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Kernel: Python 3 (system-wide)

ISOCHRONES on CoCalc in Python 3

https://isochrones.readthedocs.io/en/latest/

Data globally stored in $ISOCHRONES

command line:

  1. unset DISPLAY

  2. import matplotlib; matplotlib.use('agg')

import numpy as np import matplotlib.pyplot as plt import sep, astroalign import ccdproc %matplotlib inline
import sys sys.executable
'/usr/bin/python3'
sys.version
'3.6.9 (default, Jul 17 2020, 12:50:27) \n[GCC 8.4.0]'
import isochrones isochrones
PyMultiNest not imported. MultiNest fits will not work.
<module 'isochrones' from '/usr/local/lib/python3.6/dist-packages/isochrones/__init__.py'>
isochrones.__version__
'2.1'
from isochrones import get_ichrone iso = get_ichrone('mist', bands=['Bessell_B', 'Bessell_V'])
ages = np.linspace(1.4e9, 2e9, 5)
model = iso.isochrone(9.0)
model
eep age feh mass initial_mass radius density logTeff Teff logg logL Mbol delta_nu nu_max phase dm_deep Bessell_B_mag Bessell_V_mag
195 195.0 9.0 0.042814 0.108103 0.108103 0.133343 64.280348 3.465890 2923.411541 5.216743 -2.931855 12.069637 998.429682 2.633932e+04 -1.0 0.004742 17.092496 15.494296
196 196.0 9.0 0.042824 0.112932 0.112932 0.137791 60.856285 3.469256 2946.160133 5.205249 -2.889887 11.964717 970.463953 2.562296e+04 -1.0 0.004720 16.860383 15.281213
197 197.0 9.0 0.042834 0.117543 0.117544 0.142177 57.658212 3.472471 2968.048014 5.194272 -2.849811 11.864529 943.753111 2.493869e+04 -1.0 0.004735 16.637645 15.076675
198 198.0 9.0 0.042846 0.122402 0.122402 0.146956 54.371989 3.475860 2991.303471 5.182666 -2.807536 11.758839 915.533478 2.421504e+04 -1.0 0.004778 16.401555 14.859815
199 199.0 9.0 0.042858 0.127100 0.127100 0.151731 51.294654 3.479138 3013.966420 5.171438 -2.766651 11.656627 888.236405 2.351493e+04 -1.0 0.004716 16.192865 14.664382
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
1705 1705.0 9.0 0.105188 0.605796 2.316544 0.014040 308587.523160 4.440269 27559.329600 7.925739 -0.989547 7.213867 55107.948111 4.361877e+06 6.0 0.000746 9.823777 9.995557
1706 1706.0 9.0 0.105003 0.605877 2.317335 0.014000 311248.361569 4.432439 27066.955047 7.928245 -1.023311 7.298277 55387.362413 4.426862e+06 6.0 0.000837 9.872569 10.038028
1707 1707.0 9.0 0.104796 0.605967 2.318217 0.013962 313901.847291 4.424611 26583.439865 7.930724 -1.057039 7.382597 55665.379255 4.492508e+06 6.0 0.000941 9.921914 10.081159
1708 1708.0 9.0 0.104563 0.606069 2.319217 0.013923 316553.082774 4.416787 26108.776976 7.933184 -1.090724 7.466809 55942.797526 4.558895e+06 6.0 0.001080 9.971796 10.124933
1709 1709.0 9.0 0.104311 0.606173 2.320378 0.013884 319320.086230 4.408754 25630.313721 7.935728 -1.125324 7.553311 56232.374842 4.628347e+06 6.0 0.001274 10.023696 10.170668

1515 rows × 18 columns

model_bvs = [] model_vs = [] labels = [] for age in ages: model = iso.isochrone(np.log10(age)) model_b = model.Bessell_B_mag model_v = model.Bessell_V_mag model_bv = model_b - model_v model_vs.append(model_v) model_bvs.append(model_bv) labels.append('{:.2f} Gyr'.format(age/1e9))
fig, axis = plt.subplots(figsize=(8,6)) axis.set_xlabel('B-V') axis.set_ylabel('V') for label, v, bv in zip(labels, model_vs, model_bvs): axis.plot(bv, v, label=label) axis.legend() axis.set_ylim(-2,4) axis.invert_yaxis() plt.show()
Image in a Jupyter notebook
import astroquery astroquery.__version__
'0.4'

dependencies section

import astroquery astroquery.__version__
'0.4'
## uses too much memory?! from isochrones.mist import MIST_Isochrone mist = MIST_Isochrone() mist.radius(1.0, 9.7, 0.0)
array(nan)
! ls -lh /ext/data/isochrones/mist/
total 1.2G drwxr-xr-x 1 salvus salvus 1.4K Oct 14 09:05 MIST_v1.2_vvcrit0.4_full_isos -rw-r--r-- 1 salvus salvus 661M Sep 29 11:40 MIST_v1.2_vvcrit0.4_full_isos.txz -rw-r--r-- 1 salvus salvus 18M Oct 28 10:48 dm_deep_v1.2_vvcrit0.4_full_isos.h5 -rw-r--r-- 1 salvus salvus 336M Oct 28 10:48 full_grid_v1.2_vvcrit0.4_full_isos.npz -rw-r--r-- 1 salvus salvus 177M Oct 8 18:02 mist_v1.2_vvcrit0.4_full_isos.h5 drwxr-xr-x 1 salvus salvus 1.3K Oct 13 23:25 tracks
! ls -lh /ext/data/isochrones/BC/mist/
total 337M -rw-r--r-- 1 salvus salvus 19M Oct 8 18:04 SDSSugriz.h5 -rw-r--r-- 1 salvus salvus 1.8M Oct 8 18:04 SDSSugriz.txz -rw-r--r-- 1 salvus salvus 71M Oct 8 18:04 UBVRIplus.h5 -rw-r--r-- 1 salvus salvus 8.5M Oct 8 18:04 UBVRIplus.txz -rw-rw-r-- 1 salvus salvus 3.0M Apr 16 2016 fehm025.SDSSugriz -rw-rw-r-- 1 salvus salvus 11M Feb 5 2019 fehm025.UBVRIplus -rw-rw-r-- 1 salvus salvus 3.0M Apr 16 2016 fehm050.SDSSugriz -rw-rw-r-- 1 salvus salvus 11M Feb 5 2019 fehm050.UBVRIplus -rw-rw-r-- 1 salvus salvus 3.0M Apr 16 2016 fehm075.SDSSugriz -rw-rw-r-- 1 salvus salvus 11M Feb 5 2019 fehm075.UBVRIplus -rw-rw-r-- 1 salvus salvus 3.0M Apr 16 2016 fehm100.SDSSugriz -rw-rw-r-- 1 salvus salvus 11M Feb 5 2019 fehm100.UBVRIplus -rw-rw-r-- 1 salvus salvus 3.0M Apr 16 2016 fehm125.SDSSugriz -rw-rw-r-- 1 salvus salvus 11M Feb 5 2019 fehm125.UBVRIplus -rw-rw-r-- 1 salvus salvus 3.0M Apr 16 2016 fehm150.SDSSugriz -rw-rw-r-- 1 salvus salvus 11M Feb 5 2019 fehm150.UBVRIplus -rw-rw-r-- 1 salvus salvus 3.0M Apr 16 2016 fehm175.SDSSugriz -rw-rw-r-- 1 salvus salvus 11M Feb 5 2019 fehm175.UBVRIplus -rw-rw-r-- 1 salvus salvus 3.0M Apr 16 2016 fehm200.SDSSugriz -rw-rw-r-- 1 salvus salvus 11M Feb 5 2019 fehm200.UBVRIplus -rw-rw-r-- 1 salvus salvus 3.0M Apr 16 2016 fehm225.SDSSugriz -rw-rw-r-- 1 salvus salvus 11M Feb 5 2019 fehm225.UBVRIplus -rw-rw-r-- 1 salvus salvus 3.0M Apr 16 2016 fehm250.SDSSugriz -rw-rw-r-- 1 salvus salvus 11M Feb 5 2019 fehm250.UBVRIplus -rw-rw-r-- 1 salvus salvus 3.0M Apr 16 2016 fehm275.SDSSugriz -rw-rw-r-- 1 salvus salvus 11M Feb 5 2019 fehm275.UBVRIplus -rw-rw-r-- 1 salvus salvus 3.0M Apr 16 2016 fehm300.SDSSugriz -rw-rw-r-- 1 salvus salvus 11M Feb 5 2019 fehm300.UBVRIplus -rw-rw-r-- 1 salvus salvus 3.0M Apr 16 2016 fehm350.SDSSugriz -rw-rw-r-- 1 salvus salvus 11M Feb 5 2019 fehm350.UBVRIplus -rw-rw-r-- 1 salvus salvus 3.0M Apr 16 2016 fehm400.SDSSugriz -rw-rw-r-- 1 salvus salvus 11M Feb 5 2019 fehm400.UBVRIplus -rw-rw-r-- 1 salvus salvus 3.0M Apr 16 2016 fehp000.SDSSugriz -rw-rw-r-- 1 salvus salvus 11M Feb 5 2019 fehp000.UBVRIplus -rw-rw-r-- 1 salvus salvus 3.0M Apr 16 2016 fehp025.SDSSugriz -rw-rw-r-- 1 salvus salvus 11M Feb 5 2019 fehp025.UBVRIplus -rw-rw-r-- 1 salvus salvus 3.0M Apr 29 2016 fehp050.SDSSugriz -rw-rw-r-- 1 salvus salvus 11M Feb 5 2019 fehp050.UBVRIplus -rw-rw-r-- 1 salvus salvus 3.0M Apr 30 2016 fehp075.SDSSugriz -rw-rw-r-- 1 salvus salvus 11M Feb 5 2019 fehp075.UBVRIplus