Ejemplo n.º 1
0
    def display(self, adinputs=None, **params):
        """
        Displays an image on the ds9 display, using multiple frames if
        there are multiple extensions. Saturated pixels can be displayed
        in red, and overlays can also be shown.

        Parameters
        ----------
        extname: str
            'SCI', 'VAR', or 'DQ': plane to display
        frame: int
            starting frame for display
        ignore: bool
            setting to True turns off the display
        remove_bias: bool
            attempt to subtract bias before displaying?
        threshold: str='auto'/float
            level above which to flag pixels as saturated
        tile: bool
            attempt to tile arrays before displaying?
        zscale: bool
            use zscale algorithm?
        overlay: list
            list of overlays for the display
        """
        log = self.log
        log.debug(gt.log_message("primitive", self.myself(), "starting"))

        # No-op if ignore=True
        if params["ignore"]:
            log.warning("display turned off per user request")
            return

        threshold = params['threshold']
        remove_bias = params.get('remove_bias', False)
        extname = params['extname']
        tile = params['tile']
        zscale = params['zscale']
        overlays = params['overlay']
        frame = params['frame'] if params['frame'] else 1
        overlay_index = 0
        lnd = _localNumDisplay()

        for ad in adinputs:
            # Allows elegant break from nested loops
            if frame > 16:
                log.warning("Too many images; only the first 16 are displayed")
                break

            # Threshold and bias make sense only for SCI extension
            if extname != 'SCI':
                threshold = None
                remove_bias = False
            elif threshold == 'None':
                threshold = None
            elif threshold == 'auto':
                mosaicked = ((ad.phu.get(self.timestamp_keys["mosaicDetectors"])
                              is not None) or
                             (ad.phu.get(self.timestamp_keys["tileArrays"])
                              is not None))
                has_dq = all([ext.mask is not None for ext in ad])
                if not has_dq:
                    if mosaicked:
                        log.warning("Cannot add DQ to mosaicked data; no "
                                    "threshold mask will be applied to "
                                    "{}".format(ad.filename))
                        threshold = None
                    else:
                        # addDQ operates in place so deepcopy to preserve input
                        ad = self.addDQ([deepcopy(ad)])[0]

            if remove_bias:
                if (ad.phu.get('BIASIM') or ad.phu.get('DARKIM') or
                    any(ad.hdr.get('OVERSCAN'))):
                    log.fullinfo("Bias level has already been removed from "
                                 "data; no approximate correction will be "
                                 "performed")
                else:
                    try:
                        bias_level = get_bias_level(ad)
                    except NotImplementedError:
                        # For non-GMOS instruments
                        bias_level = None

                    if bias_level is not None:
                        ad = deepcopy(ad)  # Leave original untouched!
                        log.stdinfo("Subtracting approximate bias level from "
                                    "{} for display".format(ad.filename))
                        log.fullinfo("Bias levels used: {}".format(str(bias_level)))
                        for ext, bias in zip(ad, bias_level):
                            ext.subtract(np.float32(bias) if bias is not None
                                         else 0)
                    else:
                        log.warning("Bias level not found for {}; approximate "
                                    "bias will not be removed".format(ad.filename))

            # Check whether data needs to be tiled before displaying
            # Otherwise, flatten all desired extensions into a single list
            if tile and len(ad) > 1:
                log.fullinfo("Tiling extensions together before displaying")

                # !! This is the replacement call for tileArrays() !!
                # !! mosaicADdetectors handles both GMOS and GSAOI !!
                # ad = self.mosaicADdetectors(tile=True)[0]

                ad = self.tileArrays([ad], tile_all=True)[0]

            # Each extension is an individual display item (if the data have been
            # tiled, then there'll only be one extension per AD, of course)
            for ext in ad:
                if frame > 16:
                    break

                # Squeeze the data to remove any empty dimensions (eg, raw F2 data)
                ext.operate(np.squeeze)

                # Get the data we're going to display. TODO Replace extname with attr?
                data = getattr(ext, {'SCI':'data', 'DQ':'mask',
                                    'VAR':'variance'}[extname], None)
                dqdata = ext.mask
                if data is None:
                    log.warning("No data to display in {}[{}]".format(ext.filename,
                                                                      extname))
                    continue

                # One-dimensional data (ie, extracted spectra)
                if len(data.shape) == 1:
                    continue

                # Make threshold mask if desired
                masks = []
                mask_colors = []
                if threshold is not None:
                    if threshold != 'auto':
                        satmask = data > float(threshold)
                    else:
                        if dqdata is None:
                            log.warning("No DQ plane found; cannot make "
                                        "threshold mask")
                            satmask = None
                        else:
                            satmask = (dqdata & (DQ.non_linear | DQ.saturated)) > 0
                    if satmask is not None:
                        masks.append(satmask)
                        mask_colors.append(204)

                if overlays:
                    # Could be single overlay, or list. Replicate behaviour of
                    # gt.make_lists (which we can't use because we haven't
                    # made a complete list of displayed extensions at the start
                    # in order to avoid memory bloat)
                    try:
                        overlay = overlays[overlay_index]
                    except TypeError:
                        overlay = overlays
                    except IndexError:
                        if len(overlays) == 1:
                            overlay = overlays[0]
                    masks.append(overlay)
                    mask_colors.append(206)

                # Define the display name
                if tile and extname=='SCI':
                    name = ext.filename
                elif tile:
                    name = '{}({})'.format(ext.filename, extname)
                else:
                    name = '{}({},{})'.format(ext.filename, extname,
                                              ext.hdr['EXTVER'])

                try:
                    lnd.display(data, name=name, frame=frame, zscale=zscale,
                                bpm=None if extname=='DQ' else dqdata,
                                quiet=True, masks=masks, mask_colors=mask_colors)
                except IOError:
                    log.warning("ds9 not found; cannot display input")

                frame += 1

                # Print from statistics for flats
                if extname=='SCI' and {'GMOS', 'IMAGE', 'FLAT'}.issubset(ext.tags):
                    good_data = data[dqdata==0] if dqdata is not None else data
                    mean = np.mean(good_data)
                    median = np.median(good_data)
                    log.stdinfo("Twilight flat counts for {}:".format(ext.filename))
                    log.stdinfo("    Mean value:   {:.0f}".format(mean))
                    log.stdinfo("    Median value: {:.0f}".format(median))

        return adinputs
Ejemplo n.º 2
0
    def display(self, adinputs=None, **params):
        """
        Displays an image on the ds9 display, using multiple frames if
        there are multiple extensions. Saturated pixels can be displayed
        in red, and overlays can also be shown.

        Parameters
        ----------
        extname: str
            'SCI', 'VAR', or 'DQ': plane to display
        frame: int
            starting frame for display
        ignore: bool
            setting to True turns off the display
        remove_bias: bool
            attempt to subtract bias before displaying?
        threshold: str='auto'/float
            level above which to flag pixels as saturated
        tile: bool
            attempt to tile arrays before displaying?
        zscale: bool
            use zscale algorithm?
        overlay: list
            list of overlays for the display
        """
        log = self.log
        log.debug(gt.log_message("primitive", self.myself(), "starting"))

        # No-op if ignore=True
        if params["ignore"]:
            log.warning("display turned off per user request")
            return

        threshold = params['threshold']
        remove_bias = params.get('remove_bias', False)
        extname = params['extname']
        tile = params['tile']
        zscale = params['zscale']
        overlays = params['overlay']
        frame = params['frame'] if params['frame'] else 1
        overlay_index = 0
        lnd = _localNumDisplay()

        for ad in adinputs:
            # Allows elegant break from nested loops
            if frame > 16:
                log.warning("Too many images; only the first 16 are displayed")
                break

            # Threshold and bias make sense only for SCI extension
            if extname != 'SCI':
                threshold = None
                remove_bias = False
            elif threshold == 'None':
                threshold = None
            elif threshold == 'auto':
                mosaicked = ((ad.phu.get(
                    self.timestamp_keys["mosaicDetectors"]) is not None)
                             or (ad.phu.get(self.timestamp_keys["tileArrays"])
                                 is not None))
                has_dq = all([ext.mask is not None for ext in ad])
                if not has_dq:
                    if mosaicked:
                        log.warning("Cannot add DQ to mosaicked data; no "
                                    "threshold mask will be applied to "
                                    "{}".format(ad.filename))
                        threshold = None
                    else:
                        # addDQ operates in place so deepcopy to preserve input
                        ad = self.addDQ([deepcopy(ad)])[0]

            if remove_bias:
                if (ad.phu.get('BIASIM') or ad.phu.get('DARKIM')
                        or any(ad.hdr.get('OVERSCAN'))):
                    log.fullinfo("Bias level has already been removed from "
                                 "data; no approximate correction will be "
                                 "performed")
                else:
                    try:
                        bias_level = get_bias_level(ad)
                    except NotImplementedError:
                        # For non-GMOS instruments
                        bias_level = None

                    if bias_level is not None:
                        ad = deepcopy(ad)  # Leave original untouched!
                        log.stdinfo("Subtracting approximate bias level from "
                                    "{} for display".format(ad.filename))
                        log.fullinfo("Bias levels used: {}".format(
                            str(bias_level)))
                        for ext, bias in zip(ad, bias_level):
                            ext.subtract(
                                np.float32(bias) if bias is not None else 0)
                    else:
                        log.warning("Bias level not found for {}; approximate "
                                    "bias will not be removed".format(
                                        ad.filename))

            # Check whether data needs to be tiled before displaying
            # Otherwise, flatten all desired extensions into a single list
            if tile and len(ad) > 1:
                log.fullinfo("Tiling extensions together before displaying")

                # !! This is the replacement call for tileArrays() !!
                # !! mosaicADdetectors handles both GMOS and GSAOI !!
                # ad = self.mosaicADdetectors(tile=True)[0]

                ad = self.tileArrays([ad], tile_all=True)[0]

            # Each extension is an individual display item (if the data have been
            # tiled, then there'll only be one extension per AD, of course)
            for ext in ad:
                if frame > 16:
                    break

                # Squeeze the data to remove any empty dimensions (eg, raw F2 data)
                ext.operate(np.squeeze)

                # Get the data we're going to display. TODO Replace extname with attr?
                data = getattr(ext, {
                    'SCI': 'data',
                    'DQ': 'mask',
                    'VAR': 'variance'
                }[extname], None)
                dqdata = ext.mask
                if data is None:
                    log.warning("No data to display in {}[{}]".format(
                        ext.filename, extname))
                    continue

                # One-dimensional data (ie, extracted spectra)
                if len(data.shape) == 1:
                    continue

                # Make threshold mask if desired
                masks = []
                mask_colors = []
                if threshold is not None:
                    if threshold != 'auto':
                        satmask = data > float(threshold)
                    else:
                        if dqdata is None:
                            log.warning("No DQ plane found; cannot make "
                                        "threshold mask")
                            satmask = None
                        else:
                            satmask = (dqdata &
                                       (DQ.non_linear | DQ.saturated)) > 0
                    if satmask is not None:
                        masks.append(satmask)
                        mask_colors.append(204)

                if overlays:
                    # Could be single overlay, or list. Replicate behaviour of
                    # gt.make_lists (which we can't use because we haven't
                    # made a complete list of displayed extensions at the start
                    # in order to avoid memory bloat)
                    try:
                        overlay = overlays[overlay_index]
                    except TypeError:
                        overlay = overlays
                    except IndexError:
                        if len(overlays) == 1:
                            overlay = overlays[0]
                    masks.append(overlay)
                    mask_colors.append(206)

                # Define the display name
                if tile and extname == 'SCI':
                    name = ext.filename
                elif tile:
                    name = '{}({})'.format(ext.filename, extname)
                else:
                    name = '{}({},{})'.format(ext.filename, extname,
                                              ext.hdr['EXTVER'])

                try:
                    lnd.display(data,
                                name=name,
                                frame=frame,
                                zscale=zscale,
                                bpm=None if extname == 'DQ' else dqdata,
                                quiet=True,
                                masks=masks,
                                mask_colors=mask_colors)
                except IOError:
                    log.warning("ds9 not found; cannot display input")

                frame += 1

                # Print from statistics for flats
                if extname == 'SCI' and {'GMOS', 'IMAGE', 'FLAT'}.issubset(
                        ext.tags):
                    good_data = data[dqdata ==
                                     0] if dqdata is not None else data
                    mean = np.mean(good_data)
                    median = np.median(good_data)
                    log.stdinfo("Twilight flat counts for {}:".format(
                        ext.filename))
                    log.stdinfo("    Mean value:   {:.0f}".format(mean))
                    log.stdinfo("    Median value: {:.0f}".format(median))

        return adinputs
Ejemplo n.º 3
0
    def standardizeInstrumentHeaders(self, adinputs=None, suffix=None):
        """
        This primitive is used to make the changes and additions to the
        keywords in the headers of GMOS data, specifically.

        Parameters
        ----------
        suffix: str
            suffix to be added to output files
        """
        log = self.log
        log.debug(gt.log_message("primitive", self.myself(), "starting"))
        timestamp_key = self.timestamp_keys[self.myself()]

        for ad in adinputs:
            if ad.phu.get(timestamp_key):
                log.warning("No changes will be made to {}, since it has "
                            "already been processed by "
                            "standardizeInstrumentHeaders".format(ad.filename))
                continue

            # Standardize the headers of the input AstroData object. Update the
            # keywords in the headers that are specific to GMOS.
            log.status("Updating keywords that are specific to GMOS")

            # #M Some of the header keywords are wrong for certain types of
            # #M Hamamatsu data. This is temporary fix until GMOS-S DC is fixed
            # if ad.detector_name(pretty=True) == "Hamamatsu-S":
            #     log.status("Fixing headers for GMOS-S Hamamatsu data")
            #     # Image extension headers appear to be correct - MS 2014-10-01
            #     #     correct_image_extensions=Flase
            #     # As does the DATE-OBS but as this seemed to break even after
            #     # apparently being fixed, still perform this check. - MS
            #     hdulist = ad.to_hdulist()
            #     # correct_headers(hdulist, logger=log,
            #     #                 correct_image_extensions=False)
            #     # When we create the new AD object, it needs to retain the
            #     # filename information
            #     orig_path = ad.path
            #     ad = astrodata.open(hdulist)
            #     ad.path = orig_path

            # KL Commissioning GMOS-N Hamamatsu.  Headers are not fully
            # KL settled yet.
            if ad.detector_name(pretty=True) == "Hamamatsu-N":
                log.status("Fixing headers for GMOS-N Hamamatsu data")
                try:
                    ad.phu['DATE-OBS'] = ad.phu['DATE']
                except KeyError:
                    pass

            # Update keywords in the image extensions. The descriptors return
            # the true values on unprepared data.
            descriptors = ['pixel_scale', 'read_noise', 'gain_setting',
                               'gain', 'saturation_level']
            for desc in descriptors:
                keyword = ad._keyword_for(desc)
                comment = self.keyword_comments[keyword]
                dv = getattr(ad, desc)()
                if isinstance(dv, list):
                    for ext, value in zip(ad, dv):
                        ext.hdr.set(keyword, value, comment)
                else:
                    ad.hdr.set(keyword, dv, comment)

            if 'SPECT' in ad.tags:
                kw = ad._keyword_for('dispersion_axis')
                ad.hdr.set(kw, 1, self.keyword_comments[kw])

            # And the bias level too!
            bias_level = get_bias_level(adinput=ad,
                                        estimate='qa' in self.mode)
            for ext, bias in zip(ad, bias_level):
                if bias is not None:
                    ext.hdr.set('RAWBIAS', bias,
                                self.keyword_comments['RAWBIAS'])

            # Timestamp and update filename
            gt.mark_history(ad, primname=self.myself(), keyword=timestamp_key)
            ad.update_filename(suffix=suffix, strip=True)
        return adinputs