Merge pull request #66 from transientskp/reimplement_dataaccessor

Reimplement dataaccessor

sourcefinder/accessors/aartfaaccasaimage.py

@@ -9,7 +9,7 @@
 
 class AartfaacCasaImage(CasaImage):
     def __init__(self, url, plane=0, beam=None):
-        super(AartfaacCasaImage, self).__init__(url, plane=0, beam=None)
+        super().__init__(url, plane=0, beam=None)
         table = casacore_table(self.url, ack=False)
         self.taustart_ts = self.parse_taustartts(table)
         self.telescope = table.getkeyword('coords')['telescope']

sourcefinder/accessors/amicasaimage.py

@@ -30,7 +30,7 @@ class AmiCasaImage(CasaImage):
     """
 
     def __init__(self, url, plane=0, beam=None):
-        super(AmiCasaImage, self).__init__(url, plane, beam)
+        super().__init__(url, plane, beam)
         table = casacore_table(self.url, ack=False)
         self.taustart_ts = self.parse_taustartts(table)
         self.tau_time = 1  # Placeholder value until properly implemented

sourcefinder/accessors/casaimage.py

@@ -24,7 +24,7 @@ class CasaImage(DataAccessor):
     """
 
     def __init__(self, url, plane=0, beam=None):
-        super(CasaImage, self).__init__()
+        # super().__init__()
         self.url = url
 
         # we don't want the table as a property since it makes the accessor

sourcefinder/accessors/dataaccessor.py

@@ -1,80 +1,80 @@
 import logging
-from math import degrees, sqrt, sin, pi, cos
 
-from sourcefinder.accessors.requiredatts import RequiredAttributesMetaclass
+import numpy
+from math import degrees, sqrt, sin, pi, cos
+from dataclasses import dataclass
+from sourcefinder.utility.coordinates import WCS
 
 logger = logging.getLogger(__name__)
 
 
-class DataAccessor(object, metaclass=RequiredAttributesMetaclass):
-    _required_attributes = [
-        'beam',
-        'centre_ra',
-        'centre_decl',
-        'data',
-        'freq_bw',
-        'freq_eff',
-        'pixelsize',
-        'tau_time',
-        'taustart_ts',
-        'url',
-        'wcs',
-    ]
-
-    def __init__(self):
-        # Sphinx only picks up the class docstring if it's under an __init__
-        # *le sigh*
-        """
-        Base class for accessors used with
-        :class:`sourcefinder.image.ImageData`.
-
-        Data accessors provide a uniform way for the ImageData class (ie,
-        generic image representation) to access the various ways in which
-        images may be stored (FITS files, arrays in memory, potentially HDF5,
-        etc).
-
-        This class cannot be instantiated directly, but should be subclassed
-        and the abstract properties provided. Note that all abstract
-        properties are required to provide a valid accessor.
-
-        Additional properties may also be provided by subclasses. However,
-        TraP components are required to degrade gracefully in the absence of
-        this optional properties.
-
-        The required attributes are as follows:
-
-        Attributes:
-            beam (tuple): Restoring beam. Tuple of three floats:
-                semi-major axis (in pixels), semi-minor axis (pixels)
-                and position angle (radians).
-            centre_ra (float): Right ascension at the central pixel of the image.
-                Units of J2000 decimal degrees.
-            centre_decl (float): Declination at the central pixel of the image.
-                Units of J2000 decimal degrees.
-            data(numpy.ndarray): Two dimensional numpy.ndarray of floating point
-                pixel values.
-                (TODO: Definitive statement on orientation/transposing.)
-            freq_bw(float): The frequency bandwidth of this image in Hz.
-            freq_eff(float): Effective frequency of the image in Hz.
-                That is, the mean frequency of all the visibility data which
-                comprises this image.
-            pixelsize(tuple): (x, y) tuple representing the size of a pixel
-                along each axis in units of degrees.
-            tau_time(float): Total time on sky in seconds.
-            taustart_ts(float): Timestamp of the first integration which
-                constitutes part of this image. MJD in seconds.
-            url(string): A (string) URL representing the location of the image
-                at time of processing.
-            wcs(:class:`sourcefinder.utility.coordinates.WCS`): An instance of
-                :py:class:`sourcefinder.utility.coordinates.WCS`,
-                describing the mapping from data pixels to sky-coordinates.
-
-        The class also provides some common functionality:
-        static methods used for parsing datafiles, and an 'extract_metadata'
-        function which provides key info in a simple dict format.
-        """
-
-    def extract_metadata(self):
+@dataclass
+class DataAccessor:
+    # Sphinx only picks up the class docstring if it's under an __init__
+    # *le sigh*
+    """
+    Base class for accessors used with
+    :class:`sourcefinder.image.ImageData`.
+
+    Data accessors provide a uniform way for the ImageData class (ie,
+    generic image representation) to access the various ways in which
+    images may be stored (FITS files, arrays in memory, potentially HDF5,
+    etc).
+
+    This class cannot be instantiated directly, but should be subclassed
+    and the abstract properties provided. Note that all abstract
+    properties are required to provide a valid accessor.
+
+    Additional properties may also be provided by subclasses. However,
+    TraP components are required to degrade gracefully in the absence of
+    this optional properties.
+
+    The required attributes are as follows:
+
+    Attributes:
+        beam (tuple): Restoring beam. Tuple of three floats:
+            semi-major axis (in pixels), semi-minor axis (pixels)
+            and position angle (radians).
+        centre_ra (float): Right ascension at the central pixel of the image.
+            Units of J2000 decimal degrees.
+        centre_decl (float): Declination at the central pixel of the image.
+            Units of J2000 decimal degrees.
+        data(numpy.ndarray): Two dimensional numpy.ndarray of floating point
+            pixel values.
+            (TODO: Definitive statement on orientation/transposing.)
+        freq_bw(float): The frequency bandwidth of this image in Hz.
+        freq_eff(float): Effective frequency of the image in Hz.
+            That is, the mean frequency of all the visibility data which
+            comprises this image.
+        pixelsize(tuple): (x, y) tuple representing the size of a pixel
+            along each axis in units of degrees.
+        tau_time(float): Total time on sky in seconds.
+        taustart_ts(float): Timestamp of the first integration which
+            constitutes part of this image. MJD in seconds.
+        url(string): A (string) URL representing the location of the image
+            at time of processing.
+        wcs(:class:`sourcefinder.utility.coordinates.WCS`): An instance of
+            :py:class:`sourcefinder.utility.coordinates.WCS`,
+            describing the mapping from data pixels to sky-coordinates.
+
+    The class also provides some common functionality:
+    static methods used for parsing datafiles, and an 'extract_metadata'
+    function which provides key info in a simple dict format.
+    """
+
+    beam: tuple
+    centre_ra: float
+    centre_decl: float
+    data: numpy.ndarray
+    freq_bw: float
+    freq_eff: float
+    pixelsize: tuple
+    tau_time: float
+    taustart_ts: float
+    url: str
+    wcs: WCS
+
+    def extract_metadata(self) -> dict:
         """
         Massage the class attributes into a flat dictionary with
         database-friendly values.
@@ -155,4 +155,4 @@ def degrees2pixels(bmaj, bmin, bpa, deltax, deltay):
             (sin(pi * bpa / 180.) ** 2) / (deltay ** 2))
         )
         theta = pi * bpa / 180
-        return (semimaj, semimin, theta)
+        return semimaj, semimin, theta

sourcefinder/accessors/fitsimage.py

@@ -12,6 +12,7 @@
 
 logger = logging.getLogger(__name__)
 
+
 class FitsImage(DataAccessor):
     """
     Use PyFITS to pull image data out of a FITS file.
@@ -21,7 +22,6 @@ class FitsImage(DataAccessor):
     header.
     """
     def __init__(self, url, plane=None, beam=None, hdu_index=0):
-        super(FitsImage, self).__init__()
         self.url = url
         self.header = self._get_header(hdu_index)
         self.wcs = self.parse_coordinates()
@@ -69,7 +69,6 @@ def read_data(self, hdu_index, plane):
         data = data.transpose()
         return data
 
-
     def parse_coordinates(self):
         """Returns a WCS object"""
         header = self.header

sourcefinder/accessors/fitsimageblob.py

@@ -16,7 +16,7 @@ class FitsImageBlob(FitsImage):
     def __init__(self, hdulist, plane=None, beam=None, hdu_index=0):
         # set the URL in case we need it during header parsing for error loggign
         self.url = "AARTFAAC streaming image"
-        super(FitsImage, self).__init__()
+        # super(FitsImage, self).__init__()
 
         self.header = self._get_header(hdulist, hdu_index)
         self.wcs = self.parse_coordinates()
@@ -42,10 +42,15 @@ def __init__(self, hdulist, plane=None, beam=None, hdu_index=0):
         if 'TELESCOP' in self.header:
             self.telescope = self.header['TELESCOP']
 
-    def _get_header(self, hdulist, hdu_index):
+    def _get_header(self, *args):
+        hdulist = args[0]
+        hdu_index = args[1]
         return hdulist[hdu_index].header
 
-    def read_data(self, hdulist, hdu_index, plane):
+    def read_data(self, *args):
+        hdulist = args[0]
+        hdu_index = args[1]
+        plane = args[2]
         hdu = hdulist[hdu_index]
         data = numpy.float64(hdu.data.squeeze())
         if plane is not None and len(data.shape) > 2:

sourcefinder/accessors/kat7casaimage.py

@@ -29,7 +29,7 @@ class Kat7CasaImage(CasaImage):
     """
 
     def __init__(self, url, plane=0, beam=None):
-        super(Kat7CasaImage, self).__init__(url, plane, beam)
+        super().__init__(url, plane, beam)
         table = casacore_table(self.url, ack=False)
         self.taustart_ts = self.parse_taustartts(table)
         self.tau_time = 1  # Placeholder value

sourcefinder/accessors/lofaraccessor.py

@@ -1,7 +1,8 @@
-from sourcefinder.accessors.dataaccessor import RequiredAttributesMetaclass
+from dataclasses import dataclass
 
 
-class LofarAccessor(object, metaclass=RequiredAttributesMetaclass):
+@dataclass
+class LofarAccessor():
     """
     Additional metadata required for processing LOFAR images through QC
     checks.
@@ -15,11 +16,10 @@ class LofarAccessor(object, metaclass=RequiredAttributesMetaclass):
         subbandwidth(float): Width of a subband in Hz.
         subbands(int): Number of subbands.
     """
-    _required_attributes = [
-        'antenna_set',
-        'ncore',
-        'nremote',
-        'nintl',
-        'subbandwidth',
-        'subbands',
-    ]
+
+    antenna_set: str
+    ncore: int
+    nremote: int
+    nintl: int
+    subbandwidth: float
+    subbands: int

sourcefinder/accessors/lofarcasaimage.py

@@ -44,7 +44,7 @@ class LofarCasaImage(CasaImage, LofarAccessor):
     """
 
     def __init__(self, url, plane=0, beam=None):
-        super(LofarCasaImage, self).__init__(url, plane, beam)
+        super().__init__(url, plane, beam)
         table = casacore_table(self.url, ack=False)
         subtables = self.open_subtables(table)
         self.taustart_ts = self.parse_taustartts(subtables)

sourcefinder/accessors/lofarfitsimage.py

@@ -4,7 +4,7 @@
 
 class LofarFitsImage(FitsImage, LofarAccessor):
     def __init__(self, url, plane=False, beam=False, hdu=0):
-        super(LofarFitsImage, self).__init__(url, plane, beam, hdu)
+        super().__init__(url, plane, beam, hdu)
         header = self._get_header(hdu)
         self.antenna_set = header['ANTENNA']
         self.ncore = header['NCORE']

sourcefinder/accessors/lofarhdf5image.py

@@ -6,7 +6,6 @@
 class LofarHdf5Image(DataAccessor):
     # Not currently instantiable; LOFAR HDF5 images are not in use
     def __init__(self, source, plane=False, beam=False):
-        super(LofarHdf5Image, self).__init__()  # Set defaults
 
         self.plane = plane
 

test/test_image.py

@@ -244,7 +244,8 @@ def testForcedFitAtNans(self):
         nanbox_radius *= boxsize_proportion
 
         nandata[int(x0 - nanbox_radius):int(x0 + nanbox_radius + 1),
-        int(y0 - nanbox_radius):int(y0 + nanbox_radius + 1)] = float('nan')
+                int(y0 - nanbox_radius):int(y0 + nanbox_radius + 1)] = \
+            float('nan')
 
         # Dump image data for manual inspection:
         # import astropy.io.fits as fits
@@ -253,7 +254,6 @@ def testForcedFitAtNans(self):
         # hdu = fits.PrimaryHDU((output_data).transpose())
         # hdu.writeto('/tmp/nandata.fits',clobber=True)
 
-
         nan_image = ImageData(nandata, beam=self.image.beam,
                               wcs=self.image.wcs)