Comply with detector type update on SVO website (#44)

* Detector type update on SVO website, convert list of bytes to strings in ReadIsochrone

* Minor change in the accuracy of a unit test with Monte Carlo

README.rst

@@ -34,6 +34,11 @@ Documentation
 
 Documentation can be found at `http://species.readthedocs.io <http://species.readthedocs.io>`_.
 
+Tutorials
+---------
+
+There are several `Jupyter notebooks <https://species.readthedocs.io/en/latest/tutorials.html>`_ with tutorials that showcase the workflow and available tools. They can also be executed on `Binder <https://mybinder.org/v2/gh/tomasstolker/species/HEAD>`_ by navigating to the *docs/tutorials* folder.
+
 Attribution
 -----------
 

docs/tutorials/fitting_model_spectra.ipynb

@@ -11,7 +11,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "In this tutorial, we will fit spectra and photometric fluxes of [beta Pic b](http://exoplanet.eu/catalog/beta_pic_b/) with the synthetic spectra from a radiative-convective equilibrium atmosphere model. Here we will use [DRIFT-PHOENIX](https://leap2010blog.wordpress.com/2014/07/03/drift-phoenix-atmosphere-models-creating-new-worlds/) but there are also several [other models supported by *species*](https://species.readthedocs.io/en/latest/overview.html#supported-data)."
+    "In this tutorial, we will fit spectra and photometric fluxes of [beta Pic b](http://exoplanet.eu/catalog/beta_pic_b/) with the synthetic spectra from a radiative-convective equilibrium atmosphere model. Here we will use [DRIFT-PHOENIX](https://leap2010blog.wordpress.com/2014/07/03/drift-phoenix-atmosphere-models-creating-new-worlds/) but there are also [several other models](https://species.readthedocs.io/en/latest/overview.html#supported-data) supported by *species*."
    ]
   },
   {

species/data/filters.py

@@ -132,20 +132,18 @@ def download_filter(filter_id: str) -> Tuple[Optional[np.ndarray],
                              f'available?')
 
         if transmission is not None:
-            try:
-                det_type = table.get_field_by_id('DetectorType').value
+            det_type = table.get_field_by_id('DetectorType').value
 
-                # For backward compatibility
-                if not isinstance(det_type, str):
-                    det_type = det_type.decode('utf-8')
+            # For backward compatibility
+            if not isinstance(det_type, str):
+                det_type = det_type.decode('utf-8')
 
-                if int(det_type) == 1:
-                    det_type = 'photon'
-
-            except KeyError:
-                # Energy-counting detector if the DetectorType key is not present
+            if int(det_type) == 0:
                 det_type = 'energy'
 
+            elif int(det_type) == 1:
+                det_type = 'photon'
+
             wavelength *= 1e-4  # (um)
 
         os.remove('filter.xml')

species/data/isochrones.py

@@ -12,10 +12,9 @@ def add_baraffe(database,
                 tag,
                 filename):
     """
-    Function for adding the Baraffe et al. isochrone data to the database. Any of the isochrones
-    from  https://phoenix.ens-lyon.fr/Grids/ can be used as input.
-
-    https://ui.adsabs.harvard.edu/abs/2003A%26A...402..701B/
+    Function for adding the `Baraffe et al. (2003)
+    <https://ui.adsabs.harvard.edu/abs/2003A%26A...402..701B/>`_ isochrone data to the database.
+    Any of the isochrones from  https://phoenix.ens-lyon.fr/Grids/ can be used as input.
 
     Parameters
     ----------
@@ -32,8 +31,10 @@ def add_baraffe(database,
         None
     """
 
-    # read in all the data, ignoring empty lines or lines with '---'
+    # Read in all the data, ignoring empty lines or lines with '---'
+
     data = []
+
     with open(filename) as data_file:
         for line in data_file:
             if '---' in line or line == '\n':

species/read/read_isochrone.py

@@ -75,14 +75,16 @@ def get_isochrone(self,
             Box with the isochrone.
         """
 
-        age_points = np.repeat(age, masses.shape[0])  # (Myr)
+        age_points = np.full(masses.shape[0], age)  # (Myr)
 
         color = None
         mag_abs = None
 
         index_teff = 2
         index_logg = 4
 
+        # Read isochrone data
+
         with h5py.File(self.database, 'r') as h5_file:
             model = h5_file[f'isochrones/{self.tag}/evolution'].attrs['model']
             evolution = np.asarray(h5_file[f'isochrones/{self.tag}/evolution'])
@@ -91,6 +93,11 @@ def get_isochrone(self,
                 filters = list(h5_file[f'isochrones/{self.tag}/filters'])
                 magnitudes = np.asarray(h5_file[f'isochrones/{self.tag}/magnitudes'])
 
+                # Convert the h5py list of filters from bytes to strings
+                for i, item in enumerate(filters):
+                    if isinstance(item, bytes):
+                        filters[i] = item.decode('utf-8')
+
         if model == 'baraffe':
             if filters_color is not None:
                 index_color_1 = filters.index(filters_color[0])

test/test_analysis/test_photometry.py

@@ -115,5 +115,5 @@ def test_spectrum_to_magnitude(self):
         assert abs_mag[0] == pytest.approx(5.59000700894101, rel=self.limit, abs=0.)
 
         # The error is estimated with Monte Carlo sampling
-        assert app_mag[1] == pytest.approx(5.368048545366946e-05, rel=0., abs=1e-5)
+        assert app_mag[1] == pytest.approx(5.368048545366946e-05, rel=0., abs=2e-5)
         assert abs_mag[1] == pytest.approx(0.021714790446227043, rel=0., abs=1e-2)