
msg=
"Two-way color-temperature conversion is inconsistent. bv = %.4e, feh = %.4e"
% x)
def sanity_ramirez2005Example2(self):
"""
Checking Ramirez, Ballesteros example
"""
from PyAstronomy import pyasl
b = pyasl.BallesterosBV_T()
r = pyasl.Ramirez2005()
# Convert B-V to effective temperature and back
for bv in [
0.35, 0.45, 0.55, 0.65, 0.75, 0.85, 0.95, 1.05, 1.15, 1.25,
1.35, 1.45
]:
tr = r.colorToTeff("B-V", bv, 0.0)
tb = b.bv2T(bv)
print(("B-V [mag] = {3:4.2f} : Teff (R05) = {0:4.0f} K, " + \
"Teff (B12) = {1:4.0f} K, dTeff = {2: 4.0f} K").format(tr, tb, tr - tb, bv))
def sanity_ramirez2005Example(self):
"""
Check sanity of Ramirez/Melendez 2005 example
"""
from PyAstronomy import pyasl
# Create class instance
r = pyasl.Ramirez2005()
# Which color bands are available
print("Available color bands: ", r.availableBands())
# Convert B-V to effective temperature and back
bv = 0.75
feh = 0.0
teff = r.colorToTeff("B-V", bv, feh)
bv1 = r.teffToColor("B-V", teff, feh)
# Watch out for differences between input bv and the output bv1
print("B-V = ", bv, ", Teff = ", teff, ", bv1 = ", bv1, ", bv-bv1 = ",
bv - bv1)
pip install arviz import numpy as np import arviz as az import pandas as pd import matplotlib.pyplot as plt import tensorflow.compat.v2 as tf import tensorflow_probability as tfp from mpl_toolkits.mplot3d import Axes3D from google.colab import files import io from PyAstronomy import pyasl import time r = pyasl.BallesterosBV_T() b = pyasl.Ramirez2005() uploaded = files.upload() data0 = data = np.array(pd.read_csv(io.BytesIO(uploaded['SItable1.csv']))) import tensorflow.math as tf_m def mean_fn(x, y, a, b, c, d): return (np.exp(x)*1000)**a * b*(y - c)**d #the m relation was through trial and error #fn from Barnes 2007 pd.read_csv(io.BytesIO(uploaded['SItable1.csv'])) #tolist makes array to list to remove 'dtype=float64' from the end of the array te = data0[:,2].tolist() tee= data0[:,3].tolist() age = data0[:,4].tolist()
tsi = pd.read_csv('tsi_data_6h.txt') # TSI SORCE data (6-hourly)
montet = pd.read_csv(
'montet_stars.txt') #Original data from Montet et al. (2018)
#Downloaded from: https://iopscience.iop.org/0004-637X/851/2/116/suppdata/apjaa9e00t1_mrt.txt
#-------------------------------- FILTER DATA ----------------------------------------
montet = montet[(montet['Notes1'] == 0)] #Filter out short-period binaries
#Temperature limit stars for analysis (sun-like stars only):
T_upper = 6000
T_lower = 5000
#Convert chosen temperature limits to B-V using method in Ramirez & Melendez (2005)
bv_upper = pyasl.Ramirez2005().teffToColor_nop("B-V", T_upper, 0.0)
bv_lower = pyasl.Ramirez2005().teffToColor_nop("B-V", T_lower, 0.0)
montet_bv = montet[(montet['B-V'] < bv_lower)] #Filter stars by temperature
montet_bv = montet[(montet['B-V'] > bv_upper)]
montet = montet_bv[(montet_bv['Scatter'] <
10)] #Remove high scatter stars (> 10)
montet = montet[(montet['Prot'] >
1)] #Remove stars with rotations periods < 1 day
#----------------------------------------------------------------------------------------
fac = montet[(montet['Var'] == 'Faculae'
)].reset_index() #Montet stars identified as facula-dominated
spots = montet[(montet['Var'] == 'Spots'