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View Code? Open in Web Editor NEWPythonic stellar model grid access; easy MCMC fitting of stellar properties
Home Page: http://isochrones.readthedocs.org
License: MIT License
Pythonic stellar model grid access; easy MCMC fitting of stellar properties
Home Page: http://isochrones.readthedocs.org
License: MIT License
There is a failure when using python 3 caused because astroquer.vizier.Vizier returns bytes instead of strings in some columns and the assertions in test_query.py
fail.
======================================================================
FAIL: Testing with first entry from Gaia DR1 TGAS table
----------------------------------------------------------------------
Traceback (most recent call last):
File "/usr/lib/python3.5/site-packages/nose/case.py", line 198, in runTest
self.test(*self.arg)
File "/home/miguel/Gaia/isochrones/isochrones/tests/test_query.py", line 14, in test_queries
assert tm.get_id() == '03000819+0014074'
AssertionError:
-------------------- >> begin captured logging << --------------------
root: WARNING: PyMultiNest not imported. MultiNest fits will not work.
requests.packages.urllib3.connectionpool: DEBUG: Starting new HTTP connection (1): vizier.u-strasbg.fr
requests.packages.urllib3.connectionpool: DEBUG: http://vizier.u-strasbg.fr:80 "POST /viz-bin/votable HTTP/1.1" 200 3558
--------------------- >> end captured logging << ---------------------
----------------------------------------------------------------------
Ran 1 test in 0.986s
FAILED (failures=1)
e.g. PARSEC grid from Bressan et al. (2012)
The code below produces two very different isochrones, where I expect them to be the same. This is true for the whole range of allowed (age, feh) which does not cause isochrone()
to fail (that's another issue).
from isochrones.mist import MISTModelGrid, MIST_Isochrone
import numpy as np
from matplotlib import pyplot as plt
def test(age=9.0, feh=0.0):
age_Gyr = 10.**age/1e9
grid = MISTModelGrid(['B', 'V'])
sel = np.isclose(grid.df.feh, feh) & np.isclose(grid.df.log10_isochrone_age_yr, age)
iso1 = grid.df[sel]
mist = MIST_Isochrone()
iso2 = mist.isochrone(age, feh=feh)
plt.figure()
plt.plot(iso1.log_Teff, iso1.log_L, 'r-', label='grid.df')
plt.plot(np.log10(iso2.Teff), iso2.logL, 'b-', label='mist.isochrone')
plt.gca().invert_xaxis()
plt.xlabel('log(Teff)')
plt.ylabel('log(L)')
plt.title("log(age)=%0.2f (%0.1f Gyr) [Fe/H]=%0.2f" % (age, age_Gyr, feh))
plt.legend()
test()
For example, running this on Jupyter notebook (py3.6):
mist = MIST_Isochrone()
#masses, logages, FeHs:
m,a,f=np.random.normal(1.0,0.1,1000),np.random.normal(8.5,0.1,1000),np.random.normal(0.0,0.1,1000)
rads0=mist.radius(m,a,f) #this works fine
#Adding some NaNs in the logage
chx=np.random.random(1000)
a[chx>0.45]=np.tile(np.nan,(chx>0.45).sum())
#Running
rads=mist.radius(m,a,f)
The code just hangs infinitely, and I have to manually kill the kernel (interrupting doesn't work) and run everything else in my ipynb again.
I could definitely just put some code to catch them and return NaNs instead of running mist.radius, but equally I feel like this could be put in the function itself, and certainly any infinite loops should be caught and excepted!
Hi Tim,
Maybe I'm doing something embarrasing wrong, but I'm not able to get the right age of the Sun (4.567Gyr) using Dartmouth isochrones.
import numpy as np
from isochrones.dartmouth import Dartmouth_Isochrone
dar = Dartmouth_Isochrone()
mass, feh = 1.00, 0.00
age10 = dar.agerange(mass, feh)
age10 = np.mean(age10)
age = 10**age10/1e9 # This is 3.490Gyr
Python quits with a segmentation fault when I try to import isochrone models (e.g., import isochrones.dartmouth or from isochrones.padova import ...). This also happens after I download the data by hand and I just try to import the module, so I assume it must be because of the pd.read_hdf command (and just running pd.read_hdf confirms this). I seem to be able to open the file with h5py.
This is in IPython 2.1.0, Python 2.7.6 on Mac OS X Yosemite 10.10.2, pandas 0.16.0.
instead of multinest, try using the PTSampler
class in emcee
I am getting an error just running the first 3 lines of the example:
from isochrones.dartmouth import Dartmouth_Isochrone
dar = Dartmouth_Isochrone()
dar.radius(1.0, 9.7, 0.0) #M/Msun, log10(age), Fe/H
Below is the error message; apparently there is an issue with urlib.retrieve. I think this module is no more available with Python3.5. Not sure how to circumvent the problem, or if a fix has to be implemented to the code. Thank you!
AttributeError Traceback (most recent call last)
in ()
----> 1 from isochrones.dartmouth import Dartmouth_Isochrone
2 dar = Dartmouth_Isochrone()
3 dar.radius(1.0, 9.7, 0.0) #M/Msun, log10(age), Fe/H
//anaconda/lib/python3.5/site-packages/isochrones/dartmouth.py in ()
54
55 if not os.path.exists(MASTERFILE):
---> 56 _download_h5()
57
58 if not os.path.exists(TRI_FILE):
//anaconda/lib/python3.5/site-packages/isochrones/dartmouth.py in _download_h5()
38 if os.path.exists(MASTERFILE):
39 os.remove(MASTERFILE)
---> 40 urllib.urlretrieve(url,MASTERFILE)
41
42 def _download_tri():
AttributeError: module 'urllib' has no attribute 'urlretrieve'
The current output of the Binary and Triple fitting (the parameters in model.samples.columns) is a bit of a mishmash of notation and missing some information about the B and C components. The most important issue is that there is no output for the B and C components of logL, logg, and Teff.
The first notation issue deals with the mass. While the unlabeled physical values all stand for the A component, like 'radius' and 'logg', the A component of mass is explicitly 'mass_A' and not 'mass' like the rest of the physical values.
The second notation issue is that (it appears) that the convention of "an unlabeled parameter means it's the A component" doesn't apply to the magnitudes. Rather, the unlabeled magnitudes are (it appears) the sum of the listed A, B, and C component magnitudes.
The first one is really the only important one, but the other two are just a bit of an issue with consistency.
(And great code, by the way. Really pretty easy to use.)
To make sure the data files in ~/.isochrones
are current.
Trying to install this package I was forced to first install numexpr
and cython
. Could this perhaps be added as needed dependencies so one knows and installs them in advance, to prevent the installation from halting twice?
There is an error in test_fits when saving object data to HDF5 if multinest is not available:
======================================================================
ERROR: isochrones.tests.test_fits.test_fitting
----------------------------------------------------------------------
Traceback (most recent call last):
File "/usr/lib/python3.5/site-packages/nose/case.py", line 198, in runTest
self.test(*self.arg)
File "/home/miguel/Gaia/isochrones/isochrones/tests/test_fits.py", line 26, in test_fitting
_check_saving(mod_dar)
File "/home/miguel/Gaia/isochrones/isochrones/tests/test_fits.py", line 33, in _check_saving
mod.save_hdf(filename)
File "/home/miguel/Gaia/isochrones/isochrones/starmodel.py", line 1038, in save_hdf
attrs._mnest_basename = self._mnest_basename
AttributeError: 'StarModel' object has no attribute '_mnest_basename'
Getting JSON dump error!
Currently, the following star.ini
file is incompatible with StarModel because the companion stars were not all detected in the same filters.
maxAV = 0.162
RA = 287.69800
dec = 42.338718
Teff = 5465, 109
feh = 0.020, 0.150
logg = 4.449, 0.085
[twomass]
J = 11.252, 0.021
H = 10.910, 0.019
K = 10.871, 0.013
[Lick]
resolution = 0.5
separation_1 = 3.842
PA_1 = 53.056
H_1 = 4.343, 0.010000000000000231
K_1 = 4.105, 0.054999999999999716
separation_2 = 12.073
PA_2 = 256.378
H_2 = 7.488, 0.010000000000000231
Those companions that have detections in filters where others were not detected have useful color information that should be included, but currently cannot be. This would be a useful adjustment to the StarModel class.
Not sure why the installation is failing. I downloaded the data files by hand and moved them to ~/.isochrones, and for good measure uninstalled the older (0.9.1) version of isochrones that came bundled earlier using:
pip uninstall isochrones
pip install isochrones
But the module doesn't load into python:
Python 2.7.12 |Anaconda 2.2.0 (x86_64)| (default, Jul 2 2016, 17:43:17)
[GCC 4.2.1 (Based on Apple Inc. build 5658) (LLVM build 2336.11.00)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
Anaconda is brought to you by Continuum Analytics.
Please check out: http://continuum.io/thanks and https://anaconda.org
import isochrones
Traceback (most recent call last):
File "", line 1, in
File "//anaconda/lib/python2.7/site-packages/isochrones/init.py", line 10, in
from .isochrone import Isochrone, get_ichrone
File "//anaconda/lib/python2.7/site-packages/isochrones/isochrone.py", line 2, in
import pandas as pd
File "//anaconda/lib/python2.7/site-packages/pandas/init.py", line 53, in
from pandas.io.api import *
File "//anaconda/lib/python2.7/site-packages/pandas/io/api.py", line 10, in
from pandas.io.html import read_html
File "//anaconda/lib/python2.7/site-packages/pandas/io/html.py", line 25, in
import bs4
File "//anaconda/lib/python2.7/site-packages/bs4/init.py", line 30, in
from .builder import builder_registry, ParserRejectedMarkup
File "//anaconda/lib/python2.7/site-packages/bs4/builder/init.py", line 311, in
from . import _html5lib
File "//anaconda/lib/python2.7/site-packages/bs4/builder/_html5lib.py", line 57, in
class TreeBuilderForHtml5lib(html5lib.treebuilders._base.TreeBuilder):
AttributeError: 'module' object has no attribute '_base'
(Well, they probably don't actually.)
But the following instructions result in essentially the same values for Teff from 3000-7000:
mist = MIST_Isochrone()
model = StarModel(mist, Teff=(5770, 80), logg=(4.44, 0.08), feh=(0.,0.1))
model.fit()
model.samples['radius_0_0'].quantile([0.15,0.5,0.85])
0.15 0.922251
0.50 0.982562
0.85 1.064326
When importing the library or running the nosetests i get the following error:
File /anaconda2/lib/python2.7/site-packages/isochrones/starmodel.py", line 16, in
import pymultinest
ImportError: No module named pymultinest
When going through the code I noticed that there aren't any library import checks in starmodel.py as opposed to starmodel_old.py
mnest_available = True
try:
import pymultinest
except ImportError:
logging.warning('PyMultiNest not available; only emcee fits will be possible.')
pymultinest = None
mnest_available = False
Does the new model supports computations without pymultinest being installed or should we use the old model instead?
Would submit a pull request but we're just about to run to lunch.
starmodel:441. "thresh_100" should be "lnprob_thresh_100". Causes failure in plotting and saving to hdf5 file.
I have been trying to use the interpolation scheme fro the Dartmouth models, but this yield some strange results.
Tested in the following environment
1.0.0 >= scipy >= 0.12.0
numpy= 1.13.3
pandas= 0.20.3
python 2.7.3
from matplotlib import pyplot as plt
import numpy as np
from isochrones.dartmouth import Dartmouth_Isochrone, DartmouthModelGrid
dar = Dartmouth_Isochrone()
d = DartmouthModelGrid(['g', 'r']).df
g = dar.mag['g']
r = dar.mag['r']
## Original grid
plt.figure(figsize=(4,6))
j = (d['age']==9)&(d['feh']==-2.5)
plt.plot(d['g'][j]-d['r'][j], d['g'][j], 'k-', lw=2, label="1.00 Gyr")
j = (d['age']>9)&(d['age']< 9.097)&(d['feh']==-2.5)
plt.plot(d['g'][j]-d['r'][j], d['g'][j], 'b-', lw=2, label="1.25 Gyr")
## Interpolated model
mm = np.arange(0.1,3, 0.00001)
tg = g(mm, 9.05, -2.5)
tr = r(mm, 9.05, -2.5)
plt.plot(tg-tr,tg,'r-', lw=2, label='1.12Gyr (interp)')
plt.ylim(plt.ylim()[::-1])
plt.legend(loc='best')
plt.xlabel('g-r')
plt.ylabel('g')
plt.savefig('test.png')
In order to sample what possible multiple systems could be consistent with observable properties.
age, feh, distance, AV
would be shared between primary and secondary, photometric properties would apply to the "sum" of the magnitudes of the two stars, and spectroscopic properties would apply only to the brighter component.
Getting an error when running nosetests
and when trying to execute model.fit()
.
File "/Users//MultiNest/build/PyMultiNest/isochrones/isochrones/isochrone.py", line 145, in init
self.mass = interpnd(self.tri,m_act)
File "scipy/interpolate/interpnd.pyx", line 243, in scipy.interpolate.interpnd.LinearNDInterpolator.init (scipy/interpolate/interpnd.c:4934)
File "scipy/interpolate/interpnd.pyx", line 71, in scipy.interpolate.interpnd.NDInterpolatorBase.init (scipy/interpolate/interpnd.c:2298)
File "scipy/spatial/qhull.pyx", line 1910, in scipy.spatial.qhull.Delaunay.points (scipy/spatial/qhull.c:18057)
AttributeError: 'Delaunay' object has no attribute '_points'
Maybe there was an update where this is no longer an attribute? Can't seem to find anything on the internet.
I fail to initialize Dartmouth_Isochrone:
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-33-643606627c59> in <module>()
----> 1 dar = Dartmouth_Isochrone()
~/projects/opensource/isochrones/isochrones/dartmouth/isochrone.py in __init__(self, bands, afe, y, **kwargs)
87 df['feh'].values,df['MMo'].values, df['LogLLo'].values,
88 10**df['LogTeff'].values,df['LogG'].values,mags,tri=TRI,
---> 89 **kwargs)
90
91 def agerange(self, m, feh=0.0):
~/projects/opensource/isochrones/isochrones/isochrone.py in __init__(self, m_ini, age, feh, m_act, logL, Teff, logg, mags, tri, minage, maxage, ext_table)
143 else:
144 self.tri = tri
--> 145 self.mass = interpnd(self.tri,m_act)
146
147 self._data = {'mass':m_act,
scipy/interpolate/interpnd.pyx in scipy.interpolate.interpnd.LinearNDInterpolator.__init__ (scipy/interpolate/interpnd.c:5484)()
scipy/interpolate/interpnd.pyx in scipy.interpolate.interpnd.NDInterpolatorBase.__init__ (scipy/interpolate/interpnd.c:2621)()
scipy/spatial/qhull.pyx in scipy.spatial.qhull.Delaunay.points (scipy/spatial/qhull.c:18892)()
AttributeError: 'Delaunay' object has no attribute '_points'
https://gist.github.com/smoh/ea7505cdf227feb61b49755f71f2abe2
Do you think the picked file darthmouth.tri
is outdated or something?
(I downloaded the file for the first time as you can see)
Integrate over filters instead of relying on lookup table of effective wavelengths. This is absolutely necessary for broad bands like Gaia bands.
I get the error:
ERROR: ImportError: HDFStore requires PyTables [pandas.io.pytables]
ERROR:astropy:ImportError: HDFStore requires PyTables
My guess is that the version of Pandas required in setup.py is not sufficiently high.
Would be great to be able to implement tri-cubic interpolation if it could be of comparable efficiency as the current NDLinearInterpolator
implementation.
Maybe adapting this?
I would like to use this program to type stars in the LMC from the Dartmouth isochrones using archival HST Wfc3 Uvis and IR data. When I use your isochrone program though this is not an option for the Dartmouth isochrones:
-->DartmouthModelGrid.phot_bands
{'LSST': ['LSST_r', 'LSST_u', 'LSST_y', 'LSST_z', 'LSST_g', 'LSST_i'],
'SDSSugriz': ['sdss_z', 'sdss_i', 'sdss_r', 'sdss_u', 'sdss_g'],
'UBVRIJHKsKp': ['B', 'I', 'H', 'J', 'Ks', 'R', 'U', 'V', 'D51', 'Kp'],
'UKIDSS': ['Y', 'H', 'K', 'J', 'Z'],
'WISE': ['W4', 'W3', 'W2', 'W1']}
. Is there anyway to include the phot bands that I need?
The Dartmouth page has a calculator at:
http://stellar.dartmouth.edu/models/isolf_new.html
and the bands I am interested in are in the "Colors" pull down menu.
Thanks!
Luke Hovey
But timing the log-likelihood function is comparable to Dartmouth... not sure what's going on here.
I can initiate a grid of Dartmouth isochrones with a minimum age with no error:
dar = Dartmouth_Isochrone(minage=(10))
But if I try the same command with MIST isochrones
mist = MIST_Isochrone(minage=(10))
I get the following error:
TypeError Traceback (most recent call last)
in ()
----> 1 mist = MIST_Isochrone(minage=(10))
TypeError: init() got an unexpected keyword argument 'minage'
Hello Tim,
I just installed isochrones and I am running the example you provided in the documentation:
import numpy as np
from isochrones import StarModel
from isochrones.dartmouth import Dartmouth_Isochrone
#spectroscopic properties (value, uncertainty)
Teff = (5770, 80)
logg = (4.44, 0.08)
feh = (0.00, 0.10)
dar = Dartmouth_Isochrone()
model = StarModel(dar, Teff=Teff, logg=logg, feh=feh)
Till here everything is working fine without any errors. However, when I execute the command:
model.fit()
I get the following error:
TypeError: unsupported operand type(s) for /: 'NoneType' and 'float'
Can you please tell me how to fix this error.
Running through the demo notebook as downloaded, I get to cell 10
dar = Dartmouth_Isochrone()
dar.bands #default bands
and get the following error:
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-10-45bde7a2afff> in <module>()
----> 1 dar = Dartmouth_Isochrone()
2 dar.bands #default bands
//anaconda/lib/python2.7/site-packages/isochrones/dartmouth/isochrone.pyc in __init__(self, bands, afe, y, **kwargs)
87 df['feh'].values,df['MMo'].values, df['LogLLo'].values,
88 10**df['LogTeff'].values,df['LogG'].values,mags,tri=TRI,
---> 89 **kwargs)
90
91 def agerange(self, m, feh=0.0):
//anaconda/lib/python2.7/site-packages/isochrones/isochrone.pyc in __init__(self, m_ini, age, feh, m_act, logL, Teff, logg, mags, tri, minage, maxage, ext_table)
141 else:
142 self.tri = tri
--> 143 self.mass = interpnd(self.tri,m_act)
144
145 self._data = {'mass':m_act,
scipy/interpolate/interpnd.pyx in scipy.interpolate.interpnd.LinearNDInterpolator.__init__ (scipy/interpolate/interpnd.c:4934)()
scipy/interpolate/interpnd.pyx in scipy.interpolate.interpnd.NDInterpolatorBase.__init__ (scipy/interpolate/interpnd.c:2298)()
scipy/spatial/qhull.pyx in scipy.spatial.qhull.Delaunay.points (scipy/spatial/qhull.c:18057)()
AttributeError: 'Delaunay' object has no attribute '_points'
Migrate to h5py to avoid things like #11 .
The docstring for the MIST isochrone says that the B and V mags are Tycho-2 mags:
:param bands: (optional)
List of desired photometric bands. Default list of bands is
``['G','B','V','J','H','K','W1','W2','W3','g','r','i','z','Kepler']``.
Here ``B`` and ``V`` are Tycho-2 mags, `griz` are SDSS, and ``G`` is
Gaia G-band.
However, I think it is actually using the Bessell B and V. The get_band function in isochrones/mist/grid.py has:
# Default to SDSS for these
if b in ['u','g','r','i','z']:
phot = 'SDSS'
band = 'SDSS_{}'.format(b)
# elif b in ['B','V']:
# phot = 'UBVRIplus'
# band = 'Tycho_{}'.format(b)
elif b in ['U','B','V','R','I']:
phot = 'UBVRIplus'
band = 'Bessell_{}'.format(b)
If I want to actually use the Tycho-2 mags, I should uncomment the above and change the effective wavelengths in data/filters.txt?
Thanks!
Hi Tim,
I was able to import with current master of isochrones, but was getting some tarball decompression error even after I did it manually in ~/.isochrones/mist/
. I think this is because WISE is not in the current MIST model upload in zenodo, and the code keeps requiring it, trying to download and decompress the entire master tarball again.
Traceback:
> /Users/semyeong/projects/isochrones/isochrones/mist/grid.py(111)get_filenames()
109 if not os.path.exists(d):
110 if not os.path.exists(self.phot_tarball_file(phot, version=version)):
--> 111 self.extract_master_tarball()
112 self.extract_phot_tarball(phot, version=version)
113
ipdb> self.phot_tarball_file(phot,version=version)
'/Users/semyeong/.isochrones/mist/MIST_v1.0_WISE.tar.gz'
Just thought I'd let you know.
Here's what I'm running in spyder
from isochrones import StarModel
from isochrones.dartmouth import Dartmouth_IsochroneTeff = (5770, 80)
logg = (4.44, 0.08)
feh = (0.00, 0.10)
V = (10.0,0.05)
dar = Dartmouth_Isochrone()
model = StarModel(dar, Teff=Teff, logg=logg, feh=feh)
model.fit()
Should something be happening? It's possible it's running successfully and I just don't know how to access the parameters? (Mass, radius, etc).
I get the following warning when using the code:
from isochrones.dartmouth import Dartmouth_Isochrones
WARNING:root:Deprecation Warning: 'triangle' has been renamed to 'corner'. This shim should continue to work but you should use 'import corner' in new code. https://github.com/dfm/corner.py
I think it should just be editing line 27 here, but you might import it other places. And of course set corner
as a new dependency.
First, thanks for making this code open source and available.
I am curious about adding support for the Baraffe et al. (e.g. BCAH 2002, BHAC 2015) pre-main sequence evolutionary models:
http://perso.ens-lyon.fr/isabelle.baraffe/
My guess on how to get started is basically just copy from one of the existing example models:
This seems straighforward, but the devil is in the details. For example, one difference is that the Baraffe et al. models have fixed metallicity, so there'd be a delta function in Fe/H that could screw up parts of the code that are expecting this to be another dimension.
I'll see if this will work, but any tips or caveats are welcomed here.
The following results in ZeroDivisionError
. This seems to happen for feh
values which lie exactly on the MIST grids, but not for all ages. For example, age=9.0
works fine.
mist = MIST_Isochrone()
iso3 = mist.isochrone(8.0, feh=0.0)
I'm getting this error when trying to use mod.corner_physical
, my star.ini
file is set up just like the one in Input[40] of the demo notebook and the mod.fit()
ran fine.
WARNING:root:Use Tim's version of corner to plot priors.
Traceback (most recent call last):
File "<ipython-input-1-bc545b48eeb0>", line 1, in <module>
runfile('/Users/Austin/star_ini_test.py', wdir='/Users/Austin')
File "/Users/Austin/anaconda/lib/python3.6/site-packages/spyder/utils/site/sitecustomize.py", line 880, in runfile
execfile(filename, namespace)
File "/Users/Austin/anaconda/lib/python3.6/site-packages/spyder/utils/site/sitecustomize.py", line 102, in execfile
exec(compile(f.read(), filename, 'exec'), namespace)
File "/Users/Austin/star_ini_test.py", line 20, in <module>
mod5.corner_physical();
File "/Users/Austin/anaconda/lib/python3.6/site-packages/isochrones-1.0-py3.6.egg/isochrones/starmodel.py", line 951, in corner_physical
return self.corner(props, range=rng, **kwargs)
File "/Users/Austin/anaconda/lib/python3.6/site-packages/isochrones-1.0-py3.6.egg/isochrones/starmodel.py", line 927, in corner
fig = corner.corner(df[params], labels=params, **kwargs)
File "/Users/Austin/anaconda/lib/python3.6/site-packages/corner-2.0.1-py3.6.egg/corner/corner.py", line 240, in corner
range=np.sort(range[i]), **hist_kwargs)
File "/Users/Austin/anaconda/lib/python3.6/site-packages/matplotlib/__init__.py", line 1898, in inner
return func(ax, *args, **kwargs)
File "/Users/Austin/anaconda/lib/python3.6/site-packages/matplotlib/axes/_axes.py", line 6195, in hist
m, bins = np.histogram(x[i], bins, weights=w[i], **hist_kwargs)
File "/Users/Austin/anaconda/lib/python3.6/site-packages/numpy/lib/function_base.py", line 669, in histogram
'range parameter must be finite.')
ValueError: range parameter must be finite.`
This is what my star.ini
file looks like:
maxAV = 0.217
RA = 283.23581
dec = 41.34304
Teff = 5925, 118
feh = -0.25, 0.15
logg = 4.36, 0.15
[KIC]
g = 12.172, 0
r = 11.749, 0
i = 11.666, 0
z = 11.632, 0
[twomass]
J = 10.797, 0.023
H = 10.516, 0.023
K = 10.424, 0.019
[Lick]
resolution = 0.5
separation_1 = 0.897
PA_1 = 96.871
K_1 = 0.286, 0.1
H_1 = 0.295, 0.1
separatin_2 = 5.765
PA_2 = 174.188
H_2 = 8.058, 0.1
separation_3 = 13.879
PA_3 = 316.172
H_3 = 7.682, 0.1
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