def __init__(self, data_np=None, metadata=None, logger=None, name=None):
Callback.Callbacks.__init__(self)
if logger is not None:
self.logger = logger
else:
self.logger = logging.Logger('BaseImage')
if data_np is None:
data_np = numpy.zeros((1, 1))
self._data = data_np
self.metadata = {}
if metadata:
self.update_metadata(metadata)
self.order = ''
self.name = name
# make sure an image has these attributes
# TODO: this maybe should have a unique random string or something
# but we'd have to fix a lot of code that is currently checking for
# None
self.metadata.setdefault('name', None)
self._set_minmax()
self.autocuts = AutoCuts.Histogram(self.logger)
# For callbacks
for name in ('modified', ):
self.enable_callback(name)
def config_autocut_params(self, method):
index = self.autocut_methods.index(method)
self.w.auto_method.set_index(index)
# remove old params
self.w.acvbox.remove_all()
# Create new autocuts object of the right kind
ac_class = AutoCuts.get_autocuts(method)
# Build up a set of control widgets for the autocuts
# algorithm tweakable parameters
paramlst = ac_class.get_params_metadata()
# Get the canonical version of this object stored in our cache
# and make a ParamSet from it
params = self.autocuts_cache.setdefault(method, Bunch.Bunch())
self.ac_params = ParamSet.ParamSet(self.logger, params)
# Build widgets for the parameter/attribute list
w = self.ac_params.build_params(paramlst,
orientation=self.orientation)
self.ac_params.add_callback('changed', self.autocut_params_changed_cb)
# Add this set of widgets to the pane
self.w.acvbox.add_widget(w, stretch=1)
def config_autocut_params(self, method):
index = self.autocut_methods.index(method)
self.w.auto_method.set_index(index)
# remove old params
self.w.acvbox.remove_all()
# Create new autocuts object of the right kind
ac_class = AutoCuts.get_autocuts(method)
# Build up a set of control widgets for the autocuts
# algorithm tweakable parameters
paramlst = ac_class.get_params_metadata()
# Get the canonical version of this object stored in our cache
# and make a ParamSet from it
params = self.autocuts_cache.setdefault(method, Bunch.Bunch())
self.ac_params = ParamSet.ParamSet(self.logger, params)
# Build widgets for the parameter/attribute list
w = self.ac_params.build_params(paramlst, orientation=self.orientation)
self.ac_params.add_callback('changed', self.autocut_params_changed_cb)
# Add this set of widgets to the pane
self.w.acvbox.add_widget(w, stretch=1)
def __init__(self,
data_np=None,
metadata=None,
logger=None,
order=None,
name=None):
ViewerObjectBase.__init__(self,
logger=logger,
metadata=metadata,
name=name)
if data_np is None:
data_np = np.zeros((1, 1))
self._data = data_np
self.order = ''
self.name = name
# For navigating multidimensional data
self.naxispath = []
self.revnaxis = []
self._set_minmax()
self._calc_order(order)
self.autocuts = AutoCuts.Histogram(self.logger)
def __init__(self, data_np=None, metadata=None, logger=None, name=None):
ViewerObjectBase.__init__(self, logger=logger, metadata=metadata,
name=name)
if data_np is None:
data_np = numpy.zeros((1, 1))
self._data = data_np
self.order = ''
self.name = name
self._set_minmax()
self.autocuts = AutoCuts.Histogram(self.logger)
def __init__(self, fv, fitsimage):
# superclass defines some variables for us, like logger
super(Histogram, self).__init__(fv, fitsimage)
self.layertag = 'histogram-canvas'
self.histtag = None
# If True, limits X axis to lo/hi cut levels
self.xlimbycuts = True
self._split_sizes = [400, 500]
# get Histogram preferences
prefs = self.fv.get_preferences()
self.settings = prefs.create_category('plugin_Histogram')
self.settings.add_defaults(draw_then_move=True, num_bins=2048,
hist_color='aquamarine', show_stats=True,
maxdigits=7)
self.settings.load(onError='silent')
# Set up histogram control parameters
self.histcolor = self.settings.get('hist_color', 'aquamarine')
self.numbins = self.settings.get('num_bins', 2048)
self.autocuts = AutoCuts.Histogram(self.logger)
# for formatting statistics line
self.show_stats = self.settings.get('show_stats', True)
maxdigits = self.settings.get('maxdigits', 7)
self.fmt_cell = '{:< %d.%dg}' % (maxdigits - 1, maxdigits // 2)
self.dc = self.fv.get_draw_classes()
canvas = self.dc.DrawingCanvas()
canvas.enable_draw(True)
canvas.enable_edit(True)
canvas.set_drawtype('rectangle', color='cyan', linestyle='dash',
drawdims=True)
canvas.set_callback('draw-event', self.draw_cb)
canvas.set_callback('edit-event', self.edit_cb)
canvas.add_draw_mode('move', down=self.drag,
move=self.drag, up=self.update)
canvas.register_for_cursor_drawing(self.fitsimage)
canvas.set_surface(self.fitsimage)
canvas.set_draw_mode('draw')
self.canvas = canvas
fitssettings = fitsimage.get_settings()
for name in ['cuts']:
fitssettings.get_setting(name).add_callback(
'set', self.cutset_ext_cb, fitsimage)
self.gui_up = False
def pre_init(self, fitsfile=os.path.join(script_dir, "test.fits")):
#App design
self.format_string = formats
self.interface_file = os.path.join(script_dir,
"WebbFITSViewer_interface.yaml")
#Tunable settings
self.pan_scale = 0.05
self.initial_zoom = 1.0
self.zoom_speed = 0.02
#initialize the Ginga backend
self.logger = log.get_logger("ginga",
level=20,
log_file="/tmp/ginga.log")
self.autocuts = AutoCuts.Histogram(self.logger)
self.selected_data = None
self.box_corners = []
self.pre_fitsfile = fitsfile
def config_autocut_params(self, method):
index = self.autocut_methods.index(method)
self.w.auto_method.set_index(index)
# remove old params
self.w.acvbox.remove_all()
# Create new autocuts object of the right kind
ac = AutoCuts.get_autocuts(method)(self.logger)
# Build up a set of control widgets for the autocuts
# algorithm tweakable parameters
paramlst = ac.get_params_metadata()
params = self.autocuts_cache.setdefault(method, {})
self.ac_params = ParamSet.ParamSet(self.logger, params)
w = self.ac_params.build_params(paramlst)
self.ac_params.add_callback('changed', self.autocut_params_changed_cb)
self.w.acvbox.add_widget(w, stretch=1)
def config_autocut_params(self, method):
index = self.autocut_methods.index(method)
self.w.auto_method.set_index(index)
# remove old params
self.w.acvbox.remove_all()
# Create new autocuts object of the right kind
ac = AutoCuts.get_autocuts(method)(self.logger)
# Build up a set of control widgets for the autocuts
# algorithm tweakable parameters
paramlst = ac.get_params_metadata()
params = self.autocuts_cache.setdefault(method, {})
self.ac_params = ParamSet.ParamSet(self.logger, params)
w = self.ac_params.build_params(paramlst,
orientation=self.orientation)
self.ac_params.add_callback('changed', self.autocut_params_changed_cb)
self.w.acvbox.add_widget(w, stretch=1)
def __init__(self, data_np=None, metadata=None, logger=None):
Callback.Callbacks.__init__(self)
if logger != None:
self.logger = logger
else:
self.logger = logging.Logger('AstroImage')
if data_np == None:
data_np = numpy.zeros((1, 1))
self._data = data_np
self.metadata = {}
if metadata:
self.update_metadata(metadata)
self._set_minmax()
self.autocuts = AutoCuts.AutoCuts(self.logger)
# For callbacks
for name in ('modified', ):
self.enable_callback(name)
def config_autocut_params(self, method):
index = self.autocut_methods.index(method)
self.w.auto_method.setCurrentIndex(index)
# remove old params
layout = self.w.acvbox.layout()
for child in QtHelp.children(layout):
QtHelp.removeWidget(layout, child)
# Create new autocuts object of the right kind
ac = AutoCuts.get_autocuts(method)(self.logger)
# Build up a set of control widgets for the autocuts
# algorithm tweakable parameters
paramlst = ac.get_params_metadata()
params = self.autocuts_cache.setdefault(method, {})
self.ac_params = QtHelp.ParamSet(self.logger, params)
w = self.ac_params.build_params(paramlst)
self.ac_params.add_callback('changed', self.autocut_params_changed_cb)
self.w.acvbox.layout().addWidget(w, stretch=1)
def config_autocut_params(self, method):
index = self.autocut_methods.index(method)
self.w.auto_method.set_active(index)
# remove old params
for child in self.w.acvbox.get_children():
self.w.acvbox.remove(child)
# Create new autocuts object of the right kind
ac = AutoCuts.get_autocuts(method)(self.logger)
# Build up a set of control widgets for the autocuts
# algorithm tweakable parameters
paramlst = ac.get_params_metadata()
params = self.autocuts_cache.setdefault(method, {})
self.ac_params = GtkHelp.ParamSet(self.logger, params)
w = self.ac_params.build_params(paramlst)
self.ac_params.add_callback('changed', self.autocut_params_changed_cb)
self.w.acvbox.pack_start(w, fill=True, expand=True)
w.show()
def __init__(self, logger, ev_quit, options):
super(GingaVision, self).__init__()
self.logger = logger
self.ev_quit = ev_quit
from ginga.gw import Widgets, Viewers, GwHelp, GwMain
self.card = 'default'
# playback rate; changed when we know the actual rate
self.fps = 30
self.playback_rate = 1.0 / self.fps
# Use an AstroImage, not RGBImage for now because we get a
# different default (faster) scaling algorithm
self.pimage = AstroImage.AstroImage()
self.pdata = None
self.app = Widgets.Application(logger=logger)
self.app.add_callback('shutdown', self.quit)
self.top = self.app.make_window("Ginga example2")
self.top.add_callback('close', lambda *args: self.quit())
thread_pool = Task.ThreadPool(2, logger, ev_quit=ev_quit)
thread_pool.startall()
self.main = GwMain.GwMain(logger=logger,
ev_quit=ev_quit,
app=self.app,
thread_pool=thread_pool)
vbox = Widgets.VBox()
vbox.set_border_width(2)
vbox.set_spacing(1)
fi = Viewers.CanvasView(logger=logger)
fi.enable_autocuts('off')
fi.set_autocut_params('histogram')
fi.enable_autozoom('off')
fi.cut_levels(0, 255)
fi.defer_redraw = False
fi.set_bg(0.2, 0.2, 0.2)
# flip y
fi.transform(False, False, False)
fi.ui_setActive(True)
self.fitsimage = fi
# Some optomizations to smooth playback at decent FPS
fi.set_redraw_lag(self.playback_rate)
#fi.set_redraw_lag(0.0)
fi._invertY = False
# PassThruRGBMapper doesn't color map data--data is already colored
rgbmap = RGBMap.PassThruRGBMapper(self.logger)
fi.set_rgbmap(rgbmap)
# Clip cuts assumes data does not need to be scaled in cut levels--
# only clipped
fi.set_autocuts(AutoCuts.Clip(logger=self.logger))
bd = fi.get_bindings()
bd.enable_pan(True)
bd.enable_zoom(True)
bd.enable_cuts(True)
bd.enable_flip(True)
bd.enable_cmap(True)
fi.set_desired_size(512, 512)
iw = Viewers.GingaViewerWidget(viewer=fi)
vbox.add_widget(iw, stretch=1)
hbox = Widgets.HBox()
hbox.set_margins(4, 2, 4, 2)
wopen = Widgets.Button("Open File")
#wopen.clicked.connect(self.open_file)
wquit = Widgets.Button("Quit")
wquit.add_callback('activated', lambda *args: self.quit())
for w in (wopen, wquit):
hbox.add_widget(w, stretch=0)
hbox.add_widget(Widgets.Label(''), stretch=1)
vbox.add_widget(hbox, stretch=0)
self.top.set_widget(vbox)
self.top.set_title("Video Example Viewer")
def __init__(self, logger, ev_quit, options):
super(GingaVision, self).__init__()
self.logger = logger
self.ev_quit = ev_quit
from ginga.gw import Widgets, Viewers, GwMain
self.card = 'default'
# playback rate; changed when we know the actual rate
self.fps = options.fps
self.playback_rate = 1.0 / 30.0
self.pimage = RGBImage.RGBImage()
self.pdata = None
self.app = Widgets.Application(logger=logger)
self.app.add_callback('shutdown', self.quit)
self.top = self.app.make_window("Ginga example2")
self.top.add_callback('close', lambda *args: self.quit())
thread_pool = Task.ThreadPool(2, logger, ev_quit=ev_quit)
thread_pool.startall()
self.main = GwMain.GwMain(logger=logger, ev_quit=ev_quit,
app=self.app, thread_pool=thread_pool)
vbox = Widgets.VBox()
vbox.set_border_width(2)
vbox.set_spacing(1)
fi = Viewers.CanvasView(logger=logger)
fi.set_autocut_params('histogram')
fi.enable_autozoom('off')
fi.enable_autocenter('once')
fi.enable_autocuts('off')
fi.cut_levels(0, 255)
fi.scale_to(1, 1)
fi.set_bg(0.2, 0.2, 0.2)
fi.ui_set_active(True)
self.viewer = fi
if options.optimize:
# Some optimizations to smooth playback at decent FPS
# PassThruRGBMapper is the most efficient mapper
rgbmap = RGBMap.PassThruRGBMapper(self.logger)
fi.set_rgbmap(rgbmap)
# Clip cuts assumes data does not need to be scaled in cut levels--
# only clipped
fi.set_autocuts(AutoCuts.Clip(logger=self.logger))
bd = fi.get_bindings()
bd.enable_all(True)
fi.set_desired_size(512, 512)
iw = Viewers.GingaViewerWidget(viewer=fi)
vbox.add_widget(iw, stretch=1)
hbox = Widgets.HBox()
hbox.set_margins(4, 2, 4, 2)
wopen = Widgets.Button("Open File")
#wopen.clicked.connect(self.open_file)
wquit = Widgets.Button("Quit")
wquit.add_callback('activated', lambda *args: self.quit())
for w in (wopen, wquit):
hbox.add_widget(w, stretch=0)
hbox.add_widget(Widgets.Label(''), stretch=1)
vbox.add_widget(hbox, stretch=0)
self.top.set_widget(vbox)
self.top.set_title("Video Example Viewer")
def __init__(self, logger=None, rgbmap=None, settings=None):
Callback.Callbacks.__init__(self)
if logger != None:
self.logger = logger
else:
self.logger = logging.Logger('FitsImageBase')
# RGB mapper
if rgbmap:
self.rgbmap = rgbmap
else:
rgbmap = RGBMap.RGBMapper()
self.rgbmap = rgbmap
# Object that calculates auto cut levels
self.autocuts = AutoCuts.AutoCuts(self.logger)
# Dummy 1-pixel image
self.image = AstroImage.AstroImage(numpy.zeros((1, 1)),
logger=self.logger)
# for debugging
self.name = str(self)
# Create settings and set defaults
if settings == None:
settings = Settings.SettingGroup(logger=self.logger)
self.t_ = settings
# for color mapping
self.t_.addDefaults(color_map='ramp',
intensity_map='ramp',
color_algorithm='linear',
color_hashsize=65535)
for name in ('color_map', 'intensity_map', 'color_algorithm',
'color_hashsize'):
self.t_.getSetting(name).add_callback('set', self.cmap_changed_cb)
# Initialize RGBMap
cmap_name = self.t_.get('color_map', 'ramp')
try:
cm = cmap.get_cmap(cmap_name)
except KeyError:
cm = cmap.get_cmap('ramp')
rgbmap.set_cmap(cm)
imap_name = self.t_.get('intensity_map', 'ramp')
try:
im = imap.get_imap(imap_name)
except KeyError:
im = imap.get_imap('ramp')
rgbmap.set_imap(im)
hash_size = self.t_.get('color_hashsize', 65535)
rgbmap.set_hash_size(hash_size)
hash_alg = self.t_.get('color_algorithm', 'linear')
rgbmap.set_hash_algorithm(hash_alg)
rgbmap.add_callback('changed', self.rgbmap_cb)
# for cut levels
self.t_.addDefaults(locut=0.0, hicut=0.0)
for name in ('locut', 'hicut'):
self.t_.getSetting(name).add_callback('set', self.cut_levels_cb)
# for auto cut levels
self.autocuts_options = ('on', 'override', 'off')
self.t_.addDefaults(
autocuts='override',
autocut_method='histogram',
autocut_hist_pct=AutoCuts.default_autocuts_hist_pct,
autocut_bins=AutoCuts.default_autocuts_bins)
for name in ('autocuts', 'autocut_method', 'autocut_hist_pct',
'autocut_bins'):
self.t_.getSetting(name).add_callback('set', self.auto_levels_cb)
# for zooming
self.t_.addDefaults(zoomlevel=1.0,
zoom_algorithm='step',
scale_x_base=1.0,
scale_y_base=1.0,
zoom_rate=math.sqrt(2.0))
for name in ('zoom_rate', 'zoom_algorithm', 'scale_x_base',
'scale_y_base'):
self.t_.getSetting(name).add_callback('set',
self.zoomalg_change_cb)
# max/min scaling
self.t_.addDefaults(scale_max=10000.0, scale_min=0.00001)
# autozoom options
self.autozoom_options = ('on', 'override', 'off')
self.t_.addDefaults(autozoom='on')
# for panning
self.t_makebg = False
self.t_.addDefaults(reverse_pan=False, autocenter=True)
# for transforms
self.t_.addDefaults(flip_x=False, flip_y=False, swap_xy=False)
for name in ('flip_x', 'flip_y', 'swap_xy'):
self.t_.getSetting(name).add_callback('set', self.transform_cb)
# desired rotation angle
self.t_.addDefaults(rot_deg=0.0)
self.t_.getSetting('rot_deg').add_callback('set',
self.rotation_change_cb)
# misc
self.t_.addDefaults(use_embedded_profile=True, auto_orient=False)
# PRIVATE IMPLEMENTATION STATE
# image window width and height (see set_window_dimensions())
self._imgwin_wd = 1
self._imgwin_ht = 1
self._imgwin_set = False
# center (and reference) pixel in the screen image (in pixel coords)
self._ctr_x = 1
self._ctr_y = 1
# data indexes at the reference pixel (in data coords)
self._org_x = 0
self._org_y = 0
# pan position
self._pan_x = 0.0
self._pan_y = 0.0
# Origin in the data array of what is currently displayed (LL, UR)
self._org_x1 = 0
self._org_y1 = 0
self._org_x2 = 0
self._org_y2 = 0
# offsets in the screen image for drawing (in screen coords)
self._dst_x = 0
self._dst_y = 0
self._invertY = True
# offsets in the screen image (in data coords)
self._off_x = 0
self._off_y = 0
# desired scale factors
self._scale_x = 1.0
self._scale_y = 1.0
# actual scale factors produced from desired ones
self._org_scale_x = 0
self._org_scale_y = 0
self._cutout = None
self._rotimg = None
self._prergb = None
self._rgbarr = None
self.orientMap = {
# tag: (flip_x, flip_y, swap_xy)
1: (False, True, False),
2: (True, True, False),
3: (True, False, False),
4: (False, False, False),
5: (True, False, True),
6: (True, True, True),
7: (False, True, True),
8: (False, False, True),
}
# For callbacks
# TODO: we should be able to deprecate a lot of these with the new
# settings callbacks
for name in ('cut-set', 'zoom-set', 'pan-set', 'transform', 'rotate',
'image-set', 'configure', 'autocuts', 'autozoom'):
self.enable_callback(name)
def __init__(self, qtmain, logger, ev_quit, options):
super(GingaVision, self).__init__()
self.qtmain = qtmain
self.logger = logger
self.ev_quit = ev_quit
self.card = 'default'
# playback rate; changed when we know the actual rate
self.fps = 30
self.playback_rate = 1.0 / self.fps
# Use an AstroImage, not RGBImage for now because we get a
# different default (faster) scaling algorithm
self.pimage = AstroImage.AstroImage()
self.pdata = None
fi = ImageViewZoom(self.logger, render='widget')
fi.enable_autocuts('off')
fi.set_autocut_params('histogram')
fi.enable_autozoom('off')
fi.cut_levels(0, 255)
fi.defer_redraw = False
fi.set_bg(0.2, 0.2, 0.2)
# flip y
fi.transform(False, False, False)
fi.ui_setActive(True)
self.fitsimage = fi
# Some optomizations to smooth playback at decent FPS
fi.set_redraw_lag(self.playback_rate)
#fi.set_redraw_lag(0.0)
fi._invertY = False
# PassThruRGBMapper doesn't color map data--data is already colored
rgbmap = RGBMap.PassThruRGBMapper(self.logger)
fi.set_rgbmap(rgbmap)
# Clip cuts assumes data does not need to be scaled in cut levels--
# only clipped
fi.set_autocuts(AutoCuts.Clip(logger=self.logger))
bd = fi.get_bindings()
bd.enable_pan(True)
bd.enable_zoom(True)
bd.enable_cuts(True)
bd.enable_flip(True)
bd.enable_cmap(True)
w = fi.get_widget()
w.resize(512, 512)
vbox = QtGui.QVBoxLayout()
vbox.setContentsMargins(QtCore.QMargins(2, 2, 2, 2))
vbox.setSpacing(1)
vbox.addWidget(w, stretch=1)
hbox = QtGui.QHBoxLayout()
hbox.setContentsMargins(QtCore.QMargins(4, 2, 4, 2))
wopen = QtGui.QPushButton("Open File")
#wopen.clicked.connect(self.open_file)
wquit = QtGui.QPushButton("Quit")
wquit.clicked.connect(self.quit)
hbox.addStretch(1)
for w in (wopen, wquit):
hbox.addWidget(w, stretch=0)
hw = QtGui.QWidget()
hw.setLayout(hbox)
vbox.addWidget(hw, stretch=0)
vw = QtGui.QWidget()
self.setCentralWidget(vw)
vw.setLayout(vbox)
self.setWindowTitle("Video Example Viewer")