Merge pull request #38 from broulston/SB2-Update

SB2 update for v2.0 of PyHammer (https://arxiv.org/abs/2006.01199)

.gitignore

@@ -2,4 +2,18 @@
 resources/runbefore
 PyHammerResults*
 temp_input_*
-*.csv
+*.csv
+.DS_Store
+guess_type.txt
+measure_temp_Halpha.py
+PyHammer.app/Contents/Info.plist
+PyHammer.app/Contents/MacOS/applet
+PyHammer.app/Contents/PkgInfo
+PyHammer.app/Contents/Resources/applet.icns
+PyHammer.app/Contents/Resources/applet.rsrc
+PyHammer.app/Contents/Resources/description.rtfd/TXT.rtf
+PyHammer.app/Contents/Resources/Scripts/main.scpt
+PyHammer.app/Icon
+resources/PyHammer.scpt
+resources/templates/allspec.txt
+PyHammer.app/Icon

README.md

@@ -1,26 +1,37 @@
 # PyHammer
 
 [![GitHub release](https://img.shields.io/github/release/BU-hammerTeam/PyHammer.svg)](https://github.com/BU-hammerTeam/PyHammer/releases/latest)
-[![GitHub commits](https://img.shields.io/github/commits-since/BU-hammerTeam/PyHammer/v1.2.0.svg)](https://github.com/BU-hammerTeam/PyHammer/commits/master)
+[![GitHub commits](https://img.shields.io/github/commits-since/BU-hammerTeam/PyHammer/v2.0.0.svg)](https://github.com/BU-hammerTeam/PyHammer/commits/master)
 [![GitHub issues](https://img.shields.io/github/issues/BU-hammerTeam/PyHammer.svg)](https://github.com/BU-hammerTeam/PyHammer/issues)
 [![license](https://img.shields.io/github/license/BU-hammerTeam/PyHammer.svg)](https://github.com/BU-hammerTeam/PyHammer/blob/master/license.txt)
 [![Python Supported](https://img.shields.io/badge/Python%20Supported-3-brightgreen.svg)](conda)
-[![Maintenance](https://img.shields.io/maintenance/yes/2018.svg)]()
+[![Maintenance](https://img.shields.io/maintenance/yes/2020.svg)]()
+[![Powered by Astropy](https://img.shields.io/badge/powered%20by-AstroPy-orange.svg?style=flat)](http://www.astropy.org)
 
 ### A Python Spectral Typing Suite 
 
 PyHammer is a tool developed to allow rapid and automatic spectral classification of stars according to the Morgan-Keenan classification system. Working in the range of 3,650 - 10,200 Angstroms, the automatic spectral typing algorithm compares important spectral lines to template spectra and determines the best matching spectral type, ranging from O to L type stars. This tool has the additional features that it can determine a star's metallicity ([Fe/H]) and radial velocity shifts. Once the automatic classification algorithm has run, PyHammer provides the user an interface for determining spectral types visually by comparing their spectra to provided templates.
 
+Version 2.0.0 of PyHammer adds the ability to spectral type double-lined spectroscopic binaries (SB2). This updates adds new SB2 templates which were constructed in natural units (i.e. ergs /s /Å) using GaiaDR2 distances. This is done using a library of luminosity normalized spectra. This library was created from a combination of the [MaStar](https://www.sdss.org/surveys/mastar/) survey from [SDSS-IV](https://www.sdss.org) and the [Pickles+1998](https://ui.adsabs.harvard.edu/abs/1998PASP..110..863P/abstract) library. The Pickles library was used for OBAF stars while MaStar and SDSS was used for the GKM, C, WD stars. 
+
 Modeled after [The Hammer: An IDL Spectral Typing Suite][thehammer] published in [Covey et al. 2007][covey+07] available on [GitHub][hammerGitHub].
 
 See the [PyHammer Wiki](https://github.com/BU-hammerTeam/PyHammer/wiki) for more information on how to install and use this program.
 
+Information on how the luminosity spectra are added to create SB2 templates can be found in the [Roulston+2020][Roulston_arXiv] paper.
+
 ### Publications
 
-PyHammer is detailed in our accepted Astrophysical Journal Supplements [Kesseli et al. (2017)][apjs].
+PyHammer 1.0.0 is detailed in our accepted Astrophysical Journal Supplements [Kesseli et al. (2017)][Kesseli_apjs].
+
+PyHammer 2.0.0 is detailed in our upcoming Astrophysical Journal Supplements [Roulston et al. (2020)][Roulston_arXiv]
+
+![GUI](./resources/PyHammer2_GUI.png?raw=true)
 
 [thehammer]: http://myweb.facstaff.wwu.edu/~coveyk/thehammer.html
 [covey+07]: http://adsabs.harvard.edu/abs/2007AJ....134.2398C
 [hammerGitHub]: https://github.com/jradavenport/TheHammer
 [pyhammerwiki]: https://github.com/BU-hammerTeam/PyHammer/wiki
-[apjs]: http://iopscience.iop.org/article/10.3847/1538-4365/aa656d/pdf
+[Kesseli_apjs]: http://iopscience.iop.org/article/10.3847/1538-4365/aa656d/pdf
+[Roulston_arXiv]: https://arxiv.org/abs/2006.01199
+[SB2_GitHub]: https://github.com/broulston/SB2

measure_allTemps_Indices.py

@@ -0,0 +1,88 @@
+# %load_ext autoreload
+# %autoreload 2
+
+import numpy as np
+
+from pyhamimports import *
+from spectrum import Spectrum
+import glob
+from tqdm import tqdm
+from subprocess import check_output
+
+datestr = check_output(["/bin/date","+%F"])
+datestr = datestr.decode().replace('\n', '')
+
+singleTemp_dir = "resources/templates/"
+SB2Temp_dir = "resources/templates_SB2/"
+
+singleTemp_list = np.array([os.path.basename(x)
+                            for x in glob.glob(singleTemp_dir + "*.fits")])
+singleTemp_list.sort()
+
+SB2Temp_list = np.array([os.path.basename(x)
+                         for x in glob.glob(SB2Temp_dir + "*.fits")])
+SB2Temp_list.sort()
+
+# 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 = O, B, A, F, G, K, M, L, C, WD
+single_letter_specTypes = np.array(['O', 'B', 'A', 'F', 'G', 'K', 'M', 'L', 'C', 'W'])
+specTypes = np.array(['O', 'B', 'A', 'F', 'G', 'K', 'M', 'L', 'C', 'WD'])
+
+new_tempLines_0 = np.empty(singleTemp_list.size, dtype=int)
+new_tempLines_1 = np.empty(singleTemp_list.size, dtype=int)
+new_tempLines_2 = np.empty(singleTemp_list.size, dtype=np.float64)
+new_tempLines_3 = np.ones(singleTemp_list.size, dtype=int) * 5
+new_tempLines_4 = []
+
+for ii in range(singleTemp_list.size):
+    new_tempLines_0[ii] = np.where(
+        single_letter_specTypes == singleTemp_list[ii][0])[0][0]
+    if new_tempLines_0[ii] == 9:
+        new_tempLines_1[ii] = singleTemp_list[ii][2]
+    else:
+        new_tempLines_1[ii] = singleTemp_list[ii][1]
+    if len(singleTemp_list[ii].replace("_", " ").split()) == 1:
+        new_tempLines_2[ii] = 0.
+    else:
+        new_tempLines_2[ii] = np.float64(
+            singleTemp_list[ii].replace("_", " ").split()[1])
+
+spec = Spectrum()
+ftype = None
+print("Measuring lines for single star templates:")
+for ii in tqdm(range(singleTemp_list.size)):
+    message, ftype = spec.readFile(singleTemp_dir + singleTemp_list[ii], ftype)
+    spec._lines = spec.measureLines()
+    lines = np.array(list(spec._lines.values()))[
+        np.argsort(list(spec._lines.keys()))]
+    new_tempLines_4.append(lines)
+
+SB2_index_start = new_tempLines_0.max() + 1  # 10
+new_tempLines_0 = np.append(new_tempLines_0, np.arange(
+    SB2_index_start, SB2_index_start + SB2Temp_list.size, step=1))
+new_tempLines_1 = np.append(new_tempLines_1, np.zeros(SB2Temp_list.size))
+new_tempLines_2 = np.append(new_tempLines_2, np.zeros(SB2Temp_list.size))
+new_tempLines_3 = np.append(new_tempLines_3, np.ones(SB2Temp_list.size) * 5)
+# new_tempLines_4 = new_tempLines_4
+
+spec = Spectrum()
+ftype = None
+print("Measuring lines for SB2 templates:")
+for ii, filename in enumerate(tqdm(SB2Temp_list)):
+    # temp_list = []
+    message, ftype = spec.readFile(SB2Temp_dir + filename, ftype)
+    measuredLines = spec.measureLines()
+    spec._lines = measuredLines
+    lines = np.array(list(spec._lines.values()))[
+        np.argsort(list(spec._lines.keys()))]
+    linesLabels = np.array(list(spec._lines.keys()))[
+        np.argsort(list(spec._lines.keys()))]
+    # temp_list.append(lines)
+    new_tempLines_4.append(lines)
+
+new_tempLines = [new_tempLines_0, new_tempLines_1,
+                 new_tempLines_2, new_tempLines_3, new_tempLines_4]
+
+pklPath = os.path.join(spec.thisDir, 'resources',
+                       f'tempLines_{datestr}.pickle')
+with open(pklPath, 'wb') as pklFile:
+    pickle.dump(new_tempLines, pklFile)

pyhamimports.py

@@ -8,7 +8,7 @@
 
 # Look at version specific information
 import sys
-ver = sys.version_info # Get Python version
+ver = sys.version_info  # Get Python version
 if ver.major != 3:
     sys.exit('Python 3 is required to run PyHammer.')
 # We need a function to determine which modules
@@ -21,6 +21,7 @@
 
 # Some basic python libraries
 import os
+import re
 import getopt
 import numpy as np
 from numpy import ma
@@ -35,6 +36,9 @@
 import pickle
 import csv
 from collections import OrderedDict
+from scipy.optimize import curve_fit
+from tqdm import tqdm
+import warnings
 
 # Check which PyQt version the user may have
 # installed and import the appropriate content