Merge branch 'master' into #93

.gitignore

@@ -43,3 +43,7 @@ nosetests.xml
 doc/_build
 doc/html
 doc/latex
+
+.ropeproject/
+.eggs/
+*.bak

.travis.yml

@@ -0,0 +1,26 @@
+language: python
+
+python:
+  - "2.7"
+  - "3.6"
+
+install:
+  - pip install coverage
+  - pip install .
+
+script:
+  - cd tests
+  - nosetests --with-coverage --cover-package=stile --with-doctest --cover-erase test_binning.py test_stile_utils.py
+
+after_success:
+  - coverage xml
+  - codecov
+
+deploy:
+  provider: pypi
+  user: msimet
+  password:
+    secure: secure_token
+  on:
+    tags: true
+    branch: master

CHANGELOG.md

@@ -1,4 +1,5 @@
+7/11/18: Update code to python3
 3/17/16: Update documentation to Sphinx standard and add documentation build files (issue #17)
-2/17/16: Changes to correlation function plots & documentation (issue #77) 
+2/17/16: Changes to correlation function plots & documentation (issue #77)
 2/10/15: Add a setup.py installer (issue #57)
 8/26/14: Change from relying on compiled C-code corr2 to Python package TreeCorr (issue #33)

README.md

@@ -1,4 +1,4 @@
-Stile
+Stile [![Build Status](https://travis-ci.org/msimet/Stile.svg?branch=master)](https://travis-ci.org/msimet/Stile)
 =====
 
 Stile: the Systematics Tests In LEnsing pipeline
@@ -7,7 +7,7 @@ Stile: the Systematics Tests In LEnsing pipeline
 #### Installation instructions ####
 
 Stile is a pure python package, no compilation needed.  You can install it using:
-> python setup.py install
+> pip install stile
 
 #### Dependencies ####
 To run Stile, you must have:
@@ -17,17 +17,17 @@ To run Stile, you must have:
 
 We also recommend:
 
- - [TreeCorr](http://github.com/rmjarvis/TreeCorr), Mike Jarvis's 2-point correlation function code.  All of our correlation function tests involve calls to this package. 
+ - [TreeCorr](http://github.com/rmjarvis/TreeCorr), Mike Jarvis's 2-point correlation function code.  All of our correlation function tests involve calls to this package.
  - PyFITS/Astropy to handle FITS tables and images.  Stile can run on ASCII tables, but is much slower.
  - matplotlib to generate plots.
 
-More dependencies may be added in the future.  
- 
+Note that these dependencies will be automatically installed by pip. More dependencies may be added in the future.  
+
 -------------------------------------
 #### Documentation ####
 
 The documentation is available online at http://stile.readthedocs.io/.  You can also build it using Sphinx in the `doc/` directory.
- 
+
 -------------------------------------
 
 #### Current functionality ####
@@ -41,7 +41,7 @@ Right now, Stile can:
  - Generate histograms.
  - Perform any of the above tests for data with different binning schemes applied, using a simple method of specifying the bins.
  - Interface with sufficiently recent versions of the HSC pipeline.
- 
+
 -------------------------------------
 
 #### Wishlist ####
@@ -52,4 +52,3 @@ Over the upcoming months, we plan to add:
  - Automatic drivers to run as many tests as your data set allows.
  - A larger suite of example code.
  - Tests on images, and the utilities to make those tests easier.
-

setup.py

@@ -1,23 +1,32 @@
 #!/usr/bin/env python
+from setuptools import setup
+from io import open
 
-from distutils.core import setup
-try:
-    import treecorr
-except ImportError:
-    import warnings
-    warnings.warn("treecorr package cannot be imported. Installation will proceed, but you may "+
-                  "wish to install it if you would like to use the correlation functions within "+
-                  "Stile.")
-
+# read the contents of the README file
+with open('README.md', encoding="utf-8") as f:
+    long_description = f.read()
 
 setup(name='Stile',
       version='0.1',
       description='Stile: Systematics Tests in Lensing pipeline',
       author='The Stile team',
-      requirements=['numpy'],
+      install_requires=['numpy', 'treecorr', 'matplotlib', 'astropy<3'],
       author_email='[email protected]',
       url='https://github.com/msimet/Stile',
       packages=['stile', 'stile.hsc'],
       scripts=['bin/StileVisit.py', 'bin/StileVisitNoTract.py', 'bin/StileCCD.py',
-               'bin/StileCCDNoTract.py', 'bin/StilePatch.py', 'bin/StileTract.py']
+               'bin/StileCCDNoTract.py', 'bin/StilePatch.py', 'bin/StileTract.py'],
+      test_suite='nose.collector',
+      tests_require=['nose'],
+      classifiers=[
+          'Development Status :: 4 - Beta',
+          'Intended Audience :: Science/Research',
+          'License :: OSI Approved',
+          'Operating System :: MacOS :: MacOS X',
+          'Operating System :: POSIX :: Linux',
+          'Programming Language :: Python :: 2.7',
+          'Programming Language :: Python :: 3.5',
+          'Programming Language :: Python :: 3.6',
+          'Topic :: Scientific/Engineering :: Physics'
+      ]
       )

stile/file_io.py

@@ -13,7 +13,7 @@
         has_fits = False
 import numpy
 import os
-import stile_utils
+from . import stile_utils
 
 
 def ReadFITSImage(file_name, hdu=0):

stile/hsc/base_tasks.py

@@ -337,8 +337,7 @@ def generateColumns(self, dataRef, catalog, mask_tuple, raw_cols, extra_col_dict
 
         # offset for (x,y) if extra_col_dict has a column 'CCD'. Currently getMm() returns values
         # in pixel. When the pipeline is updated, we should update this line as well.
-        if dataRef.dataId.has_key('ccd') and extra_col_dict.has_key(
-               'CCD') and ('x' in raw_cols or 'y' in raw_cols):
+        if 'ccd' in dataRef.dataId and 'CCD' in extra_col_dict and ('x' in raw_cols or 'y' in raw_cols):
             xy0 = cameraGeomUtils.findCcd(dataRef.getButler().mapper.camera, cameraGeom.Id(
                 dataRef.dataId.get('ccd'))
                                        ).getPositionFromPixel(afwGeom.PointD(0., 0.)).getMm()
@@ -832,7 +831,7 @@ def run(self, visit, dataRefList):
                 catalogs.append(dataRef.get(self.catalog_type, immediate=True,
                                 flags=afwTable.SOURCE_IO_NO_FOOTPRINTS))
             except RuntimeError as e:
-                print e, ', skip this patch'
+                print(e, ', skip this patch')
         catalogs = [self.removeFlaggedObjects(catalog) for catalog in catalogs]
         sys_data_list = []
         extra_col_dicts = [{} for catalog in catalogs]

stile/stile_utils.py

@@ -10,7 +10,7 @@ def Parser():
     """
     Returns an argparse Parser object with input args used by Stile and TreeCorr.
     """
-    import treecorr_utils
+    from . import treecorr_utils
     import argparse
     p = argparse.Parser(parent=treecorr_utils.Parser())
     #TODO: add, obviously, EVERYTHING ELSE
@@ -111,7 +111,7 @@ def __init__(self, simple_stats):
         self.simple_stats = simple_stats
         for stat in self.simple_stats:
             init_str = 'self.' + stat + '=None'
-            exec init_str
+            exec(init_str)
 
         self.percentiles = None
         self.values = None
@@ -127,11 +127,11 @@ def __str__(self):
         # Loop over simple statistics and print them, if not None.  Generically if one is None then
         # all will be, so just check one.
         test_str = "test_val = self."+("%s"%self.simple_stats[0])
-        exec test_str
+        exec(test_str)
         if test_val is not None:
             for stat in self.simple_stats:
                 this_string = 'this_val = self.'+stat
-                exec this_string
+                exec(this_string)
                 ret_str += '\t%s: %f\n'%(stat, this_val)
             ret_str += '\n'
 

stile/sys_tests.py

@@ -31,7 +31,7 @@
 
 import numpy
 import stile
-import stile_utils
+from . import stile_utils
 try:
     import treecorr
     from treecorr.corr2 import corr2_valid_params
@@ -445,24 +445,24 @@ def getCF(self, correlation_function_type, data, data2=None,
                                    'data and random, and random2 if data2.')
         elif correlation_function_type in ['gg', 'm2', 'kk']:
             if random or random2:
-                print "Warning: randoms ignored for this correlation function type"
+                print("Warning: randoms ignored for this correlation function type")
         elif correlation_function_type in ['ng', 'nm', 'nk']:
             if data2 is None:
                 raise ValueError('Must include data2 for this correlation function type')
             if random2 is not None:
-                print "Warning: random2 ignored for this correlation function type"
+                print("Warning: random2 ignored for this correlation function type")
         elif correlation_function_type == 'norm':
             if data2 is None:
                 raise ValueError('Must include data2 for this correlation function type')
             if random is None:
                 raise ValueError('Must include random for this correlation function type')
             if random2 is None:
-                print "Warning: random2 ignored for this correlation function type"
+                print("Warning: random2 ignored for this correlation function type")
         elif correlation_function_type == 'kg':
             if data2 is None:
                 raise ValueError('Must include data2 for this correlation function type')
             if random is not None or random2 is not None:
-                print "Warning: randoms ignored for this correlation function type"
+                print("Warning: randoms ignored for this correlation function type")
 
         data = self.makeCatalog(data, config=treecorr_kwargs, use_as_k=use_as_k,
                                       use_chip_coords=use_chip_coords)
@@ -1104,9 +1104,9 @@ def __call__(self, array, percentiles=None, field=None, verbose=False, ignore_ba
             # It's a catalog, not a simple array
             if use_field is None:
                 raise RuntimeError('StatSysTest called on a catalog without specifying a field!')
-            if use_field not in use_array.dtype.fields.keys():
+            if use_field not in list(use_array.dtype.fields.keys()):
                 raise RuntimeError('Field %s is not in this catalog, which contains %s!'%
-                                   (use_field, use_array.dtype.fields.keys()))
+                                   (use_field, list(use_array.dtype.fields.keys())))
             # Select the appropriate field for this catalog.
             use_array = use_array[use_field]
         # Now take care of case (b):
@@ -1171,7 +1171,7 @@ def __call__(self, array, percentiles=None, field=None, verbose=False, ignore_ba
 
         # Print, if verbose=True.
         if verbose:
-            print result.__str__()
+            print(result.__str__())
 
         # Return.
         return result
@@ -1685,7 +1685,7 @@ def HistoPlot(self, data_list, field=None, binning_style=None, nbins=None,
                 elif style_use is 'manual':
                     bins = nbins
             else:
-                print "Unrecognized code for binning style, use default instead!"
+                print("Unrecognized code for binning style, use default instead!")
                 bins = nbins
 
             if weights is True:

stile/treecorr_utils.py

@@ -3,7 +3,7 @@
 program.
 """
 import numpy
-import file_io
+from . import file_io
 import treecorr
 from treecorr.corr2 import corr2_valid_params
 
@@ -90,7 +90,7 @@ def ReadTreeCorrResultsFile(file_name):
     :param file_name: The location of an output file from TreeCorr.
     :returns:         A numpy array corresponding to the data in ``file_name``.
     """
-    import stile_utils
+    from . import stile_utils
     output = file_io.ReadASCIITable(file_name, comments='#')
 
     if not len(output):