Merge pull request #12 from elliesch/master

More Efficient Template Storage and Added Templates and Standards

.travis.yml

@@ -8,6 +8,10 @@ python:
 script:
 - pytest
 
+install:
+- pip install matplotlib
+- pip install astropy
+
 matrix:
   allow_failures:
-    - python: 2.7.0
+    - python: 2.7.0

README.md

@@ -2,21 +2,23 @@
 Home for qualitative spectral typing GUI that follows the Cruz Method as proposed in <Cruz et al. (2017)>.
 Currently this GUI spectral types L field, L beta and L gamma brown dwarfs.
 This code is written in Python 3.6, and does not yet have functionality for Python 2.
+
 
-
-### Usage
+## Usage
 
 This code currently requires this directory tree to run properly:
 
+```
 ├── TypeFinder.py  
-├── new_types  
+├── new_types/  
 │   └── saves selected spectral type image here  
-├── spectra    
-│   └── nir  
-│       ├── store nir spectra here  
-│       └── store full nir templates here    
-└── templates  
-    └── store Cruz 2017 band-by-band templates here  
+├── spectra/    
+│   └── nir/  
+│       ├── store NIR spectra here  
+│       └── store NIR spectral standards (Table 9, Cruz et al. 2017) here    
+└── templates/  
+    └── store Cruz2017_Templates.hdf5 here  
+ ```
 
 To run many spectra consecutively, the following wrapper can be helpful.
 It will print out the file name and wait for the user to press enter before continuing.
@@ -32,15 +34,31 @@ for file in range(len(lines)):
    ...:     input("Press Enter to continue...")
 
 ```
+
+If you have the Cruz 2017 templates in ascii format, you can [download](.../blob/master/templates/Cruz2017_Templates.hdf5) the hdf5 file from this repository.
+You can also save an hdf5 file the first time you run Ultracool Typing Kit.
+
+```python
+from TypeFinder import*
+typing_kit("spectra/nir/somespectra", make_templates=True)
+
+```
+
+By default make_templates is false, and this input will raise an exception if Cruz2017_Templates.hdf5 already exists.
 
+
+---
+
 
 ### 1. Running the Program
-On running, this initial window will pop up:
+On running, this initial window will pop up, after about 10 seconds:
 <img src="https://raw.githubusercontent.com/elliesch/UltracoolTypingKit/master/opengrid.png" width="750">
 
 Your input spectra will be shown in black, over the Cruz et al. (2017) J-H-K band templates shown in red.
 The initial grid shows each spectral type band-by-band.
 
+
+
 
 ### 2. Selecting a Spectral Type
 To view a specific spectral type in more detail, key in the number you would like to see while your mouse is over the grid.
@@ -68,13 +86,16 @@ This grid shows your selected spectral type bracketed by it's neighboring types,
 the entire NIR spectrum at once in the right-hand column, following the same color scheme as the initial grid. 
 The templates used in for the entire NIR spectrum follow the templates specified in Cruz et al. (2017).
 
+
+
 
 ### 3. Saving Selected Spectral Type
 Currently the code automatically saves an image of your selection into the new_types folder. We are in the process 
 of updating it so that you can select whether you would prefer to save or see another type.
 
+
 
-### Citation
+## Citation
 Copyright 2017 Ellianna Schwab and collaborators
 
 If you make use of this code, please cite Cruz et al. (2017) and the zenodo DOI for the code, coming soon!

Tests/__init__.py

@@ -0,0 +1,4 @@
+# import the TypeFinder code to this folder
+import matplotlib
+import astropy
+from TypeFinder import *

Tests/test_typing_kit.py

@@ -1,22 +1,25 @@
 import unittest
+import os
 from TypeFinder import *
 
-# class TestData(unittest.TestCase):
-#
-#     def setUp(self):
-#         '''
-#         This defines data to test
-#         '''
-#         self.data = Data('test_L3.fits')
-#
-#     def test_init(self):
-#         '''
-#         This tests that the J-H-K arrays have been sorted properly by checking their boundary conds.
-#         '''
-#
-#         self.assertTrue([0.87 <= wlength <= 1.39 for wlength in self.data.wavelength_J])
-#         self.assertTrue([1.41 <= wlength <= 1.89 for wlength in self.data.wavelength_H])
-#         self.assertTrue([1.91 <= wlength <= 2.39 for wlength in self.data.wavelength_K])
+TESTDATA_FILENAME = os.path.join(os.path.dirname(__file__), 'test_L3.fits')
+
+class TestData(unittest.TestCase):
+
+    def setUp(self):
+        '''
+        This defines data to test
+        '''
+        self.data = Data(TESTDATA_FILENAME)
+
+    def test_init(self):
+        '''
+        This tests that the J-H-K arrays have been sorted properly by checking their boundary conds.
+        '''
+
+        self.assertTrue([0.87 <= wlength <= 1.39 for wlength in self.data.wavelength_J])
+        self.assertTrue([1.41 <= wlength <= 1.89 for wlength in self.data.wavelength_H])
+        self.assertTrue([1.91 <= wlength <= 2.39 for wlength in self.data.wavelength_K])
 
 
 ### FUTURE TESTS ###

TypeFinder.py

@@ -1,6 +1,6 @@
 import numpy as np
 import matplotlib.pyplot as plt
-from pylab import *
+# from pylab import *
 from collections import defaultdict
 from astropy.io import fits
 from astropy.io import ascii
@@ -87,27 +87,27 @@ def __init__(self):
 
         for band in ['J', 'H', 'K']:
             for spectype in range(9):
-                band_data = ascii.read("templates/L{}{}_f.txt".format(spectype, band))
-                field_templates[band][spectype] = Table([band_data['col1'], band_data['col2'], band_data['col4'], band_data['col5']], \
-                                                        names = ('wavelength', 'flux', 'upper', 'lower'))
+                field_templates[band][spectype] = Table.read('templates/Cruz2017_Templates.hdf5', \
+                                                  path='field/L{}{}_template'.format(str(spectype), band))
+
 
         #Next with beta templates
         beta_templates = defaultdict(dict)
 
         for band in ['J', 'H', 'K']:
             for spectype in range(2):
-                band_data = ascii.read("templates/L{}{}_b.txt".format(spectype, band))
-                beta_templates[band][spectype] = Table([band_data['col1'], band_data['col2'], band_data['col4'], band_data['col5']], \
-                                                       names = ('wavelength', 'flux', 'upper', 'lower'))
+                beta_templates[band][spectype]= Table.read('templates/Cruz2017_Templates.hdf5', \
+                                                path='beta/L{}{}_template'.format(str(spectype), band))
+
 
         #Next with gamma templates
         gamma_templates = defaultdict(dict)
 
         for band in ['J', 'H', 'K']:
             for spectype in range(5):
-                band_data = ascii.read("templates/L{}{}_g.txt".format(spectype, band))
-                gamma_templates[band][spectype] = Table([band_data['col1'], band_data['col2'], band_data['col4'], band_data['col5']], \
-                                                        names = ('wavelength', 'flux', 'upper', 'lower'))
+                gamma_templates[band][spectype]= Table.read('templates/Cruz2017_Templates.hdf5', \
+                                                path='gamma/L{}{}_template'.format(str(spectype), band))
+
 
         self.gamma_templates = gamma_templates
         self.beta_templates = beta_templates
@@ -411,7 +411,7 @@ def last_bracketed_plot(self, gravity_type):
 
 
 ### Function definition
-def typing_kit(file_name) :
+def typing_kit(file_name, make_templates=False) :
 
     '''
     Ellianna Schwab, Kelle Cruz
@@ -426,6 +426,38 @@ def typing_kit(file_name) :
     '''
 
 
+    ##===============
+    #Optional Section to Translate Templates to HDF5
+    ##===============
+
+    if make_templates == True:
+
+        #First for field templates
+        for band in ['J', 'H', 'K']:
+            for spectype in range(9):
+                band_data = ascii.read("templates/L{}{}_f.txt".format(spectype, band))
+                T = Table([band_data['col1'], band_data['col2'], band_data['col4'], band_data['col5']], \
+                          names = ('wavelength', 'flux', 'upper', 'lower'))
+                T.write('templates/Cruz2017_Templates.hdf5', path='field/L{}{}_template'.format(str(spectype), band), append=True)
+
+        #Next with beta templates
+        for band in ['J', 'H', 'K']:
+            for spectype in range(2):
+                band_data = ascii.read("templates/L{}{}_b.txt".format(spectype, band))
+                T = Table([band_data['col1'], band_data['col2'], band_data['col4'], band_data['col5']], \
+                          names = ('wavelength', 'flux', 'upper', 'lower'))
+                T.write('templates/Cruz2017_Templates.hdf5', path='beta/L{}{}_template'.format(str(spectype), band), append=True)
+
+        #Next with gamma templates
+        for band in ['J', 'H', 'K']:
+            for spectype in range(5):
+                band_data = ascii.read("templates/L{}{}_g.txt".format(spectype, band))
+                T = Table([band_data['col1'], band_data['col2'], band_data['col4'], band_data['col5']], \
+                          names = ('wavelength', 'flux', 'upper', 'lower'))
+                T.write('templates/Cruz2017_Templates.hdf5', path='gamma/L{}{}_template'.format(str(spectype), band), append=True)
+
+
+
     ##===============
     #This defines the template arrays
     ##===============