def sanity_BallesterosExample(self):
"""
Checking example for Ballesteros
"""
from PyAstronomy import pyasl
b = pyasl.BallesterosBV_T()
bv = 0.65
# Convert B-V into effective temperature
teff = b.bv2T(0.65)
print("B-V = {0:4.2f} mag -> Teff = {1:4.0f} K".format(bv, teff))
# Convert effective temperature into B-V color
teff = 4568.0
bv = b.t2bv(teff)
print("Teff = {0:4.0f} K -> B-V = {1:4.2f} mag".format(teff, bv))
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))
pip install pyAstronomy 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()