Merge pull request #230 from cdeil/setuptools-entrypoints

Move scripts to gammapy/scripts and use setuptools entry_points

.gitignore

@@ -18,6 +18,9 @@ htmlcov
 # Sphinx
 _build
 
+# Pytest
+.cache
+
 # Packages/installer info
 *.egg
 *.egg-info

scripts/gammapy-sherpa-ts-image → dev/sherpa/sherpa_ts_image.py

@@ -1,9 +1,13 @@
-#!/usr/bin/env python
+# Licensed under a 3-clause BSD style license - see LICENSE.rst
+from __future__ import (absolute_import, division, print_function,
+                        unicode_literals)
 """Compute TS image with Sherpa.
 
 TODO: describe what is done.
 """
 
+# TODO: clean up or remove!
+
 # Parse command line arguments
 
 from gammapy.utils.scripts import argparse, GammapyFormatter
@@ -38,9 +42,8 @@
                     'This can be useful to get a quick look at a significance map without '
                     'bothering fimgbin on the input images. By default significance is '
                     'computed for all pixels')
-parser.add_argument('-c', '--clobber',
-                    action='store_true', default=False,
-                    help='Overwrite output files?')
+parser.add_argument('--overwrite', action='store_true',
+                    help='Overwrite existing output file?')
 args = parser.parse_args()
 
 import logging
@@ -63,7 +66,7 @@
 # time computing the significance image but not being able to save it
 # ---------------------------------------------------------
 
-if (args.clobber == False and isfile(args.significance_image)):
+if (args.overwrite == False and isfile(args.significance_image)):
     logging.error('Output file exists: {0}'.format(args.significance_image))
     from sys import exit
     exit(-1)
@@ -184,7 +187,7 @@
                 significance = np.sign(test_source.ampl.val) * np.sqrt(np.abs(L0 - L1))
 
             except FitErr as e:
-                print e
+                print(e)
                 significance = np.nan
 
             # Print and remember values
@@ -205,5 +208,5 @@
 # Save the TS map to file
 # ---------------------------------------------------------
 logging.info('Writing significance_image: {0}'.format(args.significance_image))
-save_data('significance', args.significance_image, clobber=args.clobber)
+save_data('significance', args.significance_image, clobber=args.overwrite)
 

scripts/gammapy-ts-image → dev/ts_image.py

@@ -1,5 +1,6 @@
-#!/usr/bin/env python
 # Licensed under a 3-clause BSD style license - see LICENSE.rst
+from __future__ import (absolute_import, division, print_function,
+                        unicode_literals)
 """
 Compute source model residual images.
 
@@ -35,8 +36,8 @@
                     help='Input excess model FITS file name')
 parser.add_argument('--threshold', type=float, default=None,
                     help="Minimal required initial (before fitting) TS value, that the fit is done at all.")
-parser.add_argument('--clobber', action='store_true',
-                    help='Clobber output files?')
+parser.add_argument('--overwrite', action='store_true',
+                    help='Overwrite existing output file?')
 args = parser.parse_args()
 
 # Execute script
@@ -120,4 +121,4 @@
         results[name] = ts_results[name]
 
 logging.info('Writing {0}'.format(filename))
-dict_to_hdulist(results, maps['ExpGammaMap'].header).writeto(filename, clobber=args.clobber)
+dict_to_hdulist(results, maps['ExpGammaMap'].header).writeto(filename, clobber=args.overwrite)

docs/scripts/index.rst

@@ -1,26 +1,36 @@
 .. _scripts:
 
-Command line tools
-==================
+***************************************
+Command line tools  (`gammapy.scripts`)
+***************************************
 
-The ``gammapy/scripts`` folder contains command line tools
-that are also installed in the ``bin`` directory if you install Gammapy
-and are thus available to you if that is on your ``$PATH``. 
+.. currentmodule:: gammapy.scripts
 
-TODO: explain better how to find out where the scripts were installed,
-i.e. what the user should add to their ``$PATH``.
+Introduction
+============
 
-.. note:: For now the full list of scripts is only available here:
-   https://github.com/gammapy/gammapy/tree/master/scripts
-
-   We plan to integrate that into the online Sphinx docs ...
-   please help if you know how to do this:
-   https://github.com/gammapy/gammapy/issues/24
+Currently the `gammapy.scripts` sub-package contains the Gammapy command line tools.
 
-Here's an example of a script listed by hand ... this should be auto-generated
-by ``build_sphinx``:
+This might change though ... see the notes here:
+https://github.com/gammapy/gammapy/pull/230
 
-.. toctree::
-  :maxdepth: 1
+To be able to use them you have to install Gammapy:
 
-  gammapy-info
+.. code-block:: bash
+
+    $ pip install --user .
+
+
+For Gammapy development we recommend you run this command so that you can edit
+Gammapy and the tools and don't have to re-install after every change.
+
+.. code-block:: bash
+
+    $ pip install --user --editable .
+
+
+Reference/API
+=============
+
+.. automodapi:: gammapy.scripts
+    :no-inheritance-diagram:

gammapy/data/spectral_cube.py

@@ -419,19 +419,17 @@ def to_fits(self):
 
         return hdu_list
 
-    def writeto(self, filename, clobber=False):
+    def writeto(self, filename, overwrite=False):
         """Writes SpectralCube to fits file.
 
         Parameters
         ----------
         filename : string
             Name of output file (.fits)
-        clobber : bool
-            True: overwrites existing files of same name.
-            False: returns error if a file exists of the same name in the
-            output directory.
+        overwrite : bool
+            Overwrite existing output file?
         """
-        self.to_fits.writeto(filename, clobber)
+        self.to_fits.writeto(filename, overwrite)
 
     def __repr__(self):
         # Copied from `spectral-cube` package

gammapy/detect/cwt.py

@@ -183,10 +183,10 @@ def max_scale_image(self):
         maximum = np.argmax(self.transform, 0)
         return self.scale_array[maximum] * (self.support.sum(0) > 0)
 
-    def save_filter(self, filename, clobber=False):
+    def save_filter(self, filename, overwrite=False):
         """Save filter to file."""
         hdu = fits.PrimaryHDU(self.filter, self.header)
-        hdu.writeto(filename, clobber=clobber)
+        hdu.writeto(filename, clobber=overwrite)
         fits.append(filename, self.approx, self.header)
         fits.append(filename, self.filter + self.approx, self.header)
         fits.append(filename, self.max_scale_image(), self.header)

gammapy/detect/iterfind.py

@@ -39,7 +39,6 @@
 from ..image import disk_correlate
 
 __all__ = ['IterativeSourceDetector',
-           'run_detection',
            ]
 
 
@@ -73,7 +72,7 @@ class IterativeSourceDetector(object):
     """
 
     def __init__(self, maps, scales, max_sources=10, significance_threshold=5,
-                 max_ncall=300, debug_output_folder='', clobber=False):
+                 max_ncall=300, debug_output_folder='', overwrite=False):
         self.maps = maps
         # Note: FITS convention is to start counting pixels at 1
         y, x = np.indices(maps['counts'].shape, dtype=np.int32) + 1
@@ -88,7 +87,7 @@ def __init__(self, maps, scales, max_sources=10, significance_threshold=5,
         self.significance_threshold = significance_threshold
         self.max_ncall = max_ncall
         self.debug_output_folder = debug_output_folder
-        self.clobber = clobber
+        self.overwrite = overwrite
 
         self.sources_guess = []
         self.sources = []
@@ -116,14 +115,14 @@ def run(self):
                 for name in ['background']:
                     filename = '{0}/{1}.fits'.format(debug_folder, name)
                     logging.info('Writing {0}'.format(filename))
-                    fits.writeto(filename, self.iter_maps[name], clobber=self.clobber)
+                    fits.writeto(filename, self.iter_maps[name], clobber=self.overwrite)
 
                 # Save per iteration and scale maps
                 for name in ['significance']:
                     for scale in self.scales:
                         filename = '{0}/{1}_{2}.fits'.format(debug_folder, name, scale)
                         logging.info('Writing {0}'.format(filename))
-                        fits.writeto(filename, self.iter_maps[name][scale], clobber=self.clobber)
+                        fits.writeto(filename, self.iter_maps[name][scale], clobber=self.overwrite)
 
             self.find_peaks()
             # TODO: debug output to JSON here and for later steps
@@ -362,33 +361,3 @@ def save_json(self, filename):
         # TypeError: 1.2617354e-10 is not JSON serializable 
         with open(filename, 'w') as outfile:
             json.dump(data, outfile, indent=4)
-
-
-def run_detection(args):
-    """Run iterative source detection."""
-    # Load data
-    maps = dict()
-    for mapname in ['counts', 'background', 'exposure']:
-        filename = args[mapname]
-        logging.info('Reading {0} map: {1}'.format(mapname, filename))
-        maps[mapname] = fits.getdata(filename)
-
-    # Compute scales in pixel coordinates
-    DEG_PER_PIX = np.abs(fits.getval(args['counts'], 'CDELT1'))
-    scales_deg = args['scales']
-    scales_pix = np.array(scales_deg) / DEG_PER_PIX
-    logging.info('Number of scales: {0}'.format(len(scales_deg)))
-    logging.info('DEG_PER_PIX: {0}'.format(DEG_PER_PIX))
-    logging.info('Scales in deg: {0}'.format(scales_deg))
-    logging.info('Scales in pix: {0}'.format(scales_pix))
-
-    # Run the iterative source detection
-    detector = IterativeSourceDetector(maps=maps, scales=scales_pix,
-                                       debug_output_folder=args['debug_output_folder'],
-                                       clobber=True)
-    detector.run()
-
-    # Save the results
-    # detector.save_fits(args['output_fits'])
-    detector.save_regions(args['output_regions'])
-    # detector.save_json('detect.json')

gammapy/obs/run.py

@@ -1,6 +1,7 @@
 # Licensed under a 3-clause BSD style license - see LICENSE.rst
 """Run and RunList class"""
-from __future__ import print_function, division
+from __future__ import (absolute_import, division, print_function,
+                        unicode_literals)
 
 __all__ = ['Run', 'RunList']
 

gammapy/scripts/__init__.py

@@ -0,0 +1,35 @@
+# Licensed under a 3-clause BSD style license - see LICENSE.rst
+"""Gammapy command line tools.
+
+TODO: document how this works and how users should write their own
+command line tools.
+"""
+
+from .background_cube import *
+from .bin_cube import *
+from .bin_image import *
+from .check import *
+from .coordinate_images import *
+from .cwt import *
+from .derived_images import *
+from .detect import *
+from .find_runs import *
+from .image_decompose_a_trous import *
+from .info import *
+from .irf_info import *
+from .irf_root_to_fits import *
+from .iterative_source_detect import *
+from .look_up_image import *
+from .model_image import *
+from .pfmap import *
+from .pfsim import *
+from .pfspec import *
+from .reflected_regions import *
+from .residual_images import *
+from .root_to_fits import *
+from .sherpa_like import *
+from .sherpa_model_image import *
+from .significance_image import *
+from .simulate_source_catalog import *
+# from .ts_image import *
+from .xspec import *

gammapy/scripts/background_cube.py

@@ -0,0 +1,38 @@
+# Licensed under a 3-clause BSD style license - see LICENSE.rst
+from __future__ import (absolute_import, division, print_function,
+                        unicode_literals)
+from ..utils.scripts import get_parser
+
+__all__ = ['background_cube']
+
+
+def main(args=None):
+    parser = get_parser(background_cube)
+    parser.add_argument('run_list', type=str,
+                        help='Input run list file name')
+    parser.add_argument('exclusion_list', type=str,
+                        help='Input exclusion list file name')
+    parser.add_argument('reference_file', type=str,
+                        help='Input FITS reference cube file name')
+    parser.add_argument('out_file', type=str,
+                        help='Output FITS counts cube file name')
+    parser.add_argument('--overwrite', action='store_true',
+                        help='Overwrite existing output file?')
+    args = parser.parse_args(args)
+    background_cube(**vars(args))
+
+
+def background_cube(run_list,
+                    exclusion_list,
+                    reference_file,
+                    out_file,
+                    overwrite):
+    """Create background model cube from off runs.
+
+    TODO: explain a bit.
+    """
+    import logging
+    logging.basicConfig(level=logging.DEBUG, format='%(levelname)s - %(message)s')
+
+    # TODO: implement
+    raise NotImplementedError