Context Navigation

asapplotter.py@ 1728

Visit:

Last change on this file since 1728 was 1724, checked in by Kana Sugimoto, 15 years ago

New Development: Yes

JIRA Issue: Yes (CAS-1801)

Ready to Release: Yes

Interface Changes: Yes

What Interface Changed: two classes, CustomToolbarTkAgg and CustomToolbarCommon,

are created to a new module casatoolbar

Test Programs: run sdplot with plottype='spectra' and 'totalpower'

Put in Release Notes: Yes/No

Module(s): CASA task sdplot, sdbaseline, sdstat, sdfit

Description:

Two new classes, CustomToolbarTkAgg and CustomToolbarCommon, are
created to a new module casatoolbar in order to remove backend dependency
of sdplot(). The other code are modified accordingly.
The additional toolbar, casabar, is now default in ASAP plotter
(asapplotter.plot and asapplotter.plottp).

Property svn:eol-style set to native
Property svn:keywords set to Author Date Id Revision

File size: 47.3 KB

Rev	Line
[947]	1	from asap import rcParams, print_log, selector
[1614]	2	from asap import asaplog
[1153]	3	import matplotlib.axes
[1317]	4	import re
[203]	5
	6	class asapplotter:
[226]	7	"""
	8	The ASAP plotter.
	9	By default the plotter is set up to plot polarisations
	10	'colour stacked' and scantables across panels.
	11	Note:
	12	Currenly it only plots 'spectra' not Tsys or
	13	other variables.
	14	"""
[734]	15	def __init__(self, visible=None):
	16	self._visible = rcParams['plotter.gui']
	17	if visible is not None:
	18	self._visible = visible
[710]	19	self._plotter = self._newplotter()
[1724]	20	if self._visible and matplotlib.get_backend() == "TkAgg":
	21	from asap.casatoolbar import CustomToolbarTkAgg
	22	self._plotter.figmgr.casabar = CustomToolbarTkAgg(self)
[710]	23
[554]	24	self._panelling = None
	25	self._stacking = None
	26	self.set_panelling()
	27	self.set_stacking()
[377]	28	self._rows = None
	29	self._cols = None
[203]	30	self._autoplot = False
[525]	31	self._minmaxx = None
	32	self._minmaxy = None
[710]	33	self._datamask = None
[203]	34	self._data = None
[607]	35	self._lmap = None
[226]	36	self._title = None
[257]	37	self._ordinate = None
	38	self._abcissa = None
[709]	39	self._abcunit = None
[920]	40	self._usermask = []
	41	self._maskselection = None
	42	self._selection = selector()
[1023]	43	self._hist = rcParams['plotter.histogram']
[1723]	44	self._panellayout = self.set_panellayout(refresh=False)
[1023]	45
[920]	46	def _translate(self, instr):
	47	keys = "s b i p t".split()
	48	if isinstance(instr, str):
	49	for key in keys:
	50	if instr.lower().startswith(key):
	51	return key
	52	return None
	53
[710]	54	def _newplotter(self):
[1724]	55	backend=matplotlib.get_backend()
	56	if not self._visible:
	57	from asap.asaplot import asaplot
	58	elif backend == 'TkAgg':
[710]	59	from asap.asaplotgui import asaplotgui as asaplot
[1724]	60	elif backend == 'Qt4Agg':
	61	from asap.asaplotgui_qt4 import asaplotgui as asaplot
	62	elif backend == 'GTkAgg':
	63	from asap.asaplotgui_gtk import asaplotgui as asaplot
[710]	64	else:
	65	from asap.asaplot import asaplot
	66	return asaplot()
	67
	68
[935]	69	def plot(self, scan=None):
[203]	70	"""
[920]	71	Plot a scantable.
[203]	72	Parameters:
[920]	73	scan: a scantable
[203]	74	Note:
[920]	75	If a scantable was specified in a previous call
[203]	76	to plot, no argument has to be given to 'replot'
[920]	77	NO checking is done that the abcissas of the scantable
[203]	78	are consistent e.g. all 'channel' or all 'velocity' etc.
	79	"""
[710]	80	if self._plotter.is_dead:
	81	self._plotter = self._newplotter()
[600]	82	self._plotter.hold()
[203]	83	self._plotter.clear()
[935]	84	if not self._data and not scan:
[1101]	85	msg = "Input is not a scantable"
	86	if rcParams['verbose']:
[1612]	87	#print msg
[1614]	88	asaplog.push( msg )
	89	print_log( 'ERROR' )
[1101]	90	return
	91	raise TypeError(msg)
[1698]	92	if scan: self.set_data(scan,refresh=False)
[920]	93	self._plot(self._data)
[709]	94	if self._minmaxy is not None:
	95	self._plotter.set_limits(ylim=self._minmaxy)
[1724]	96	if self._plotter.figmgr.casabar: self._plotter.figmgr.casabar.enable_button()
[203]	97	self._plotter.release()
[1153]	98	self._plotter.tidy()
	99	self._plotter.show(hardrefresh=False)
[753]	100	print_log()
[203]	101	return
	102
[1153]	103
	104	# forwards to matplotlib axes
	105	def text(self, args, *kwargs):
	106	self._axes_callback("text", args, *kwargs)
[1358]	107	text.__doc__ = matplotlib.axes.Axes.text.__doc__
[1153]	108	def arrow(self, args, *kwargs):
	109	self._axes_callback("arrow", args, *kwargs)
[1358]	110	arrow.__doc__ = matplotlib.axes.Axes.arrow.__doc__
[1153]	111	def axvline(self, args, *kwargs):
	112	self._axes_callback("axvline", args, *kwargs)
[1358]	113	axvline.__doc__ = matplotlib.axes.Axes.axvline.__doc__
[1153]	114	def axhline(self, args, *kwargs):
	115	self._axes_callback("axhline", args, *kwargs)
[1358]	116	axhline.__doc__ = matplotlib.axes.Axes.axhline.__doc__
[1153]	117	def axvspan(self, args, *kwargs):
	118	self._axes_callback("axvspan", args, *kwargs)
	119	# hack to preventy mpl from redrawing the patch
	120	# it seem to convert the patch into lines on every draw.
	121	# This doesn't happen in a test script???
	122	del self._plotter.axes.patches[-1]
[1358]	123	axvspan.__doc__ = matplotlib.axes.Axes.axvspan.__doc__
[1232]	124
[1153]	125	def axhspan(self, args, *kwargs):
[1232]	126	self._axes_callback("axhspan", args, *kwargs)
[1153]	127	# hack to preventy mpl from redrawing the patch
	128	# it seem to convert the patch into lines on every draw.
	129	# This doesn't happen in a test script???
	130	del self._plotter.axes.patches[-1]
[1358]	131	axhspan.__doc__ = matplotlib.axes.Axes.axhspan.__doc__
[1153]	132
	133	def _axes_callback(self, axesfunc, args, *kwargs):
	134	panel = 0
	135	if kwargs.has_key("panel"):
	136	panel = kwargs.pop("panel")
	137	coords = None
	138	if kwargs.has_key("coords"):
	139	coords = kwargs.pop("coords")
	140	if coords.lower() == 'world':
	141	kwargs["transform"] = self._plotter.axes.transData
	142	elif coords.lower() == 'relative':
	143	kwargs["transform"] = self._plotter.axes.transAxes
	144	self._plotter.subplot(panel)
	145	self._plotter.axes.set_autoscale_on(False)
	146	getattr(self._plotter.axes, axesfunc)(args, *kwargs)
	147	self._plotter.show(False)
	148	self._plotter.axes.set_autoscale_on(True)
	149	# end matplotlib.axes fowarding functions
	150
[1698]	151	def set_data(self, scan, refresh=True):
[203]	152	"""
[1698]	153	Set a scantable to plot.
	154	Parameters:
	155	scan: a scantable
	156	refresh: True (default) or False. If True, the plot is
	157	replotted based on the new parameter setting(s).
	158	Otherwise,the parameter(s) are set without replotting.
[1702]	159	Note:
	160	The user specified masks and data selections will be reset
	161	if a new scantable is set. This method should be called before
	162	setting data selections (set_selection) and/or masks (set_mask).
[1698]	163	"""
	164	from asap import scantable
	165	if isinstance(scan, scantable):
	166	if self._data is not None:
	167	if scan != self._data:
	168	self._data = scan
	169	# reset
	170	self._reset()
[1702]	171	msg = "A new scantable is set to the plotter. The masks and data selections are reset."
	172	asaplog.push( msg )
	173	print_log( 'INFO' )
[1698]	174	else:
	175	self._data = scan
	176	self._reset()
	177	else:
	178	msg = "Input is not a scantable"
	179	if rcParams['verbose']:
	180	#print msg
	181	asaplog.push( msg )
	182	print_log( 'ERROR' )
	183	return
	184	raise TypeError(msg)
	185
	186	# ranges become invalid when unit changes
	187	if self._abcunit and self._abcunit != self._data.get_unit():
	188	self._minmaxx = None
	189	self._minmaxy = None
	190	self._abcunit = self._data.get_unit()
	191	self._datamask = None
	192	if refresh: self.plot()
	193
	194
	195	def set_mode(self, stacking=None, panelling=None, refresh=True):
	196	"""
[377]	197	Set the plots look and feel, i.e. what you want to see on the plot.
[203]	198	Parameters:
	199	stacking: tell the plotter which variable to plot
[1217]	200	as line colour overlays (default 'pol')
[203]	201	panelling: tell the plotter which variable to plot
	202	across multiple panels (default 'scan'
[1698]	203	refresh: True (default) or False. If True, the plot is
	204	replotted based on the new parameter setting(s).
	205	Otherwise,the parameter(s) are set without replotting.
[203]	206	Note:
	207	Valid modes are:
	208	'beam' 'Beam' 'b': Beams
	209	'if' 'IF' 'i': IFs
	210	'pol' 'Pol' 'p': Polarisations
	211	'scan' 'Scan' 's': Scans
	212	'time' 'Time' 't': Times
	213	"""
[753]	214	msg = "Invalid mode"
	215	if not self.set_panelling(panelling) or \
	216	not self.set_stacking(stacking):
	217	if rcParams['verbose']:
[1612]	218	#print msg
[1614]	219	asaplog.push( msg )
	220	print_log( 'ERROR' )
[753]	221	return
	222	else:
	223	raise TypeError(msg)
[1698]	224	if refresh and self._data: self.plot(self._data)
[203]	225	return
	226
[554]	227	def set_panelling(self, what=None):
	228	mode = what
	229	if mode is None:
	230	mode = rcParams['plotter.panelling']
	231	md = self._translate(mode)
[203]	232	if md:
[554]	233	self._panelling = md
[226]	234	self._title = None
[203]	235	return True
	236	return False
	237
[1698]	238	def set_layout(self,rows=None,cols=None,refresh=True):
[377]	239	"""
	240	Set the multi-panel layout, i.e. how many rows and columns plots
	241	are visible.
	242	Parameters:
	243	rows: The number of rows of plots
	244	cols: The number of columns of plots
[1698]	245	refresh: True (default) or False. If True, the plot is
	246	replotted based on the new parameter setting(s).
	247	Otherwise,the parameter(s) are set without replotting.
[377]	248	Note:
	249	If no argument is given, the potter reverts to its auto-plot
	250	behaviour.
	251	"""
	252	self._rows = rows
	253	self._cols = cols
[1698]	254	if refresh and self._data: self.plot(self._data)
[377]	255	return
	256
[709]	257	def set_stacking(self, what=None):
[554]	258	mode = what
[709]	259	if mode is None:
	260	mode = rcParams['plotter.stacking']
[554]	261	md = self._translate(mode)
[203]	262	if md:
	263	self._stacking = md
[226]	264	self._lmap = None
[203]	265	return True
	266	return False
	267
[1698]	268	def set_range(self,xstart=None,xend=None,ystart=None,yend=None,refresh=True):
[203]	269	"""
	270	Set the range of interest on the abcissa of the plot
	271	Parameters:
[525]	272	[x,y]start,[x,y]end: The start and end points of the 'zoom' window
[1698]	273	refresh: True (default) or False. If True, the plot is
	274	replotted based on the new parameter setting(s).
	275	Otherwise,the parameter(s) are set without replotting.
[203]	276	Note:
	277	These become non-sensical when the unit changes.
	278	use plotter.set_range() without parameters to reset
	279
	280	"""
[525]	281	if xstart is None and xend is None:
	282	self._minmaxx = None
[600]	283	else:
	284	self._minmaxx = [xstart,xend]
[525]	285	if ystart is None and yend is None:
	286	self._minmaxy = None
[600]	287	else:
[709]	288	self._minmaxy = [ystart,yend]
[1698]	289	if refresh and self._data: self.plot(self._data)
[203]	290	return
[709]	291
[1698]	292	def set_legend(self, mp=None, fontsize = None, mode = 0, refresh=True):
[203]	293	"""
	294	Specify a mapping for the legend instead of using the default
	295	indices:
	296	Parameters:
[1101]	297	mp: a list of 'strings'. This should have the same length
	298	as the number of elements on the legend and then maps
	299	to the indeces in order. It is possible to uses latex
	300	math expression. These have to be enclosed in r'',
	301	e.g. r'$x^{2}$'
	302	fontsize: The font size of the label (default None)
	303	mode: where to display the legend
	304	Any other value for loc else disables the legend:
[1096]	305	0: auto
	306	1: upper right
	307	2: upper left
	308	3: lower left
	309	4: lower right
	310	5: right
	311	6: center left
	312	7: center right
	313	8: lower center
	314	9: upper center
	315	10: center
[1698]	316	refresh: True (default) or False. If True, the plot is
	317	replotted based on the new parameter setting(s).
	318	Otherwise,the parameter(s) are set without replotting.
[203]	319
	320	Example:
[485]	321	If the data has two IFs/rest frequencies with index 0 and 1
[203]	322	for CO and SiO:
	323	plotter.set_stacking('i')
[710]	324	plotter.set_legend(['CO','SiO'])
[203]	325	plotter.plot()
[710]	326	plotter.set_legend([r'$^{12}CO$', r'SiO'])
[203]	327	"""
	328	self._lmap = mp
[1096]	329	self._plotter.legend(mode)
[1101]	330	if isinstance(fontsize, int):
	331	from matplotlib import rc as rcp
	332	rcp('legend', fontsize=fontsize)
[1698]	333	if refresh and self._data: self.plot(self._data)
[226]	334	return
	335
[1698]	336	def set_title(self, title=None, fontsize=None, refresh=True):
[710]	337	"""
	338	Set the title of the plot. If multiple panels are plotted,
	339	multiple titles have to be specified.
[1698]	340	Parameters:
	341	refresh: True (default) or False. If True, the plot is
	342	replotted based on the new parameter setting(s).
	343	Otherwise,the parameter(s) are set without replotting.
[710]	344	Example:
	345	# two panels are visible on the plotter
	346	plotter.set_title(["First Panel","Second Panel"])
	347	"""
[226]	348	self._title = title
[1101]	349	if isinstance(fontsize, int):
	350	from matplotlib import rc as rcp
	351	rcp('axes', titlesize=fontsize)
[1698]	352	if refresh and self._data: self.plot(self._data)
[226]	353	return
	354
[1698]	355	def set_ordinate(self, ordinate=None, fontsize=None, refresh=True):
[710]	356	"""
	357	Set the y-axis label of the plot. If multiple panels are plotted,
	358	multiple labels have to be specified.
[1021]	359	Parameters:
	360	ordinate: a list of ordinate labels. None (default) let
	361	data determine the labels
[1698]	362	refresh: True (default) or False. If True, the plot is
	363	replotted based on the new parameter setting(s).
	364	Otherwise,the parameter(s) are set without replotting.
[710]	365	Example:
	366	# two panels are visible on the plotter
	367	plotter.set_ordinate(["First Y-Axis","Second Y-Axis"])
	368	"""
[257]	369	self._ordinate = ordinate
[1101]	370	if isinstance(fontsize, int):
	371	from matplotlib import rc as rcp
	372	rcp('axes', labelsize=fontsize)
	373	rcp('ytick', labelsize=fontsize)
[1698]	374	if refresh and self._data: self.plot(self._data)
[257]	375	return
	376
[1698]	377	def set_abcissa(self, abcissa=None, fontsize=None, refresh=True):
[710]	378	"""
	379	Set the x-axis label of the plot. If multiple panels are plotted,
	380	multiple labels have to be specified.
[1021]	381	Parameters:
	382	abcissa: a list of abcissa labels. None (default) let
	383	data determine the labels
[1698]	384	refresh: True (default) or False. If True, the plot is
	385	replotted based on the new parameter setting(s).
	386	Otherwise,the parameter(s) are set without replotting.
[710]	387	Example:
	388	# two panels are visible on the plotter
	389	plotter.set_ordinate(["First X-Axis","Second X-Axis"])
	390	"""
[257]	391	self._abcissa = abcissa
[1101]	392	if isinstance(fontsize, int):
	393	from matplotlib import rc as rcp
	394	rcp('axes', labelsize=fontsize)
	395	rcp('xtick', labelsize=fontsize)
[1698]	396	if refresh and self._data: self.plot(self._data)
[257]	397	return
	398
[1698]	399	def set_colors(self, colmap, refresh=True):
[377]	400	"""
[1217]	401	Set the colours to be used. The plotter will cycle through
	402	these colours when lines are overlaid (stacking mode).
[1021]	403	Parameters:
[1217]	404	colmap: a list of colour names
[1698]	405	refresh: True (default) or False. If True, the plot is
	406	replotted based on the new parameter setting(s).
	407	Otherwise,the parameter(s) are set without replotting.
[710]	408	Example:
	409	plotter.set_colors("red green blue")
	410	# If for example four lines are overlaid e.g I Q U V
	411	# 'I' will be 'red', 'Q' will be 'green', U will be 'blue'
	412	# and 'V' will be 'red' again.
	413	"""
[1217]	414	if isinstance(colmap,str):
	415	colmap = colmap.split()
	416	self._plotter.palette(0, colormap=colmap)
[1698]	417	if refresh and self._data: self.plot(self._data)
[710]	418
[1217]	419	# alias for english speakers
	420	set_colours = set_colors
	421
[1698]	422	def set_histogram(self, hist=True, linewidth=None, refresh=True):
[1021]	423	"""
	424	Enable/Disable histogram-like plotting.
	425	Parameters:
	426	hist: True (default) or False. The fisrt default
	427	is taken from the .asaprc setting
	428	plotter.histogram
[1698]	429	refresh: True (default) or False. If True, the plot is
	430	replotted based on the new parameter setting(s).
	431	Otherwise,the parameter(s) are set without replotting.
[1021]	432	"""
[1023]	433	self._hist = hist
[1101]	434	if isinstance(linewidth, float) or isinstance(linewidth, int):
	435	from matplotlib import rc as rcp
	436	rcp('lines', linewidth=linewidth)
[1698]	437	if refresh and self._data: self.plot(self._data)
[1023]	438
[1698]	439	def set_linestyles(self, linestyles=None, linewidth=None, refresh=True):
[710]	440	"""
[734]	441	Set the linestyles to be used. The plotter will cycle through
	442	these linestyles when lines are overlaid (stacking mode) AND
	443	only one color has been set.
[710]	444	Parameters:
	445	linestyles: a list of linestyles to use.
	446	'line', 'dashed', 'dotted', 'dashdot',
	447	'dashdotdot' and 'dashdashdot' are
	448	possible
[1698]	449	refresh: True (default) or False. If True, the plot is
	450	replotted based on the new parameter setting(s).
	451	Otherwise,the parameter(s) are set without replotting.
[710]	452	Example:
	453	plotter.set_colors("black")
	454	plotter.set_linestyles("line dashed dotted dashdot")
	455	# If for example four lines are overlaid e.g I Q U V
	456	# 'I' will be 'solid', 'Q' will be 'dashed',
	457	# U will be 'dotted' and 'V' will be 'dashdot'.
	458	"""
	459	if isinstance(linestyles,str):
	460	linestyles = linestyles.split()
	461	self._plotter.palette(color=0,linestyle=0,linestyles=linestyles)
[1101]	462	if isinstance(linewidth, float) or isinstance(linewidth, int):
	463	from matplotlib import rc as rcp
	464	rcp('lines', linewidth=linewidth)
[1698]	465	if refresh and self._data: self.plot(self._data)
[710]	466
[1698]	467	def set_font(self, family=None, style=None, weight=None, size=None, refresh=True):
[1101]	468	"""
	469	Set font properties.
	470	Parameters:
	471	family: one of 'sans-serif', 'serif', 'cursive', 'fantasy', 'monospace'
	472	style: one of 'normal' (or 'roman'), 'italic' or 'oblique'
	473	weight: one of 'normal or 'bold'
	474	size: the 'general' font size, individual elements can be adjusted
	475	seperately
[1698]	476	refresh: True (default) or False. If True, the plot is
	477	replotted based on the new parameter setting(s).
	478	Otherwise,the parameter(s) are set without replotting.
[1101]	479	"""
	480	from matplotlib import rc as rcp
	481	if isinstance(family, str):
	482	rcp('font', family=family)
	483	if isinstance(style, str):
	484	rcp('font', style=style)
	485	if isinstance(weight, str):
	486	rcp('font', weight=weight)
	487	if isinstance(size, float) or isinstance(size, int):
	488	rcp('font', size=size)
[1698]	489	if refresh and self._data: self.plot(self._data)
[1101]	490
[1723]	491	def set_panellayout(self,layout=[],refresh=True):
	492	"""
	493	Set the layout of subplots.
	494	Parameters:
	495	layout: a list of subplots layout in figure coordinate (0-1),
	496	i.e., fraction of the figure width or height.
	497	The order of elements should be:
	498	[left, bottom, right, top, horizontal space btw panels,
	499	vertical space btw panels].
	500	refresh: True (default) or False. If True, the plot is
	501	replotted based on the new parameter setting(s).
	502	Otherwise,the parameter(s) are set without replotting.
	503	Note
	504	* When layout is not specified, the values are reset to the defaults
	505	of matplotlib.
	506	* If any element is set to be None, the current value is adopted.
	507	"""
	508	if layout == []: self._panellayout=self._reset_panellayout()
	509	else:
	510	self._panellayout=[None]*6
	511	self._panellayout[0:len(layout)]=layout
	512	#print "panel layout set to ",self._panellayout
	513	if refresh and self._data: self.plot(self._data)
	514
	515	def _reset_panellayout(self):
	516	ks=map(lambda x: 'figure.subplot.'+x,
	517	['left','bottom','right','top','hspace','wspace'])
	518	return map(matplotlib.rcParams.get,ks)
	519
[1259]	520	def plot_lines(self, linecat=None, doppler=0.0, deltachan=10, rotate=90.0,
[1146]	521	location=None):
	522	"""
[1158]	523	Plot a line catalog.
	524	Parameters:
	525	linecat: the linecatalog to plot
[1168]	526	doppler: the velocity shift to apply to the frequencies
[1158]	527	deltachan: the number of channels to include each side of the
	528	line to determine a local maximum/minimum
[1259]	529	rotate: the rotation (in degrees) )for the text label (default 90.0)
[1158]	530	location: the location of the line annotation from the 'top',
	531	'bottom' or alternate (None - the default)
[1165]	532	Notes:
	533	If the spectrum is flagged no line will be drawn in that location.
[1146]	534	"""
[1259]	535	if not self._data:
	536	raise RuntimeError("No scantable has been plotted yet.")
[1146]	537	from asap._asap import linecatalog
[1259]	538	if not isinstance(linecat, linecatalog):
	539	raise ValueError("'linecat' isn't of type linecatalog.")
	540	if not self._data.get_unit().endswith("Hz"):
	541	raise RuntimeError("Can only overlay linecatalogs when data is in frequency.")
[1153]	542	from matplotlib.numerix import ma
[1146]	543	for j in range(len(self._plotter.subplots)):
	544	self._plotter.subplot(j)
	545	lims = self._plotter.axes.get_xlim()
[1153]	546	for row in range(linecat.nrow()):
[1259]	547	# get_frequency returns MHz
	548	base = { "GHz": 1000.0, "MHz": 1.0, "Hz": 1.0e-6 }
	549	restf = linecat.get_frequency(row)/base[self._data.get_unit()]
[1165]	550	c = 299792.458
[1174]	551	freq = restf*(1.0-doppler/c)
[1146]	552	if lims[0] < freq < lims[1]:
	553	if location is None:
	554	loc = 'bottom'
[1153]	555	if row%2: loc='top'
[1146]	556	else: loc = location
[1153]	557	maxys = []
	558	for line in self._plotter.axes.lines:
	559	v = line._x
	560	asc = v[0] < v[-1]
	561
	562	idx = None
	563	if not asc:
	564	if v[len(v)-1] <= freq <= v[0]:
	565	i = len(v)-1
	566	while i>=0 and v[i] < freq:
	567	idx = i
	568	i-=1
	569	else:
	570	if v[0] <= freq <= v[len(v)-1]:
	571	i = 0
	572	while i<len(v) and v[i] < freq:
	573	idx = i
	574	i+=1
	575	if idx is not None:
	576	lower = idx - deltachan
	577	upper = idx + deltachan
	578	if lower < 0: lower = 0
	579	if upper > len(v): upper = len(v)
	580	s = slice(lower, upper)
[1167]	581	y = line._y[s]
[1165]	582	maxy = ma.maximum(y)
	583	if isinstance( maxy, float):
	584	maxys.append(maxy)
[1164]	585	if len(maxys):
	586	peak = max(maxys)
[1165]	587	if peak > self._plotter.axes.get_ylim()[1]:
	588	loc = 'bottom'
[1164]	589	else:
	590	continue
[1157]	591	self._plotter.vline_with_label(freq, peak,
	592	linecat.get_name(row),
	593	location=loc, rotate=rotate)
[1153]	594	self._plotter.show(hardrefresh=False)
[1146]	595
[1153]	596
[710]	597	def save(self, filename=None, orientation=None, dpi=None):
	598	"""
[377]	599	Save the plot to a file. The know formats are 'png', 'ps', 'eps'.
	600	Parameters:
	601	filename: The name of the output file. This is optional
	602	and autodetects the image format from the file
	603	suffix. If non filename is specified a file
	604	called 'yyyymmdd_hhmmss.png' is created in the
	605	current directory.
[709]	606	orientation: optional parameter for postscript only (not eps).
	607	'landscape', 'portrait' or None (default) are valid.
	608	If None is choosen for 'ps' output, the plot is
	609	automatically oriented to fill the page.
[710]	610	dpi: The dpi of the output non-ps plot
[377]	611	"""
[709]	612	self._plotter.save(filename,orientation,dpi)
[377]	613	return
[709]	614
[257]	615
[1698]	616	def set_mask(self, mask=None, selection=None, refresh=True):
[525]	617	"""
[734]	618	Set a plotting mask for a specific polarization.
	619	This is useful for masking out "noise" Pangle outside a source.
	620	Parameters:
[920]	621	mask: a mask from scantable.create_mask
	622	selection: the spectra to apply the mask to.
[1698]	623	refresh: True (default) or False. If True, the plot is
	624	replotted based on the new parameter setting(s).
	625	Otherwise,the parameter(s) are set without replotting.
[734]	626	Example:
[920]	627	select = selector()
	628	select.setpolstrings("Pangle")
	629	plotter.set_mask(mymask, select)
[734]	630	"""
[710]	631	if not self._data:
[920]	632	msg = "Can only set mask after a first call to plot()"
[753]	633	if rcParams['verbose']:
[1612]	634	#print msg
[1614]	635	asaplog.push( msg )
	636	print_log( 'ERROR' )
[762]	637	return
[753]	638	else:
[762]	639	raise RuntimeError(msg)
[920]	640	if len(mask):
	641	if isinstance(mask, list) or isinstance(mask, tuple):
	642	self._usermask = array(mask)
[710]	643	else:
[920]	644	self._usermask = mask
	645	if mask is None and selection is None:
	646	self._usermask = []
	647	self._maskselection = None
	648	if isinstance(selection, selector):
[947]	649	self._maskselection = {'b': selection.get_beams(),
	650	's': selection.get_scans(),
	651	'i': selection.get_ifs(),
	652	'p': selection.get_pols(),
[920]	653	't': [] }
[710]	654	else:
[920]	655	self._maskselection = None
[1698]	656	if refresh: self.plot(self._data)
[710]	657
[709]	658	def _slice_indeces(self, data):
	659	mn = self._minmaxx[0]
	660	mx = self._minmaxx[1]
	661	asc = data[0] < data[-1]
	662	start=0
	663	end = len(data)-1
	664	inc = 1
	665	if not asc:
	666	start = len(data)-1
	667	end = 0
	668	inc = -1
	669	# find min index
[1562]	670	#while start > 0 and data[start] < mn:
	671	# start+= inc
	672	minind=start
	673	for ind in xrange(start,end+inc,inc):
	674	if data[ind] > mn: break
	675	minind=ind
[709]	676	# find max index
[1562]	677	#while end > 0 and data[end] > mx:
	678	# end-=inc
	679	#if end > 0: end +=1
	680	maxind=end
	681	for ind in xrange(end,start-inc,-inc):
	682	if data[ind] < mx: break
	683	maxind=ind
	684	start=minind
	685	end=maxind
[709]	686	if start > end:
[1562]	687	return end,start+1
	688	elif start < end:
	689	return start,end+1
	690	else:
	691	return start,end
[709]	692
[710]	693	def _reset(self):
[920]	694	self._usermask = []
[710]	695	self._usermaskspectra = None
[920]	696	self.set_selection(None, False)
	697
	698	def _plot(self, scan):
[947]	699	savesel = scan.get_selection()
	700	sel = savesel + self._selection
	701	d0 = {'s': 'SCANNO', 'b': 'BEAMNO', 'i':'IFNO',
	702	'p': 'POLNO', 'c': 'CYCLENO', 't' : 'TIME' }
	703	order = [d0[self._panelling],d0[self._stacking]]
	704	sel.set_order(order)
	705	scan.set_selection(sel)
[920]	706	d = {'b': scan.getbeam, 's': scan.getscan,
	707	'i': scan.getif, 'p': scan.getpol, 't': scan._gettime }
	708
[1148]	709	polmodes = dict(zip(self._selection.get_pols(),
	710	self._selection.get_poltypes()))
	711	# this returns either a tuple of numbers or a length (ncycles)
	712	# convert this into lengths
	713	n0,nstack0 = self._get_selected_n(scan)
	714	if isinstance(n0, int): n = n0
[1175]	715	else: n = len(n0)
[1148]	716	if isinstance(nstack0, int): nstack = nstack0
[1175]	717	else: nstack = len(nstack0)
[998]	718	maxpanel, maxstack = 16,8
[920]	719	if n > maxpanel or nstack > maxstack:
[1148]	720	maxn = 0
	721	if nstack > maxstack: maxn = maxstack
	722	if n > maxpanel: maxn = maxpanel
[920]	723	msg ="Scan to be plotted contains more than %d selections.\n" \
[1148]	724	"Selecting first %d selections..." % (maxn, maxn)
[920]	725	asaplog.push(msg)
[1614]	726	print_log('WARN')
[920]	727	n = min(n,maxpanel)
[998]	728	nstack = min(nstack,maxstack)
[920]	729	if n > 1:
	730	ganged = rcParams['plotter.ganged']
[1446]	731	if self._panelling == 'i':
	732	ganged = False
[920]	733	if self._rows and self._cols:
	734	n = min(n,self._rows*self._cols)
	735	self._plotter.set_panels(rows=self._rows,cols=self._cols,
[1723]	736	# nplots=n,ganged=ganged)
	737	nplots=n,layout=self._panellayout,ganged=ganged)
[920]	738	else:
[1723]	739	# self._plotter.set_panels(rows=n,cols=0,nplots=n,ganged=ganged)
	740	self._plotter.set_panels(rows=n,cols=0,nplots=n,layout=self._panellayout,ganged=ganged)
[920]	741	else:
[1723]	742	# self._plotter.set_panels()
	743	self._plotter.set_panels(layout=self._panellayout)
[920]	744	r=0
	745	nr = scan.nrow()
	746	a0,b0 = -1,-1
	747	allxlim = []
[1018]	748	allylim = []
[920]	749	newpanel=True
	750	panelcount,stackcount = 0,0
[1002]	751	while r < nr:
[920]	752	a = d[self._panelling](r)
	753	b = d[self._stacking](r)
	754	if a > a0 and panelcount < n:
	755	if n > 1:
	756	self._plotter.subplot(panelcount)
	757	self._plotter.palette(0)
	758	#title
	759	xlab = self._abcissa and self._abcissa[panelcount] \
	760	or scan._getabcissalabel()
	761	ylab = self._ordinate and self._ordinate[panelcount] \
	762	or scan._get_ordinate_label()
	763	self._plotter.set_axes('xlabel',xlab)
	764	self._plotter.set_axes('ylabel',ylab)
	765	lbl = self._get_label(scan, r, self._panelling, self._title)
	766	if isinstance(lbl, list) or isinstance(lbl, tuple):
	767	if 0 <= panelcount < len(lbl):
	768	lbl = lbl[panelcount]
	769	else:
	770	# get default label
	771	lbl = self._get_label(scan, r, self._panelling, None)
	772	self._plotter.set_axes('title',lbl)
	773	newpanel = True
	774	stackcount =0
	775	panelcount += 1
	776	if (b > b0 or newpanel) and stackcount < nstack:
	777	y = []
	778	if len(polmodes):
	779	y = scan._getspectrum(r, polmodes[scan.getpol(r)])
	780	else:
	781	y = scan._getspectrum(r)
	782	m = scan._getmask(r)
[1146]	783	from matplotlib.numerix import logical_not, logical_and
[920]	784	if self._maskselection and len(self._usermask) == len(m):
	785	if d[self._stacking](r) in self._maskselection[self._stacking]:
	786	m = logical_and(m, self._usermask)
	787	x = scan._getabcissa(r)
[1146]	788	from matplotlib.numerix import ma, array
[1116]	789	y = ma.masked_array(y,mask=logical_not(array(m,copy=False)))
[920]	790	if self._minmaxx is not None:
	791	s,e = self._slice_indeces(x)
	792	x = x[s:e]
	793	y = y[s:e]
[1096]	794	if len(x) > 1024 and rcParams['plotter.decimate']:
	795	fac = len(x)/1024
[920]	796	x = x[::fac]
	797	y = y[::fac]
	798	llbl = self._get_label(scan, r, self._stacking, self._lmap)
	799	if isinstance(llbl, list) or isinstance(llbl, tuple):
	800	if 0 <= stackcount < len(llbl):
	801	# use user label
	802	llbl = llbl[stackcount]
	803	else:
	804	# get default label
	805	llbl = self._get_label(scan, r, self._stacking, None)
	806	self._plotter.set_line(label=llbl)
[1023]	807	plotit = self._plotter.plot
	808	if self._hist: plotit = self._plotter.hist
[1146]	809	if len(x) > 0:
	810	plotit(x,y)
	811	xlim= self._minmaxx or [min(x),max(x)]
	812	allxlim += xlim
	813	ylim= self._minmaxy or [ma.minimum(y),ma.maximum(y)]
	814	allylim += ylim
[1562]	815	else:
	816	xlim = self._minmaxx or []
	817	allxlim += xlim
	818	ylim= self._minmaxy or []
	819	allylim += ylim
[920]	820	stackcount += 1
	821	# last in colour stack -> autoscale x
[1562]	822	if stackcount == nstack and len(allxlim) > 0:
[920]	823	allxlim.sort()
[1446]	824	self._plotter.subplots[panelcount-1]['axes'].set_xlim([allxlim[0],allxlim[-1]])
[920]	825	# clear
	826	allxlim =[]
	827
	828	newpanel = False
	829	a0=a
	830	b0=b
	831	# ignore following rows
	832	if (panelcount == n) and (stackcount == nstack):
[1018]	833	# last panel -> autoscale y if ganged
[1562]	834	if rcParams['plotter.ganged'] and len(allylim) > 0:
[1018]	835	allylim.sort()
	836	self._plotter.set_limits(ylim=[allylim[0],allylim[-1]])
[998]	837	break
[920]	838	r+=1 # next row
[947]	839	#reset the selector to the scantable's original
	840	scan.set_selection(savesel)
[920]	841
	842	def set_selection(self, selection=None, refresh=True):
[1698]	843	"""
	844	Parameters:
	845	selection: a selector object (default unset the selection)
	846	refresh: True (default) or False. If True, the plot is
	847	replotted based on the new parameter setting(s).
	848	Otherwise,the parameter(s) are set without replotting.
	849	"""
[947]	850	self._selection = isinstance(selection,selector) and selection or selector()
[920]	851	d0 = {'s': 'SCANNO', 'b': 'BEAMNO', 'i':'IFNO',
	852	'p': 'POLNO', 'c': 'CYCLENO', 't' : 'TIME' }
	853	order = [d0[self._panelling],d0[self._stacking]]
[947]	854	self._selection.set_order(order)
[1698]	855	if refresh and self._data: self.plot(self._data)
[920]	856
	857	def _get_selected_n(self, scan):
[1148]	858	d1 = {'b': scan.getbeamnos, 's': scan.getscannos,
	859	'i': scan.getifnos, 'p': scan.getpolnos, 't': scan.ncycle }
	860	d2 = { 'b': self._selection.get_beams(),
	861	's': self._selection.get_scans(),
	862	'i': self._selection.get_ifs(),
	863	'p': self._selection.get_pols(),
	864	't': self._selection.get_cycles() }
[920]	865	n = d2[self._panelling] or d1[self._panelling]()
	866	nstack = d2[self._stacking] or d1[self._stacking]()
	867	return n,nstack
	868
	869	def _get_label(self, scan, row, mode, userlabel=None):
[1153]	870	if isinstance(userlabel, list) and len(userlabel) == 0:
	871	userlabel = " "
[947]	872	pms = dict(zip(self._selection.get_pols(),self._selection.get_poltypes()))
[920]	873	if len(pms):
	874	poleval = scan._getpollabel(scan.getpol(row),pms[scan.getpol(row)])
	875	else:
	876	poleval = scan._getpollabel(scan.getpol(row),scan.poltype())
	877	d = {'b': "Beam "+str(scan.getbeam(row)),
[1714]	878	#'s': scan._getsourcename(row),
	879	's': "Scan "+str(scan.getscan(row))+\
	880	" ("+str(scan._getsourcename(row))+")",
[920]	881	'i': "IF"+str(scan.getif(row)),
[964]	882	'p': poleval,
[1175]	883	't': str(scan.get_time(row)) }
[920]	884	return userlabel or d[mode]
[1153]	885
[1446]	886	def plotazel(self, scan=None, outfile=None):
[1389]	887	"""
	888	plot azimuth and elevation versus time of a scantable
	889	"""
	890	import pylab as PL
	891	from matplotlib.dates import DateFormatter, timezone, HourLocator, MinuteLocator, DayLocator
	892	from matplotlib.ticker import MultipleLocator
	893	from matplotlib.numerix import array, pi
	894	self._data = scan
[1446]	895	self._outfile = outfile
[1457]	896	dates = self._data.get_time(asdatetime=True)
[1389]	897	t = PL.date2num(dates)
	898	tz = timezone('UTC')
	899	PL.cla()
[1446]	900	#PL.ioff()
[1389]	901	PL.clf()
[1723]	902	# Adjust subplot layouts
	903	if len(self._panellayout) !=6: self.set_panellayout(refresh=False)
	904	lef, bot, rig, top, wsp, hsp = self._panellayout
	905	PL.gcf().subplots_adjust(left=lef,bottom=bot,right=rig,top=top,
	906	wspace=wsp,hspace=hsp)
	907
[1389]	908	tdel = max(t) - min(t)
	909	ax = PL.subplot(2,1,1)
	910	el = array(self._data.get_elevation())*180./pi
	911	PL.ylabel('El [deg.]')
	912	dstr = dates[0].strftime('%Y/%m/%d')
	913	if tdel > 1.0:
	914	dstr2 = dates[len(dates)-1].strftime('%Y/%m/%d')
	915	dstr = dstr + " - " + dstr2
	916	majloc = DayLocator()
	917	minloc = HourLocator(range(0,23,12))
	918	timefmt = DateFormatter("%b%d")
	919	else:
	920	timefmt = DateFormatter('%H')
	921	majloc = HourLocator()
	922	minloc = MinuteLocator(20)
	923	PL.title(dstr)
[1446]	924
	925	if tdel == 0.0:
	926	th = (t - PL.floor(t))*24.0
	927	PL.plot(th,el,'o',markersize=2, markerfacecolor='b', markeredgecolor='b')
	928	else:
	929	PL.plot_date(t,el,'o', markersize=2, markerfacecolor='b', markeredgecolor='b',tz=tz)
	930	#ax.grid(True)
	931	ax.xaxis.set_major_formatter(timefmt)
	932	ax.xaxis.set_major_locator(majloc)
	933	ax.xaxis.set_minor_locator(minloc)
[1389]	934	ax.yaxis.grid(True)
	935	yloc = MultipleLocator(30)
	936	ax.set_ylim(0,90)
	937	ax.yaxis.set_major_locator(yloc)
	938	if tdel > 1.0:
	939	labels = ax.get_xticklabels()
	940	# PL.setp(labels, fontsize=10, rotation=45)
	941	PL.setp(labels, fontsize=10)
[1446]	942
[1389]	943	# Az plot
	944	az = array(self._data.get_azimuth())*180./pi
	945	if min(az) < 0:
	946	for irow in range(len(az)):
	947	if az[irow] < 0: az[irow] += 360.0
	948
	949	ax = PL.subplot(2,1,2)
[1446]	950	#PL.xlabel('Time (UT [hour])')
[1389]	951	PL.ylabel('Az [deg.]')
[1446]	952	if tdel == 0.0:
	953	PL.plot(th,az,'o',markersize=2, markeredgecolor='b',markerfacecolor='b')
	954	else:
	955	PL.plot_date(t,az,'o', markersize=2,markeredgecolor='b',markerfacecolor='b',tz=tz)
	956	ax.xaxis.set_major_formatter(timefmt)
	957	ax.xaxis.set_major_locator(majloc)
	958	ax.xaxis.set_minor_locator(minloc)
	959	#ax.grid(True)
[1389]	960	ax.set_ylim(0,360)
	961	ax.yaxis.grid(True)
	962	#hfmt = DateFormatter('%H')
	963	#hloc = HourLocator()
	964	yloc = MultipleLocator(60)
	965	ax.yaxis.set_major_locator(yloc)
	966	if tdel > 1.0:
	967	labels = ax.get_xticklabels()
	968	PL.setp(labels, fontsize=10)
[1446]	969	PL.xlabel('Time (UT [day])')
	970	else:
	971	PL.xlabel('Time (UT [hour])')
	972
	973	#PL.ion()
[1389]	974	PL.draw()
[1446]	975	if (self._outfile is not None):
	976	PL.savefig(self._outfile)
[1389]	977
[1446]	978	def plotpointing(self, scan=None, outfile=None):
[1389]	979	"""
	980	plot telescope pointings
	981	"""
	982	import pylab as PL
	983	from matplotlib.dates import DateFormatter, timezone
	984	from matplotlib.ticker import MultipleLocator
	985	from matplotlib.numerix import array, pi, zeros
	986	self._data = scan
[1446]	987	self._outfile = outfile
[1389]	988	dir = array(self._data.get_directionval()).transpose()
	989	ra = dir[0]*180./pi
	990	dec = dir[1]*180./pi
	991	PL.cla()
[1446]	992	#PL.ioff()
[1389]	993	PL.clf()
[1723]	994	# Adjust subplot layouts
	995	if len(self._panellayout) !=6: self.set_panellayout(refresh=False)
	996	lef, bot, rig, top, wsp, hsp = self._panellayout
	997	PL.gcf().subplots_adjust(left=lef,bottom=bot,right=rig,top=top,
	998	wspace=wsp,hspace=hsp)
[1389]	999	ax = PL.axes([0.1,0.1,0.8,0.8])
	1000	ax = PL.axes([0.1,0.1,0.8,0.8])
	1001	ax.set_aspect('equal')
	1002	PL.plot(ra,dec, 'b,')
	1003	PL.xlabel('RA [deg.]')
	1004	PL.ylabel('Declination [deg.]')
	1005	PL.title('Telescope pointings')
	1006	[xmin,xmax,ymin,ymax] = PL.axis()
	1007	PL.axis([xmax,xmin,ymin,ymax])
[1446]	1008	#PL.ion()
[1389]	1009	PL.draw()
[1446]	1010	if (self._outfile is not None):
	1011	PL.savefig(self._outfile)
[1389]	1012
[1446]	1013	# plot total power data
	1014	# plotting in time is not yet implemented..
	1015	def plottp(self, scan=None, outfile=None):
	1016	if self._plotter.is_dead:
	1017	self._plotter = self._newplotter()
	1018	self._plotter.hold()
	1019	self._plotter.clear()
	1020	from asap import scantable
	1021	if not self._data and not scan:
	1022	msg = "Input is not a scantable"
	1023	if rcParams['verbose']:
[1612]	1024	#print msg
[1614]	1025	asaplog.push( msg )
	1026	print_log( 'ERROR' )
[1446]	1027	return
	1028	raise TypeError(msg)
	1029	if isinstance(scan, scantable):
	1030	if self._data is not None:
	1031	if scan != self._data:
	1032	self._data = scan
	1033	# reset
	1034	self._reset()
	1035	else:
	1036	self._data = scan
	1037	self._reset()
	1038	# ranges become invalid when abcissa changes?
	1039	#if self._abcunit and self._abcunit != self._data.get_unit():
	1040	# self._minmaxx = None
	1041	# self._minmaxy = None
	1042	# self._abcunit = self._data.get_unit()
	1043	# self._datamask = None
[1723]	1044
	1045	# Adjust subplot layouts
	1046	if len(self._panellayout) !=6: self.set_panellayout(refresh=False)
	1047	lef, bot, rig, top, wsp, hsp = self._panellayout
	1048	self._plotter.figure.subplots_adjust(
	1049	left=lef,bottom=bot,right=rig,top=top,wspace=wsp,hspace=hsp)
[1724]	1050	if self._plotter.figmgr.casabar: self._plotter.figmgr.casabar.disable_button()
[1446]	1051	self._plottp(self._data)
	1052	if self._minmaxy is not None:
	1053	self._plotter.set_limits(ylim=self._minmaxy)
	1054	self._plotter.release()
	1055	self._plotter.tidy()
	1056	self._plotter.show(hardrefresh=False)
	1057	print_log()
	1058	return
	1059
	1060	def _plottp(self,scan):
	1061	"""
	1062	private method for plotting total power data
	1063	"""
	1064	from matplotlib.numerix import ma, array, arange, logical_not
	1065	r=0
	1066	nr = scan.nrow()
	1067	a0,b0 = -1,-1
	1068	allxlim = []
	1069	allylim = []
	1070	y=[]
	1071	self._plotter.set_panels()
	1072	self._plotter.palette(0)
	1073	#title
	1074	#xlab = self._abcissa and self._abcissa[panelcount] \
	1075	# or scan._getabcissalabel()
	1076	#ylab = self._ordinate and self._ordinate[panelcount] \
	1077	# or scan._get_ordinate_label()
	1078	xlab = self._abcissa or 'row number' #or Time
	1079	ylab = self._ordinate or scan._get_ordinate_label()
	1080	self._plotter.set_axes('xlabel',xlab)
	1081	self._plotter.set_axes('ylabel',ylab)
	1082	lbl = self._get_label(scan, r, 's', self._title)
	1083	if isinstance(lbl, list) or isinstance(lbl, tuple):
	1084	# if 0 <= panelcount < len(lbl):
	1085	# lbl = lbl[panelcount]
	1086	# else:
	1087	# get default label
	1088	lbl = self._get_label(scan, r, self._panelling, None)
	1089	self._plotter.set_axes('title',lbl)
	1090	y=array(scan._get_column(scan._getspectrum,-1))
	1091	m = array(scan._get_column(scan._getmask,-1))
	1092	y = ma.masked_array(y,mask=logical_not(array(m,copy=False)))
	1093	x = arange(len(y))
	1094	# try to handle spectral data somewhat...
	1095	l,m = y.shape
	1096	if m > 1:
	1097	y=y.mean(axis=1)
	1098	plotit = self._plotter.plot
	1099	llbl = self._get_label(scan, r, self._stacking, None)
	1100	self._plotter.set_line(label=llbl)
	1101	if len(x) > 0:
	1102	plotit(x,y)
	1103
	1104
	1105	# forwards to matplotlib.Figure.text
	1106	def figtext(self, args, *kwargs):
	1107	"""
	1108	Add text to figure at location x,y (relative 0-1 coords).
	1109	This method forwards args and *kwargs to a Matplotlib method,
	1110	matplotlib.Figure.text.
	1111	See the method help for detailed information.
	1112	"""
	1113	self._plotter.text(args, *kwargs)
	1114	# end matplotlib.Figure.text forwarding function
	1115
[1723]	1116
	1117	# printing header information
	1118	def print_header(self, plot=True, fontsize=9, logger=False, selstr='', extrastr=''):
	1119	"""
	1120	print data (scantable) header on the plot and/or logger.
	1121	Parameters:
	1122	plot: whether or not print header info on the plot.
	1123	fontsize: header font size (valid only plot=True)
	1124	autoscale: whether or not autoscale the plot (valid only plot=True)
	1125	logger: whether or not print header info on the logger.
	1126	selstr: additional selection string (not verified)
	1127	extrastr: additional string to print (not verified)
	1128	"""
	1129	if not plot and not logger: return
	1130	if not self._data: raise RuntimeError("No scantable has been set yet.")
	1131	# Now header will be printed on plot and/or logger.
	1132	# Get header information and format it.
	1133	ssum=self._data.__str__()
	1134	# Print Observation header to the upper-left corner of plot
	1135	if plot:
	1136	srest=ssum[ssum.find('Rest Freqs:'):ssum.find('Abcissa:')]
	1137	shead=ssum[ssum.find('Beams:'):ssum.find('Flux Unit:')]
	1138	headstr=shead.split('\n\n')
	1139	if extrastr != '': headstr[1]=extrastr+'\n'+headstr[1]
	1140	#headstr[1]='Data File: '+(filestr or 'unknown')+'\n'+headstr[1]
	1141	headstr[0]=headstr[0]+'\n'+srest
	1142	headstr.reverse()
	1143	ssel='*Selections*\n'+(selstr+self._data.get_selection().__str__() or 'none')
	1144	headstr.append(ssel)
	1145	nstcol=len(headstr)
	1146
	1147	self._plotter.hold()
	1148	for i in range(nstcol):
	1149	self._plotter.figure.text(0.03+float(i)/nstcol,0.98,
	1150	headstr[i],
	1151	horizontalalignment='left',
	1152	verticalalignment='top',
	1153	fontsize=fontsize)
	1154	import time
	1155	self._plotter.figure.text(0.99,0.0,
	1156	time.strftime("%a %d %b %Y %H:%M:%S %Z"),
	1157	horizontalalignment='right',
	1158	verticalalignment='bottom',fontsize=8)
	1159	self._plotter.release()
	1160	del srest, shead, headstr, ssel
	1161	if logger:
	1162	asaplog.push("----------------\n Plot Summary\n----------------")
	1163	asaplog.push(extrastr)
	1164	asaplog.push(ssum[ssum.find('Beams:'):])
	1165	print_log()
	1166	del ssum
[1724]	1167
	1168

Note: See TracBrowser for help on using the repository browser.

Context Navigation

source: branches/alma/python/asapplotter.py@ 1728

Download in other formats: