Move fixtures into source-tree, fix sourcefind script.

Author: timstaley

docs/standalone_notebooks/simpipe_with_intermediate_products.ipynb

@@ -52,7 +52,7 @@
     "uvw_path = 'uvw.npz'\n",
     "load_uvw = False\n",
     "image_size=1024 * u.pixel\n",
-    "cell_size=3 * u.arcsecond\n"
+    "cell_size=3 * u.arcsecond"
    ]
   },
   {
@@ -110,8 +110,7 @@
     "else:\n",
     "    with open(uvw_path, 'rb') as f:\n",
     "        npz_content = np.load(f)\n",
-    "        uvw_lambda = npz_content['uvw_lambda']\n",
-    "\n"
+    "        uvw_lambda = npz_content['uvw_lambda']"
    ]
   },
   {
@@ -126,20 +125,20 @@
     "\n",
     "# Now use UVW to generate visibilities from scratch...\n",
     "# Represent incoming data; includes transient sources, noise:\n",
-    "data_vis = visibility.calculated_summed_vis(\n",
+    "data_vis = visibility.visibilities_for_source_list(\n",
     "    pointing_centre, source_list_w_transient, uvw_lambda)\n",
     "data_vis = visibility.add_gaussian_noise(vis_noise_level, data_vis)\n",
     "\n",
     "# Model vis; only steady sources from the catalog, noise free.\n",
-    "model_vis = visibility.calculated_summed_vis(\n",
+    "model_vis = visibility.visibilities_for_source_list(\n",
     "    pointing_centre, steady_source_list, uvw_lambda)\n",
     "\n",
     "# Subtract model-generated visibilities from incoming data\n",
     "residual_vis = data_vis - model_vis\n",
     "\n",
     "# Will move this to a config option later\n",
     "kernel_support = 3\n",
-    "kernel_func = GaussianSinc(trunc=kernel_support)\n"
+    "kernel_func = GaussianSinc(trunc=kernel_support)"
    ]
   },
   {
@@ -155,7 +154,7 @@
     "                                        cell_size=cell_size,\n",
     "                                        kernel_func=kernel_func,\n",
     "                                        kernel_support=kernel_support,\n",
-    "                                        kernel_oversampling=None)\n"
+    "                                        kernel_oversampling=None)"
    ]
   },
   {
@@ -182,8 +181,7 @@
     "                                        cell_size=cell_size,\n",
     "                                        kernel_func=kernel_func,\n",
     "                                        kernel_support=kernel_support,\n",
-    "                                        kernel_oversampling=None)\n",
-    "\n"
+    "                                        kernel_oversampling=None)"
    ]
   },
   {
@@ -258,5 +256,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 1
+ "nbformat_minor": 0
 }

src/fastimgproto/fixtures/__init__.py

@@ -0,0 +1,6 @@
+"""
+Datastructures and subroutines used primarily for testing.
+
+These are kept in the source-tree as they are occasionally useful when demoing
+functionality in notebooks.
+"""

src/fastimgproto/resources/testdata/__init__.py src/fastimgproto/fixtures/data/__init__.py

@@ -122,12 +122,12 @@ def main(steady_source_list,
 
     # Now use UVW to generate visibilities from scratch...
     # Represent incoming data; includes transient sources, noise:
-    data_vis = visibility.calculated_summed_vis(
+    data_vis = visibility.visibilities_for_source_list(
         pointing_centre, source_list_w_transient, uvw_lambda)
     data_vis = visibility.add_gaussian_noise(vis_noise_level, data_vis)
 
     # Model vis; only steady sources from the catalog, noise free.
-    model_vis = visibility.calculated_summed_vis(
+    model_vis = visibility.visibilities_for_source_list(
         pointing_centre, steady_source_list, uvw_lambda)
 
     # Subtract model-generated visibilities from incoming data

src/fastimgproto/resources/testdata/simple_vis.npz src/fastimgproto/fixtures/data/simple_vis.npz

@@ -4,14 +4,19 @@
 
 import click
 from astropy.io import fits
+from fastimgproto.sourcefind.image import SourceFindImage, IslandParams
+
 # from fastimgproto.sourcefind import extract_sources
 
 
 def main(fits_image_path, detection_n_sigma, analysis_n_sigma):
     hdu0 = fits.open(fits_image_path)[0]
     imgdata = hdu0.data.squeeze()
-    sources = extract_sources(imgdata, detection_n_sigma, analysis_n_sigma)
-    return sources
+    sfimage = SourceFindImage(data=imgdata,
+                              detection_n_sigma=detection_n_sigma,
+                              analysis_n_sigma=analysis_n_sigma,
+                              )
+    return sfimage
 
 
 @click.command()
@@ -21,9 +26,8 @@ def main(fits_image_path, detection_n_sigma, analysis_n_sigma):
 @click.option('-a', '--analysis', type=click.FLOAT, default=3.,
               help="Analysis threshold (multiple of RMS above background)")
 def cli(fitsfile, detection, analysis):
-    sources = main(fitsfile, detection, analysis)
+    sfimage = main(fitsfile, detection, analysis)
     click.echo("Found the following sources:")
-    for s in sources:
-        peak_pixel, peak_value = s
-        y,x = peak_pixel
-        click.echo("({},{}):\t{}".format(x,y,peak_value))
+    for src in sfimage.islands:
+        assert isinstance(src, IslandParams)
+        click.echo("({},{}):\t{}".format(src.xbar,src.ybar,src.peak_val))

tests/fixtures/image.py src/fastimgproto/fixtures/image.py

@@ -74,7 +74,7 @@ def visibilities_for_point_source(dist_uvw, l, m, flux):
     return flux * src_n * np.exp(-2j * np.pi * np.dot(dist_uvw, src_offset))
 
 
-def calculated_summed_vis(pointing_centre, source_list, uvw):
+def visibilities_for_source_list(pointing_centre, source_list, uvw):
     """
     Generate noise-free visibilities from UVW baselines and point-sources.
 

src/fastimgproto/resources/__init__.py

@@ -1,4 +1,4 @@
-from ..fixtures.image import (
+from fastimgproto.fixtures.image import (
     evaluate_model_on_pixel_grid,
     gaussian_point_source,
 )

src/fastimgproto/scripts/simpipe.py

@@ -3,7 +3,7 @@
 import numpy as np
 
 from click.testing import CliRunner
-from fastimgproto.resources.testdata import simple_vis_npz_filepath
+from fastimgproto.fixtures.data import simple_vis_npz_filepath
 from fastimgproto.scripts.extract_lsm import cli as extract_lsm_cli
 from fastimgproto.skymodel.extraction import SumssSrc
 import csv

src/fastimgproto/scripts/sourcefind.py

@@ -1,10 +1,12 @@
 import json
-import numpy as np
 
+import numpy as np
 from click.testing import CliRunner
-from fastimgproto.resources.testdata import simple_vis_npz_filepath
-from fastimgproto.scripts.simple_imager import ConfigKeys, \
-    cli as simple_imager_cli
+from fastimgproto.fixtures.data import simple_vis_npz_filepath
+from fastimgproto.scripts.simple_imager import (
+    ConfigKeys,
+    cli as simple_imager_cli,
+)
 
 
 def test_simple_imager():
@@ -29,4 +31,4 @@ def test_simple_imager():
         with open(output_filename, 'rb') as f:
             output_data = np.load(f)
             assert 'image' in output_data
-            assert 'beam' in output_data
+            assert 'beam' in output_data

src/fastimgproto/visibility.py

@@ -1,4 +1,4 @@
-from ..fixtures.image import (
+from fastimgproto.fixtures.image import (
     evaluate_model_on_pixel_grid,
     gaussian_point_source,
     uncorrelated_gaussian_noise_background

tests/fixtures/__init__.py

@@ -2,7 +2,6 @@
 import numpy as np
 import astropy.units as u
 import fastimgproto.visibility as visibility
-import pytest
 
 
 def test_complex_gaussian_noise_generation():
@@ -19,8 +18,8 @@ def test_complex_gaussian_noise_generation():
     for component_array in np.real(complex_noise_1jy), np.imag(complex_noise_1jy):
         mean = np.mean(component_array)
         std_dev = np.std(component_array)
-        print("Mean:", mean)
-        print("S.D.:", std_dev)
+        # print("Mean:", mean)
+        # print("S.D.:", std_dev)
         assert mean < 0.001
         assert np.fabs(std_dev - 1.0)< 0.02
 
@@ -31,8 +30,8 @@ def test_complex_gaussian_noise_generation():
     for component_array in np.real(complex_noise_5jy), np.imag(complex_noise_5jy):
         mean = np.mean(component_array)
         std_dev = np.std(component_array)
-        print("Mean:", mean)
-        print("S.D.:", std_dev)
+        # print("Mean:", mean)
+        # print("S.D.:", std_dev)
         assert mean < 0.006
         assert np.fabs(std_dev - 5.0)< 0.1