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source: trunk/python/asapplotter.py @ 1904

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Last change on this file since 1904 was 1897, checked in by Malte Marquarding, 14 years ago
Ticket #202: add offset keyword to asapplotter.set_range
Property svn:eol-style set to `native` Property svn:keywords set to `Author Date Id Revision`
File size: 52.4 KB

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[1824]	1	from asap.parameters import rcParams
	2	from asap.selector import selector
	3	from asap.scantable import scantable
[1862]	4	from asap.logging import asaplog, asaplog_post_dec
[1153]	5	import matplotlib.axes
[1556]	6	from matplotlib.font_manager import FontProperties
	7	from matplotlib.text import Text
	8
[1317]	9	import re
[203]	10
	11	class asapplotter:
[226]	12	"""
	13	The ASAP plotter.
	14	By default the plotter is set up to plot polarisations
	15	'colour stacked' and scantables across panels.
[1858]	16
	17	.. note::
	18
[226]	19	Currenly it only plots 'spectra' not Tsys or
	20	other variables.
[1858]	21
[226]	22	"""
[1563]	23	def __init__(self, visible=None , **kwargs):
[734]	24	self._visible = rcParams['plotter.gui']
	25	if visible is not None:
	26	self._visible = visible
[1563]	27	self._plotter = self._newplotter(**kwargs)
[1819]	28	# additional tool bar
	29	self._plotter.figmgr.casabar=self._newcasabar()
[710]	30
[554]	31	self._panelling = None
	32	self._stacking = None
	33	self.set_panelling()
	34	self.set_stacking()
[377]	35	self._rows = None
	36	self._cols = None
[203]	37	self._autoplot = False
[525]	38	self._minmaxx = None
	39	self._minmaxy = None
[710]	40	self._datamask = None
[203]	41	self._data = None
[607]	42	self._lmap = None
[226]	43	self._title = None
[257]	44	self._ordinate = None
	45	self._abcissa = None
[709]	46	self._abcunit = None
[920]	47	self._usermask = []
	48	self._maskselection = None
	49	self._selection = selector()
[1023]	50	self._hist = rcParams['plotter.histogram']
[1556]	51	self._fp = FontProperties()
[1819]	52	self._panellayout = self.set_panellayout(refresh=False)
[1897]	53	self._offset = None
[1023]	54
[920]	55	def _translate(self, instr):
	56	keys = "s b i p t".split()
	57	if isinstance(instr, str):
	58	for key in keys:
	59	if instr.lower().startswith(key):
	60	return key
	61	return None
	62
[1563]	63	def _newplotter(self, **kwargs):
[1819]	64	backend=matplotlib.get_backend()
	65	if not self._visible:
	66	from asap.asaplot import asaplot
	67	elif backend == 'TkAgg':
[710]	68	from asap.asaplotgui import asaplotgui as asaplot
[1819]	69	elif backend == 'Qt4Agg':
	70	from asap.asaplotgui_qt4 import asaplotgui as asaplot
	71	elif backend == 'GTkAgg':
	72	from asap.asaplotgui_gtk import asaplotgui as asaplot
[710]	73	else:
	74	from asap.asaplot import asaplot
[1563]	75	return asaplot(**kwargs)
[710]	76
[1819]	77	def _newcasabar(self):
	78	backend=matplotlib.get_backend()
	79	if self._visible and backend == "TkAgg":
	80	from asap.casatoolbar import CustomToolbarTkAgg
	81	return CustomToolbarTkAgg(self)
	82	else: return None
	83
[1862]	84	@asaplog_post_dec
[935]	85	def plot(self, scan=None):
[203]	86	"""
[920]	87	Plot a scantable.
[203]	88	Parameters:
[920]	89	scan: a scantable
[203]	90	Note:
[920]	91	If a scantable was specified in a previous call
[203]	92	to plot, no argument has to be given to 'replot'
[920]	93	NO checking is done that the abcissas of the scantable
[203]	94	are consistent e.g. all 'channel' or all 'velocity' etc.
	95	"""
[710]	96	if self._plotter.is_dead:
[1819]	97	if hasattr(self._plotter.figmgr,'casabar'):
	98	del self._plotter.figmgr.casabar
[710]	99	self._plotter = self._newplotter()
[1819]	100	self._plotter.figmgr.casabar=self._newcasabar()
[600]	101	self._plotter.hold()
[203]	102	self._plotter.clear()
[935]	103	if not self._data and not scan:
[1101]	104	msg = "Input is not a scantable"
	105	raise TypeError(msg)
[1897]	106	if scan:
	107	self.set_data(scan, refresh=False)
[920]	108	self._plot(self._data)
[709]	109	if self._minmaxy is not None:
	110	self._plotter.set_limits(ylim=self._minmaxy)
[1819]	111	if self._plotter.figmgr.casabar: self._plotter.figmgr.casabar.enable_button()
[203]	112	self._plotter.release()
[1153]	113	self._plotter.tidy()
	114	self._plotter.show(hardrefresh=False)
[203]	115	return
	116
[1572]	117	def gca(self):
	118	return self._plotter.figure.gca()
	119
[1550]	120	def refresh(self):
[1572]	121	"""Do a soft refresh"""
[1550]	122	self._plotter.figure.show()
	123
[1555]	124	def create_mask(self, nwin=1, panel=0, color=None):
[1597]	125	"""
	126	Interactively define a mask.It retruns a mask that is equivalent to
	127	the one created manually with scantable.create_mask.
	128	Parameters:
	129	nwin: The number of mask windows to create interactively
	130	default is 1.
	131	panel: Which panel to use for mask selection. This is useful
	132	if different IFs are spread over panels (default 0)
	133	"""
[1555]	134	if self._data is None:
	135	return []
[1547]	136	outmask = []
[1549]	137	self._plotter.subplot(panel)
	138	xmin, xmax = self._plotter.axes.get_xlim()
[1548]	139	marg = 0.05*(xmax-xmin)
[1549]	140	self._plotter.axes.set_xlim(xmin-marg, xmax+marg)
[1550]	141	self.refresh()
[1695]	142
[1555]	143	def cleanup(lines=False, texts=False, refresh=False):
	144	if lines:
	145	del self._plotter.axes.lines[-1]
	146	if texts:
	147	del self._plotter.axes.texts[-1]
	148	if refresh:
	149	self.refresh()
	150
	151	for w in xrange(nwin):
[1547]	152	wpos = []
[1695]	153	self.text(0.05,1.0, "Add start boundary",
[1555]	154	coords="relative", fontsize=10)
	155	point = self._plotter.get_point()
	156	cleanup(texts=True)
	157	if point is None:
	158	continue
	159	wpos.append(point[0])
[1695]	160	self.axvline(wpos[0], color=color)
[1551]	161	self.text(0.05,1.0, "Add end boundary", coords="relative", fontsize=10)
[1555]	162	point = self._plotter.get_point()
	163	cleanup(texts=True, lines=True)
	164	if point is None:
	165	self.refresh()
	166	continue
	167	wpos.append(point[0])
	168	self.axvspan(wpos[0], wpos[1], alpha=0.1,
	169	edgecolor=color, facecolor=color)
	170	ymin, ymax = self._plotter.axes.get_ylim()
[1547]	171	outmask.append(wpos)
[1153]	172
[1555]	173	self._plotter.axes.set_xlim(xmin, xmax)
	174	self.refresh()
	175	if len(outmask) > 0:
	176	return self._data.create_mask(*outmask)
	177	return []
	178
[1153]	179	# forwards to matplotlib axes
	180	def text(self, args, *kwargs):
[1547]	181	if kwargs.has_key("interactive"):
	182	if kwargs.pop("interactive"):
	183	pos = self._plotter.get_point()
	184	args = tuple(pos)+args
[1153]	185	self._axes_callback("text", args, *kwargs)
[1547]	186
[1358]	187	text.__doc__ = matplotlib.axes.Axes.text.__doc__
[1559]	188
[1153]	189	def arrow(self, args, *kwargs):
[1547]	190	if kwargs.has_key("interactive"):
	191	if kwargs.pop("interactive"):
	192	pos = self._plotter.get_region()
	193	dpos = (pos[0][0], pos[0][1],
	194	pos[1][0]-pos[0][0],
	195	pos[1][1] - pos[0][1])
	196	args = dpos + args
[1153]	197	self._axes_callback("arrow", args, *kwargs)
[1547]	198
[1358]	199	arrow.__doc__ = matplotlib.axes.Axes.arrow.__doc__
[1559]	200
	201	def annotate(self, text, xy=None, xytext=None, **kwargs):
	202	if kwargs.has_key("interactive"):
	203	if kwargs.pop("interactive"):
	204	xy = self._plotter.get_point()
	205	xytext = self._plotter.get_point()
	206	if not kwargs.has_key("arrowprops"):
	207	kwargs["arrowprops"] = dict(arrowstyle="->")
	208	self._axes_callback("annotate", text, xy, xytext, **kwargs)
	209
	210	annotate.__doc__ = matplotlib.axes.Axes.annotate.__doc__
	211
[1153]	212	def axvline(self, args, *kwargs):
[1547]	213	if kwargs.has_key("interactive"):
	214	if kwargs.pop("interactive"):
	215	pos = self._plotter.get_point()
	216	args = (pos[0],)+args
[1153]	217	self._axes_callback("axvline", args, *kwargs)
[1559]	218
[1358]	219	axvline.__doc__ = matplotlib.axes.Axes.axvline.__doc__
[1547]	220
[1153]	221	def axhline(self, args, *kwargs):
[1547]	222	if kwargs.has_key("interactive"):
	223	if kwargs.pop("interactive"):
	224	pos = self._plotter.get_point()
	225	args = (pos[1],)+args
[1153]	226	self._axes_callback("axhline", args, *kwargs)
[1559]	227
[1358]	228	axhline.__doc__ = matplotlib.axes.Axes.axhline.__doc__
[1547]	229
[1153]	230	def axvspan(self, args, *kwargs):
[1547]	231	if kwargs.has_key("interactive"):
	232	if kwargs.pop("interactive"):
	233	pos = self._plotter.get_region()
	234	dpos = (pos[0][0], pos[1][0])
	235	args = dpos + args
[1153]	236	self._axes_callback("axvspan", args, *kwargs)
	237	# hack to preventy mpl from redrawing the patch
	238	# it seem to convert the patch into lines on every draw.
	239	# This doesn't happen in a test script???
[1547]	240	#del self._plotter.axes.patches[-1]
	241
[1358]	242	axvspan.__doc__ = matplotlib.axes.Axes.axvspan.__doc__
[1232]	243
[1153]	244	def axhspan(self, args, *kwargs):
[1547]	245	if kwargs.has_key("interactive"):
	246	if kwargs.pop("interactive"):
	247	pos = self._plotter.get_region()
	248	dpos = (pos[0][1], pos[1][1])
	249	args = dpos + args
[1232]	250	self._axes_callback("axhspan", args, *kwargs)
[1153]	251	# hack to preventy mpl from redrawing the patch
	252	# it seem to convert the patch into lines on every draw.
	253	# This doesn't happen in a test script???
[1547]	254	#del self._plotter.axes.patches[-1]
[1559]	255
[1358]	256	axhspan.__doc__ = matplotlib.axes.Axes.axhspan.__doc__
[1153]	257
	258	def _axes_callback(self, axesfunc, args, *kwargs):
	259	panel = 0
	260	if kwargs.has_key("panel"):
	261	panel = kwargs.pop("panel")
	262	coords = None
	263	if kwargs.has_key("coords"):
	264	coords = kwargs.pop("coords")
	265	if coords.lower() == 'world':
	266	kwargs["transform"] = self._plotter.axes.transData
	267	elif coords.lower() == 'relative':
	268	kwargs["transform"] = self._plotter.axes.transAxes
	269	self._plotter.subplot(panel)
	270	self._plotter.axes.set_autoscale_on(False)
	271	getattr(self._plotter.axes, axesfunc)(args, *kwargs)
	272	self._plotter.show(False)
	273	self._plotter.axes.set_autoscale_on(True)
	274	# end matplotlib.axes fowarding functions
	275
[1862]	276	@asaplog_post_dec
[1819]	277	def set_data(self, scan, refresh=True):
	278	"""
[1824]	279	Set a scantable to plot.
[1819]	280	Parameters:
	281	scan: a scantable
	282	refresh: True (default) or False. If True, the plot is
[1824]	283	replotted based on the new parameter setting(s).
[1819]	284	Otherwise,the parameter(s) are set without replotting.
	285	Note:
	286	The user specified masks and data selections will be reset
	287	if a new scantable is set. This method should be called before
[1824]	288	setting data selections (set_selection) and/or masks (set_mask).
[1819]	289	"""
	290	from asap import scantable
	291	if isinstance(scan, scantable):
	292	if self._data is not None:
	293	if scan != self._data:
	294	self._data = scan
	295	# reset
	296	self._reset()
[1897]	297	msg = "A new scantable is set to the plotter. "\
	298	"The masks and data selections are reset."
[1819]	299	asaplog.push( msg )
	300	else:
	301	self._data = scan
	302	self._reset()
	303	else:
	304	msg = "Input is not a scantable"
	305	raise TypeError(msg)
[1547]	306
[1819]	307	# ranges become invalid when unit changes
	308	if self._abcunit and self._abcunit != self._data.get_unit():
	309	self._minmaxx = None
	310	self._minmaxy = None
	311	self._abcunit = self._data.get_unit()
	312	self._datamask = None
	313	if refresh: self.plot()
	314
[1862]	315	@asaplog_post_dec
[1819]	316	def set_mode(self, stacking=None, panelling=None, refresh=True):
[203]	317	"""
[377]	318	Set the plots look and feel, i.e. what you want to see on the plot.
[203]	319	Parameters:
	320	stacking: tell the plotter which variable to plot
[1217]	321	as line colour overlays (default 'pol')
[203]	322	panelling: tell the plotter which variable to plot
	323	across multiple panels (default 'scan'
[1819]	324	refresh: True (default) or False. If True, the plot is
[1824]	325	replotted based on the new parameter setting(s).
[1819]	326	Otherwise,the parameter(s) are set without replotting.
[203]	327	Note:
	328	Valid modes are:
	329	'beam' 'Beam' 'b': Beams
	330	'if' 'IF' 'i': IFs
	331	'pol' 'Pol' 'p': Polarisations
	332	'scan' 'Scan' 's': Scans
	333	'time' 'Time' 't': Times
	334	"""
[753]	335	msg = "Invalid mode"
	336	if not self.set_panelling(panelling) or \
	337	not self.set_stacking(stacking):
[1859]	338	raise TypeError(msg)
[1819]	339	if refresh and self._data: self.plot(self._data)
[203]	340	return
	341
[554]	342	def set_panelling(self, what=None):
[1858]	343	"""Set the 'panelling' mode i.e. which type of spectra should be
	344	spread across different panels.
	345	"""
	346
[554]	347	mode = what
	348	if mode is None:
	349	mode = rcParams['plotter.panelling']
	350	md = self._translate(mode)
[203]	351	if md:
[554]	352	self._panelling = md
[226]	353	self._title = None
[203]	354	return True
	355	return False
	356
[1819]	357	def set_layout(self,rows=None,cols=None,refresh=True):
[377]	358	"""
	359	Set the multi-panel layout, i.e. how many rows and columns plots
	360	are visible.
	361	Parameters:
	362	rows: The number of rows of plots
	363	cols: The number of columns of plots
[1819]	364	refresh: True (default) or False. If True, the plot is
[1824]	365	replotted based on the new parameter setting(s).
[1819]	366	Otherwise,the parameter(s) are set without replotting.
[377]	367	Note:
	368	If no argument is given, the potter reverts to its auto-plot
	369	behaviour.
	370	"""
	371	self._rows = rows
	372	self._cols = cols
[1819]	373	if refresh and self._data: self.plot(self._data)
[377]	374	return
	375
[709]	376	def set_stacking(self, what=None):
[1858]	377	"""Set the 'stacking' mode i.e. which type of spectra should be
	378	overlayed.
	379	"""
[554]	380	mode = what
[709]	381	if mode is None:
	382	mode = rcParams['plotter.stacking']
[554]	383	md = self._translate(mode)
[203]	384	if md:
	385	self._stacking = md
[226]	386	self._lmap = None
[203]	387	return True
	388	return False
	389
[1897]	390	def set_range(self,xstart=None,xend=None,ystart=None,yend=None,refresh=True, offset=None):
[203]	391	"""
	392	Set the range of interest on the abcissa of the plot
	393	Parameters:
[525]	394	[x,y]start,[x,y]end: The start and end points of the 'zoom' window
[1819]	395	refresh: True (default) or False. If True, the plot is
[1824]	396	replotted based on the new parameter setting(s).
[1819]	397	Otherwise,the parameter(s) are set without replotting.
[1897]	398	offset: shift the abcissa by the given amount. The abcissa label will
	399	have '(relative)' appended to it.
[203]	400	Note:
	401	These become non-sensical when the unit changes.
	402	use plotter.set_range() without parameters to reset
	403
	404	"""
[1897]	405	self._offset = offset
[525]	406	if xstart is None and xend is None:
	407	self._minmaxx = None
[600]	408	else:
	409	self._minmaxx = [xstart,xend]
[525]	410	if ystart is None and yend is None:
	411	self._minmaxy = None
[600]	412	else:
[709]	413	self._minmaxy = [ystart,yend]
[1819]	414	if refresh and self._data: self.plot(self._data)
[203]	415	return
[709]	416
[1819]	417	def set_legend(self, mp=None, fontsize = None, mode = 0, refresh=True):
[203]	418	"""
	419	Specify a mapping for the legend instead of using the default
	420	indices:
	421	Parameters:
[1101]	422	mp: a list of 'strings'. This should have the same length
	423	as the number of elements on the legend and then maps
	424	to the indeces in order. It is possible to uses latex
	425	math expression. These have to be enclosed in r'',
	426	e.g. r'$x^{2}$'
	427	fontsize: The font size of the label (default None)
	428	mode: where to display the legend
	429	Any other value for loc else disables the legend:
[1096]	430	0: auto
	431	1: upper right
	432	2: upper left
	433	3: lower left
	434	4: lower right
	435	5: right
	436	6: center left
	437	7: center right
	438	8: lower center
	439	9: upper center
	440	10: center
[1819]	441	refresh: True (default) or False. If True, the plot is
[1824]	442	replotted based on the new parameter setting(s).
[1819]	443	Otherwise,the parameter(s) are set without replotting.
[203]	444
	445	Example:
[485]	446	If the data has two IFs/rest frequencies with index 0 and 1
[203]	447	for CO and SiO:
	448	plotter.set_stacking('i')
[710]	449	plotter.set_legend(['CO','SiO'])
[203]	450	plotter.plot()
[710]	451	plotter.set_legend([r'$^{12}CO$', r'SiO'])
[203]	452	"""
	453	self._lmap = mp
[1096]	454	self._plotter.legend(mode)
[1101]	455	if isinstance(fontsize, int):
	456	from matplotlib import rc as rcp
	457	rcp('legend', fontsize=fontsize)
[1819]	458	if refresh and self._data: self.plot(self._data)
[226]	459	return
	460
[1819]	461	def set_title(self, title=None, fontsize=None, refresh=True):
[710]	462	"""
	463	Set the title of the plot. If multiple panels are plotted,
	464	multiple titles have to be specified.
[1819]	465	Parameters:
	466	refresh: True (default) or False. If True, the plot is
[1824]	467	replotted based on the new parameter setting(s).
[1819]	468	Otherwise,the parameter(s) are set without replotting.
[710]	469	Example:
	470	# two panels are visible on the plotter
	471	plotter.set_title(["First Panel","Second Panel"])
	472	"""
[226]	473	self._title = title
[1101]	474	if isinstance(fontsize, int):
	475	from matplotlib import rc as rcp
	476	rcp('axes', titlesize=fontsize)
[1819]	477	if refresh and self._data: self.plot(self._data)
[226]	478	return
	479
[1819]	480	def set_ordinate(self, ordinate=None, fontsize=None, refresh=True):
[710]	481	"""
	482	Set the y-axis label of the plot. If multiple panels are plotted,
	483	multiple labels have to be specified.
[1021]	484	Parameters:
	485	ordinate: a list of ordinate labels. None (default) let
	486	data determine the labels
[1819]	487	refresh: True (default) or False. If True, the plot is
[1824]	488	replotted based on the new parameter setting(s).
[1819]	489	Otherwise,the parameter(s) are set without replotting.
[710]	490	Example:
	491	# two panels are visible on the plotter
	492	plotter.set_ordinate(["First Y-Axis","Second Y-Axis"])
	493	"""
[257]	494	self._ordinate = ordinate
[1101]	495	if isinstance(fontsize, int):
	496	from matplotlib import rc as rcp
	497	rcp('axes', labelsize=fontsize)
	498	rcp('ytick', labelsize=fontsize)
[1819]	499	if refresh and self._data: self.plot(self._data)
[257]	500	return
	501
[1819]	502	def set_abcissa(self, abcissa=None, fontsize=None, refresh=True):
[710]	503	"""
	504	Set the x-axis label of the plot. If multiple panels are plotted,
	505	multiple labels have to be specified.
[1021]	506	Parameters:
	507	abcissa: a list of abcissa labels. None (default) let
	508	data determine the labels
[1819]	509	refresh: True (default) or False. If True, the plot is
[1824]	510	replotted based on the new parameter setting(s).
[1819]	511	Otherwise,the parameter(s) are set without replotting.
[710]	512	Example:
	513	# two panels are visible on the plotter
	514	plotter.set_ordinate(["First X-Axis","Second X-Axis"])
	515	"""
[257]	516	self._abcissa = abcissa
[1101]	517	if isinstance(fontsize, int):
	518	from matplotlib import rc as rcp
	519	rcp('axes', labelsize=fontsize)
	520	rcp('xtick', labelsize=fontsize)
[1819]	521	if refresh and self._data: self.plot(self._data)
[257]	522	return
	523
[1819]	524	def set_colors(self, colmap, refresh=True):
[377]	525	"""
[1217]	526	Set the colours to be used. The plotter will cycle through
	527	these colours when lines are overlaid (stacking mode).
[1021]	528	Parameters:
[1217]	529	colmap: a list of colour names
[1819]	530	refresh: True (default) or False. If True, the plot is
[1824]	531	replotted based on the new parameter setting(s).
[1819]	532	Otherwise,the parameter(s) are set without replotting.
[710]	533	Example:
	534	plotter.set_colors("red green blue")
	535	# If for example four lines are overlaid e.g I Q U V
	536	# 'I' will be 'red', 'Q' will be 'green', U will be 'blue'
	537	# and 'V' will be 'red' again.
	538	"""
[1217]	539	if isinstance(colmap,str):
	540	colmap = colmap.split()
	541	self._plotter.palette(0, colormap=colmap)
[1819]	542	if refresh and self._data: self.plot(self._data)
[710]	543
[1217]	544	# alias for english speakers
	545	set_colours = set_colors
	546
[1819]	547	def set_histogram(self, hist=True, linewidth=None, refresh=True):
[1021]	548	"""
	549	Enable/Disable histogram-like plotting.
	550	Parameters:
	551	hist: True (default) or False. The fisrt default
	552	is taken from the .asaprc setting
	553	plotter.histogram
[1819]	554	refresh: True (default) or False. If True, the plot is
[1824]	555	replotted based on the new parameter setting(s).
[1819]	556	Otherwise,the parameter(s) are set without replotting.
[1021]	557	"""
[1023]	558	self._hist = hist
[1101]	559	if isinstance(linewidth, float) or isinstance(linewidth, int):
	560	from matplotlib import rc as rcp
	561	rcp('lines', linewidth=linewidth)
[1819]	562	if refresh and self._data: self.plot(self._data)
[1023]	563
[1819]	564	def set_linestyles(self, linestyles=None, linewidth=None, refresh=True):
[710]	565	"""
[734]	566	Set the linestyles to be used. The plotter will cycle through
	567	these linestyles when lines are overlaid (stacking mode) AND
	568	only one color has been set.
[710]	569	Parameters:
	570	linestyles: a list of linestyles to use.
	571	'line', 'dashed', 'dotted', 'dashdot',
	572	'dashdotdot' and 'dashdashdot' are
	573	possible
[1819]	574	refresh: True (default) or False. If True, the plot is
[1824]	575	replotted based on the new parameter setting(s).
[1819]	576	Otherwise,the parameter(s) are set without replotting.
[710]	577	Example:
	578	plotter.set_colors("black")
	579	plotter.set_linestyles("line dashed dotted dashdot")
	580	# If for example four lines are overlaid e.g I Q U V
	581	# 'I' will be 'solid', 'Q' will be 'dashed',
	582	# U will be 'dotted' and 'V' will be 'dashdot'.
	583	"""
	584	if isinstance(linestyles,str):
	585	linestyles = linestyles.split()
	586	self._plotter.palette(color=0,linestyle=0,linestyles=linestyles)
[1101]	587	if isinstance(linewidth, float) or isinstance(linewidth, int):
	588	from matplotlib import rc as rcp
	589	rcp('lines', linewidth=linewidth)
[1819]	590	if refresh and self._data: self.plot(self._data)
[710]	591
[1819]	592	def set_font(self, refresh=True,**kwargs):
[1101]	593	"""
	594	Set font properties.
	595	Parameters:
	596	family: one of 'sans-serif', 'serif', 'cursive', 'fantasy', 'monospace'
	597	style: one of 'normal' (or 'roman'), 'italic' or 'oblique'
	598	weight: one of 'normal or 'bold'
	599	size: the 'general' font size, individual elements can be adjusted
	600	seperately
[1819]	601	refresh: True (default) or False. If True, the plot is
[1824]	602	replotted based on the new parameter setting(s).
[1819]	603	Otherwise,the parameter(s) are set without replotting.
[1101]	604	"""
	605	from matplotlib import rc as rcp
[1547]	606	fdict = {}
	607	for k,v in kwargs.iteritems():
	608	if v:
	609	fdict[k] = v
[1556]	610	self._fp = FontProperties(**fdict)
[1819]	611	if refresh and self._data: self.plot(self._data)
[1101]	612
[1819]	613	def set_panellayout(self,layout=[],refresh=True):
	614	"""
	615	Set the layout of subplots.
	616	Parameters:
	617	layout: a list of subplots layout in figure coordinate (0-1),
[1824]	618	i.e., fraction of the figure width or height.
[1819]	619	The order of elements should be:
	620	[left, bottom, right, top, horizontal space btw panels,
[1824]	621	vertical space btw panels].
[1819]	622	refresh: True (default) or False. If True, the plot is
[1824]	623	replotted based on the new parameter setting(s).
[1819]	624	Otherwise,the parameter(s) are set without replotting.
	625	Note
	626	* When layout is not specified, the values are reset to the defaults
	627	of matplotlib.
[1824]	628	* If any element is set to be None, the current value is adopted.
[1819]	629	"""
	630	if layout == []: self._panellayout=self._reset_panellayout()
[1824]	631	else:
[1819]	632	self._panellayout=[None]*6
	633	self._panellayout[0:len(layout)]=layout
	634	#print "panel layout set to ",self._panellayout
	635	if refresh and self._data: self.plot(self._data)
	636
	637	def _reset_panellayout(self):
	638	ks=map(lambda x: 'figure.subplot.'+x,
	639	['left','bottom','right','top','hspace','wspace'])
	640	return map(matplotlib.rcParams.get,ks)
	641
[1259]	642	def plot_lines(self, linecat=None, doppler=0.0, deltachan=10, rotate=90.0,
[1146]	643	location=None):
	644	"""
[1158]	645	Plot a line catalog.
	646	Parameters:
	647	linecat: the linecatalog to plot
[1168]	648	doppler: the velocity shift to apply to the frequencies
[1158]	649	deltachan: the number of channels to include each side of the
	650	line to determine a local maximum/minimum
[1259]	651	rotate: the rotation (in degrees) )for the text label (default 90.0)
[1158]	652	location: the location of the line annotation from the 'top',
	653	'bottom' or alternate (None - the default)
[1165]	654	Notes:
	655	If the spectrum is flagged no line will be drawn in that location.
[1146]	656	"""
[1259]	657	if not self._data:
	658	raise RuntimeError("No scantable has been plotted yet.")
[1146]	659	from asap._asap import linecatalog
[1259]	660	if not isinstance(linecat, linecatalog):
	661	raise ValueError("'linecat' isn't of type linecatalog.")
	662	if not self._data.get_unit().endswith("Hz"):
	663	raise RuntimeError("Can only overlay linecatalogs when data is in frequency.")
[1739]	664	from numpy import ma
[1146]	665	for j in range(len(self._plotter.subplots)):
	666	self._plotter.subplot(j)
	667	lims = self._plotter.axes.get_xlim()
[1153]	668	for row in range(linecat.nrow()):
[1259]	669	# get_frequency returns MHz
	670	base = { "GHz": 1000.0, "MHz": 1.0, "Hz": 1.0e-6 }
	671	restf = linecat.get_frequency(row)/base[self._data.get_unit()]
[1165]	672	c = 299792.458
[1174]	673	freq = restf*(1.0-doppler/c)
[1146]	674	if lims[0] < freq < lims[1]:
	675	if location is None:
	676	loc = 'bottom'
[1153]	677	if row%2: loc='top'
[1146]	678	else: loc = location
[1153]	679	maxys = []
	680	for line in self._plotter.axes.lines:
	681	v = line._x
	682	asc = v[0] < v[-1]
	683
	684	idx = None
	685	if not asc:
	686	if v[len(v)-1] <= freq <= v[0]:
	687	i = len(v)-1
	688	while i>=0 and v[i] < freq:
	689	idx = i
	690	i-=1
	691	else:
	692	if v[0] <= freq <= v[len(v)-1]:
	693	i = 0
	694	while i<len(v) and v[i] < freq:
	695	idx = i
	696	i+=1
	697	if idx is not None:
	698	lower = idx - deltachan
	699	upper = idx + deltachan
	700	if lower < 0: lower = 0
	701	if upper > len(v): upper = len(v)
	702	s = slice(lower, upper)
[1167]	703	y = line._y[s]
[1165]	704	maxy = ma.maximum(y)
	705	if isinstance( maxy, float):
	706	maxys.append(maxy)
[1164]	707	if len(maxys):
	708	peak = max(maxys)
[1165]	709	if peak > self._plotter.axes.get_ylim()[1]:
	710	loc = 'bottom'
[1164]	711	else:
	712	continue
[1157]	713	self._plotter.vline_with_label(freq, peak,
	714	linecat.get_name(row),
	715	location=loc, rotate=rotate)
[1153]	716	self._plotter.show(hardrefresh=False)
[1146]	717
[1153]	718
[710]	719	def save(self, filename=None, orientation=None, dpi=None):
	720	"""
[377]	721	Save the plot to a file. The know formats are 'png', 'ps', 'eps'.
	722	Parameters:
	723	filename: The name of the output file. This is optional
	724	and autodetects the image format from the file
	725	suffix. If non filename is specified a file
	726	called 'yyyymmdd_hhmmss.png' is created in the
	727	current directory.
[709]	728	orientation: optional parameter for postscript only (not eps).
	729	'landscape', 'portrait' or None (default) are valid.
	730	If None is choosen for 'ps' output, the plot is
	731	automatically oriented to fill the page.
[710]	732	dpi: The dpi of the output non-ps plot
[377]	733	"""
[709]	734	self._plotter.save(filename,orientation,dpi)
[377]	735	return
[709]	736
[1862]	737	@asaplog_post_dec
[1819]	738	def set_mask(self, mask=None, selection=None, refresh=True):
[525]	739	"""
[734]	740	Set a plotting mask for a specific polarization.
	741	This is useful for masking out "noise" Pangle outside a source.
	742	Parameters:
[920]	743	mask: a mask from scantable.create_mask
	744	selection: the spectra to apply the mask to.
[1819]	745	refresh: True (default) or False. If True, the plot is
[1824]	746	replotted based on the new parameter setting(s).
[1819]	747	Otherwise,the parameter(s) are set without replotting.
[734]	748	Example:
[920]	749	select = selector()
	750	select.setpolstrings("Pangle")
	751	plotter.set_mask(mymask, select)
[734]	752	"""
[710]	753	if not self._data:
[920]	754	msg = "Can only set mask after a first call to plot()"
[1859]	755	raise RuntimeError(msg)
[920]	756	if len(mask):
	757	if isinstance(mask, list) or isinstance(mask, tuple):
	758	self._usermask = array(mask)
[710]	759	else:
[920]	760	self._usermask = mask
	761	if mask is None and selection is None:
	762	self._usermask = []
	763	self._maskselection = None
	764	if isinstance(selection, selector):
[947]	765	self._maskselection = {'b': selection.get_beams(),
	766	's': selection.get_scans(),
	767	'i': selection.get_ifs(),
	768	'p': selection.get_pols(),
[920]	769	't': [] }
[710]	770	else:
[920]	771	self._maskselection = None
[1819]	772	if refresh: self.plot(self._data)
[710]	773
[709]	774	def _slice_indeces(self, data):
	775	mn = self._minmaxx[0]
	776	mx = self._minmaxx[1]
	777	asc = data[0] < data[-1]
	778	start=0
	779	end = len(data)-1
	780	inc = 1
	781	if not asc:
	782	start = len(data)-1
	783	end = 0
	784	inc = -1
	785	# find min index
[1819]	786	#while start > 0 and data[start] < mn:
	787	# start+= inc
	788	minind=start
	789	for ind in xrange(start,end+inc,inc):
	790	if data[ind] > mn: break
	791	minind=ind
[709]	792	# find max index
[1819]	793	#while end > 0 and data[end] > mx:
	794	# end-=inc
	795	#if end > 0: end +=1
	796	maxind=end
	797	for ind in xrange(end,start-inc,-inc):
	798	if data[ind] < mx: break
	799	maxind=ind
	800	start=minind
	801	end=maxind
[709]	802	if start > end:
[1819]	803	return end,start+1
	804	elif start < end:
	805	return start,end+1
	806	else:
	807	return start,end
[709]	808
[710]	809	def _reset(self):
[920]	810	self._usermask = []
[710]	811	self._usermaskspectra = None
[1897]	812	self._offset = None
[920]	813	self.set_selection(None, False)
	814
	815	def _plot(self, scan):
[947]	816	savesel = scan.get_selection()
	817	sel = savesel + self._selection
	818	d0 = {'s': 'SCANNO', 'b': 'BEAMNO', 'i':'IFNO',
	819	'p': 'POLNO', 'c': 'CYCLENO', 't' : 'TIME' }
	820	order = [d0[self._panelling],d0[self._stacking]]
	821	sel.set_order(order)
	822	scan.set_selection(sel)
[920]	823	d = {'b': scan.getbeam, 's': scan.getscan,
	824	'i': scan.getif, 'p': scan.getpol, 't': scan._gettime }
	825
[1148]	826	polmodes = dict(zip(self._selection.get_pols(),
	827	self._selection.get_poltypes()))
	828	# this returns either a tuple of numbers or a length (ncycles)
	829	# convert this into lengths
	830	n0,nstack0 = self._get_selected_n(scan)
	831	if isinstance(n0, int): n = n0
[1175]	832	else: n = len(n0)
[1148]	833	if isinstance(nstack0, int): nstack = nstack0
[1175]	834	else: nstack = len(nstack0)
[1582]	835	maxpanel, maxstack = 16,16
[920]	836	if n > maxpanel or nstack > maxstack:
[1148]	837	maxn = 0
	838	if nstack > maxstack: maxn = maxstack
	839	if n > maxpanel: maxn = maxpanel
[920]	840	msg ="Scan to be plotted contains more than %d selections.\n" \
[1148]	841	"Selecting first %d selections..." % (maxn, maxn)
[920]	842	asaplog.push(msg)
[1861]	843	asaplog.post('WARN')
[920]	844	n = min(n,maxpanel)
[998]	845	nstack = min(nstack,maxstack)
[920]	846	if n > 1:
	847	ganged = rcParams['plotter.ganged']
[1819]	848	if self._panelling == 'i':
	849	ganged = False
[920]	850	if self._rows and self._cols:
	851	n = min(n,self._rows*self._cols)
	852	self._plotter.set_panels(rows=self._rows,cols=self._cols,
[1819]	853	# nplots=n,ganged=ganged)
	854	nplots=n,layout=self._panellayout,ganged=ganged)
[920]	855	else:
[1819]	856	# self._plotter.set_panels(rows=n,cols=0,nplots=n,ganged=ganged)
	857	self._plotter.set_panels(rows=n,cols=0,nplots=n,layout=self._panellayout,ganged=ganged)
[920]	858	else:
[1819]	859	# self._plotter.set_panels()
	860	self._plotter.set_panels(layout=self._panellayout)
[920]	861	r=0
	862	nr = scan.nrow()
	863	a0,b0 = -1,-1
	864	allxlim = []
[1018]	865	allylim = []
[920]	866	newpanel=True
	867	panelcount,stackcount = 0,0
[1002]	868	while r < nr:
[920]	869	a = d[self._panelling](r)
	870	b = d[self._stacking](r)
	871	if a > a0 and panelcount < n:
	872	if n > 1:
	873	self._plotter.subplot(panelcount)
	874	self._plotter.palette(0)
	875	#title
	876	xlab = self._abcissa and self._abcissa[panelcount] \
	877	or scan._getabcissalabel()
[1897]	878	if self._offset and not self._abcissa:
	879	xlab += " (relative)"
[920]	880	ylab = self._ordinate and self._ordinate[panelcount] \
	881	or scan._get_ordinate_label()
[1547]	882	self._plotter.set_axes('xlabel', xlab)
	883	self._plotter.set_axes('ylabel', ylab)
[920]	884	lbl = self._get_label(scan, r, self._panelling, self._title)
	885	if isinstance(lbl, list) or isinstance(lbl, tuple):
	886	if 0 <= panelcount < len(lbl):
	887	lbl = lbl[panelcount]
	888	else:
	889	# get default label
	890	lbl = self._get_label(scan, r, self._panelling, None)
	891	self._plotter.set_axes('title',lbl)
	892	newpanel = True
	893	stackcount =0
	894	panelcount += 1
	895	if (b > b0 or newpanel) and stackcount < nstack:
	896	y = []
	897	if len(polmodes):
	898	y = scan._getspectrum(r, polmodes[scan.getpol(r)])
	899	else:
	900	y = scan._getspectrum(r)
	901	m = scan._getmask(r)
[1739]	902	from numpy import logical_not, logical_and
[920]	903	if self._maskselection and len(self._usermask) == len(m):
	904	if d[self._stacking](r) in self._maskselection[self._stacking]:
	905	m = logical_and(m, self._usermask)
[1739]	906	from numpy import ma, array
[1897]	907	x = array(scan._getabcissa(r))
	908	if self._offset:
	909	x += self._offset
[1116]	910	y = ma.masked_array(y,mask=logical_not(array(m,copy=False)))
[920]	911	if self._minmaxx is not None:
	912	s,e = self._slice_indeces(x)
	913	x = x[s:e]
	914	y = y[s:e]
[1096]	915	if len(x) > 1024 and rcParams['plotter.decimate']:
	916	fac = len(x)/1024
[920]	917	x = x[::fac]
	918	y = y[::fac]
	919	llbl = self._get_label(scan, r, self._stacking, self._lmap)
	920	if isinstance(llbl, list) or isinstance(llbl, tuple):
	921	if 0 <= stackcount < len(llbl):
	922	# use user label
	923	llbl = llbl[stackcount]
	924	else:
	925	# get default label
	926	llbl = self._get_label(scan, r, self._stacking, None)
	927	self._plotter.set_line(label=llbl)
[1023]	928	plotit = self._plotter.plot
	929	if self._hist: plotit = self._plotter.hist
[1146]	930	if len(x) > 0:
	931	plotit(x,y)
	932	xlim= self._minmaxx or [min(x),max(x)]
	933	allxlim += xlim
	934	ylim= self._minmaxy or [ma.minimum(y),ma.maximum(y)]
	935	allylim += ylim
[1819]	936	else:
	937	xlim = self._minmaxx or []
	938	allxlim += xlim
	939	ylim= self._minmaxy or []
	940	allylim += ylim
[920]	941	stackcount += 1
	942	# last in colour stack -> autoscale x
[1819]	943	if stackcount == nstack and len(allxlim) > 0:
[920]	944	allxlim.sort()
[1819]	945	self._plotter.subplots[panelcount-1]['axes'].set_xlim([allxlim[0],allxlim[-1]])
[920]	946	# clear
	947	allxlim =[]
	948
	949	newpanel = False
	950	a0=a
	951	b0=b
	952	# ignore following rows
	953	if (panelcount == n) and (stackcount == nstack):
[1018]	954	# last panel -> autoscale y if ganged
[1819]	955	if rcParams['plotter.ganged'] and len(allylim) > 0:
[1018]	956	allylim.sort()
	957	self._plotter.set_limits(ylim=[allylim[0],allylim[-1]])
[998]	958	break
[920]	959	r+=1 # next row
[947]	960	#reset the selector to the scantable's original
	961	scan.set_selection(savesel)
[1824]	962
[1819]	963	#temporary switch-off for older matplotlib
	964	#if self._fp is not None:
	965	if self._fp is not None and getattr(self._plotter.figure,'findobj',False):
[1556]	966	for o in self._plotter.figure.findobj(Text):
	967	o.set_fontproperties(self._fp)
[920]	968
[1582]	969	def set_selection(self, selection=None, refresh=True, **kw):
[1819]	970	"""
	971	Parameters:
	972	selection: a selector object (default unset the selection)
	973	refresh: True (default) or False. If True, the plot is
[1824]	974	replotted based on the new parameter setting(s).
[1819]	975	Otherwise,the parameter(s) are set without replotting.
	976	"""
[1582]	977	if selection is None:
	978	# reset
	979	if len(kw) == 0:
	980	self._selection = selector()
	981	else:
	982	# try keywords
	983	for k in kw:
	984	if k not in selector.fields:
	985	raise KeyError("Invalid selection key '%s', valid keys are %s" % (k, selector.fields))
	986	self._selection = selector(**kw)
	987	elif isinstance(selection, selector):
	988	self._selection = selection
	989	else:
	990	raise TypeError("'selection' is not of type selector")
	991
[920]	992	d0 = {'s': 'SCANNO', 'b': 'BEAMNO', 'i':'IFNO',
	993	'p': 'POLNO', 'c': 'CYCLENO', 't' : 'TIME' }
	994	order = [d0[self._panelling],d0[self._stacking]]
[947]	995	self._selection.set_order(order)
[1819]	996	if refresh and self._data: self.plot(self._data)
[920]	997
	998	def _get_selected_n(self, scan):
[1148]	999	d1 = {'b': scan.getbeamnos, 's': scan.getscannos,
	1000	'i': scan.getifnos, 'p': scan.getpolnos, 't': scan.ncycle }
	1001	d2 = { 'b': self._selection.get_beams(),
	1002	's': self._selection.get_scans(),
	1003	'i': self._selection.get_ifs(),
	1004	'p': self._selection.get_pols(),
	1005	't': self._selection.get_cycles() }
[920]	1006	n = d2[self._panelling] or d1[self._panelling]()
	1007	nstack = d2[self._stacking] or d1[self._stacking]()
	1008	return n,nstack
	1009
	1010	def _get_label(self, scan, row, mode, userlabel=None):
[1153]	1011	if isinstance(userlabel, list) and len(userlabel) == 0:
	1012	userlabel = " "
[947]	1013	pms = dict(zip(self._selection.get_pols(),self._selection.get_poltypes()))
[920]	1014	if len(pms):
	1015	poleval = scan._getpollabel(scan.getpol(row),pms[scan.getpol(row)])
	1016	else:
	1017	poleval = scan._getpollabel(scan.getpol(row),scan.poltype())
	1018	d = {'b': "Beam "+str(scan.getbeam(row)),
[1819]	1019	#'s': scan._getsourcename(row),
	1020	's': "Scan "+str(scan.getscan(row))+\
	1021	" ("+str(scan._getsourcename(row))+")",
[920]	1022	'i': "IF"+str(scan.getif(row)),
[964]	1023	'p': poleval,
[1175]	1024	't': str(scan.get_time(row)) }
[920]	1025	return userlabel or d[mode]
[1153]	1026
[1819]	1027	def plotazel(self, scan=None, outfile=None):
	1028	#def plotazel(self):
[1391]	1029	"""
[1696]	1030	plot azimuth and elevation versus time of a scantable
[1391]	1031	"""
[1696]	1032	from matplotlib import pylab as PL
	1033	from matplotlib.dates import DateFormatter, timezone
	1034	from matplotlib.dates import HourLocator, MinuteLocator,SecondLocator, DayLocator
[1391]	1035	from matplotlib.ticker import MultipleLocator
[1739]	1036	from numpy import array, pi
[1819]	1037	self._data = scan
	1038	self._outfile = outfile
[1556]	1039	dates = self._data.get_time(asdatetime=True)
[1391]	1040	t = PL.date2num(dates)
	1041	tz = timezone('UTC')
	1042	PL.cla()
	1043	PL.ioff()
	1044	PL.clf()
[1819]	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	PL.gcf().subplots_adjust(left=lef,bottom=bot,right=rig,top=top,
	1049	wspace=wsp,hspace=hsp)
[1824]	1050
[1391]	1051	tdel = max(t) - min(t)
	1052	ax = PL.subplot(2,1,1)
	1053	el = array(self._data.get_elevation())*180./pi
	1054	PL.ylabel('El [deg.]')
	1055	dstr = dates[0].strftime('%Y/%m/%d')
	1056	if tdel > 1.0:
	1057	dstr2 = dates[len(dates)-1].strftime('%Y/%m/%d')
	1058	dstr = dstr + " - " + dstr2
	1059	majloc = DayLocator()
	1060	minloc = HourLocator(range(0,23,12))
	1061	timefmt = DateFormatter("%b%d")
[1696]	1062	elif tdel > 24./60.:
	1063	timefmt = DateFormatter('%H:%M')
	1064	majloc = HourLocator()
	1065	minloc = MinuteLocator(30)
[1391]	1066	else:
[1696]	1067	timefmt = DateFormatter('%H:%M')
	1068	majloc = MinuteLocator(interval=5)
	1069	minloc = SecondLocator(30)
	1070
[1391]	1071	PL.title(dstr)
[1819]	1072	if tdel == 0.0:
	1073	th = (t - PL.floor(t))*24.0
	1074	PL.plot(th,el,'o',markersize=2, markerfacecolor='b', markeredgecolor='b')
	1075	else:
	1076	PL.plot_date(t,el,'o', markersize=2, markerfacecolor='b', markeredgecolor='b',tz=tz)
	1077	#ax.grid(True)
	1078	ax.xaxis.set_major_formatter(timefmt)
	1079	ax.xaxis.set_major_locator(majloc)
	1080	ax.xaxis.set_minor_locator(minloc)
[1391]	1081	ax.yaxis.grid(True)
[1819]	1082	yloc = MultipleLocator(30)
	1083	ax.set_ylim(0,90)
	1084	ax.yaxis.set_major_locator(yloc)
[1391]	1085	if tdel > 1.0:
	1086	labels = ax.get_xticklabels()
	1087	# PL.setp(labels, fontsize=10, rotation=45)
	1088	PL.setp(labels, fontsize=10)
[1819]	1089
[1391]	1090	# Az plot
	1091	az = array(self._data.get_azimuth())*180./pi
	1092	if min(az) < 0:
	1093	for irow in range(len(az)):
	1094	if az[irow] < 0: az[irow] += 360.0
	1095
[1819]	1096	ax2 = PL.subplot(2,1,2)
	1097	#PL.xlabel('Time (UT [hour])')
	1098	PL.ylabel('Az [deg.]')
	1099	if tdel == 0.0:
	1100	PL.plot(th,az,'o',markersize=2, markeredgecolor='b',markerfacecolor='b')
	1101	else:
	1102	PL.plot_date(t,az,'o', markersize=2,markeredgecolor='b',markerfacecolor='b',tz=tz)
	1103	ax2.xaxis.set_major_formatter(timefmt)
	1104	ax2.xaxis.set_major_locator(majloc)
	1105	ax2.xaxis.set_minor_locator(minloc)
	1106	#ax2.grid(True)
	1107	ax2.set_ylim(0,360)
[1696]	1108	ax2.yaxis.grid(True)
[1819]	1109	#hfmt = DateFormatter('%H')
	1110	#hloc = HourLocator()
	1111	yloc = MultipleLocator(60)
	1112	ax2.yaxis.set_major_locator(yloc)
	1113	if tdel > 1.0:
	1114	labels = ax2.get_xticklabels()
	1115	PL.setp(labels, fontsize=10)
	1116	PL.xlabel('Time (UT [day])')
	1117	else:
	1118	PL.xlabel('Time (UT [hour])')
	1119
[1391]	1120	PL.ion()
	1121	PL.draw()
[1819]	1122	if (self._outfile is not None):
	1123	PL.savefig(self._outfile)
[1391]	1124
[1819]	1125	def plotpointing(self, scan=None, outfile=None):
	1126	#def plotpointing(self):
[1391]	1127	"""
	1128	plot telescope pointings
	1129	"""
[1696]	1130	from matplotlib import pylab as PL
[1819]	1131	from numpy import array, pi
	1132	self._data = scan
	1133	self._outfile = outfile
[1391]	1134	dir = array(self._data.get_directionval()).transpose()
	1135	ra = dir[0]*180./pi
	1136	dec = dir[1]*180./pi
	1137	PL.cla()
[1819]	1138	#PL.ioff()
[1391]	1139	PL.clf()
[1819]	1140	# Adjust subplot layouts
	1141	if len(self._panellayout) !=6: self.set_panellayout(refresh=False)
	1142	lef, bot, rig, top, wsp, hsp = self._panellayout
	1143	PL.gcf().subplots_adjust(left=lef,bottom=bot,right=rig,top=top,
	1144	wspace=wsp,hspace=hsp)
	1145	ax = PL.gca()
	1146	#ax = PL.axes([0.1,0.1,0.8,0.8])
	1147	#ax = PL.axes([0.1,0.1,0.8,0.8])
[1391]	1148	ax.set_aspect('equal')
[1696]	1149	PL.plot(ra, dec, 'b,')
[1391]	1150	PL.xlabel('RA [deg.]')
	1151	PL.ylabel('Declination [deg.]')
	1152	PL.title('Telescope pointings')
	1153	[xmin,xmax,ymin,ymax] = PL.axis()
	1154	PL.axis([xmax,xmin,ymin,ymax])
[1819]	1155	#PL.ion()
[1391]	1156	PL.draw()
[1819]	1157	if (self._outfile is not None):
	1158	PL.savefig(self._outfile)
	1159
	1160	# plot total power data
	1161	# plotting in time is not yet implemented..
[1862]	1162	@asaplog_post_dec
[1819]	1163	def plottp(self, scan=None, outfile=None):
	1164	if self._plotter.is_dead:
	1165	if hasattr(self._plotter.figmgr,'casabar'):
	1166	del self._plotter.figmgr.casabar
	1167	self._plotter = self._newplotter()
	1168	self._plotter.figmgr.casabar=self._newcasabar()
	1169	self._plotter.hold()
	1170	self._plotter.clear()
	1171	from asap import scantable
	1172	if not self._data and not scan:
	1173	msg = "Input is not a scantable"
	1174	raise TypeError(msg)
	1175	if isinstance(scan, scantable):
	1176	if self._data is not None:
	1177	if scan != self._data:
	1178	self._data = scan
	1179	# reset
	1180	self._reset()
	1181	else:
	1182	self._data = scan
	1183	self._reset()
	1184	# ranges become invalid when abcissa changes?
	1185	#if self._abcunit and self._abcunit != self._data.get_unit():
	1186	# self._minmaxx = None
	1187	# self._minmaxy = None
	1188	# self._abcunit = self._data.get_unit()
	1189	# self._datamask = None
	1190
	1191	# Adjust subplot layouts
	1192	if len(self._panellayout) !=6: self.set_panellayout(refresh=False)
	1193	lef, bot, rig, top, wsp, hsp = self._panellayout
	1194	self._plotter.figure.subplots_adjust(
	1195	left=lef,bottom=bot,right=rig,top=top,wspace=wsp,hspace=hsp)
	1196	if self._plotter.figmgr.casabar: self._plotter.figmgr.casabar.disable_button()
	1197	self._plottp(self._data)
	1198	if self._minmaxy is not None:
	1199	self._plotter.set_limits(ylim=self._minmaxy)
	1200	self._plotter.release()
	1201	self._plotter.tidy()
	1202	self._plotter.show(hardrefresh=False)
	1203	return
	1204
	1205	def _plottp(self,scan):
	1206	"""
	1207	private method for plotting total power data
	1208	"""
	1209	from numpy import ma, array, arange, logical_not
	1210	r=0
	1211	nr = scan.nrow()
	1212	a0,b0 = -1,-1
	1213	allxlim = []
	1214	allylim = []
	1215	y=[]
	1216	self._plotter.set_panels()
	1217	self._plotter.palette(0)
	1218	#title
	1219	#xlab = self._abcissa and self._abcissa[panelcount] \
	1220	# or scan._getabcissalabel()
	1221	#ylab = self._ordinate and self._ordinate[panelcount] \
	1222	# or scan._get_ordinate_label()
	1223	xlab = self._abcissa or 'row number' #or Time
	1224	ylab = self._ordinate or scan._get_ordinate_label()
	1225	self._plotter.set_axes('xlabel',xlab)
	1226	self._plotter.set_axes('ylabel',ylab)
	1227	lbl = self._get_label(scan, r, 's', self._title)
	1228	if isinstance(lbl, list) or isinstance(lbl, tuple):
	1229	# if 0 <= panelcount < len(lbl):
	1230	# lbl = lbl[panelcount]
	1231	# else:
	1232	# get default label
	1233	lbl = self._get_label(scan, r, self._panelling, None)
	1234	self._plotter.set_axes('title',lbl)
	1235	y=array(scan._get_column(scan._getspectrum,-1))
	1236	m = array(scan._get_column(scan._getmask,-1))
	1237	y = ma.masked_array(y,mask=logical_not(array(m,copy=False)))
	1238	x = arange(len(y))
	1239	# try to handle spectral data somewhat...
	1240	l,m = y.shape
	1241	if m > 1:
	1242	y=y.mean(axis=1)
	1243	plotit = self._plotter.plot
	1244	llbl = self._get_label(scan, r, self._stacking, None)
	1245	self._plotter.set_line(label=llbl)
	1246	if len(x) > 0:
	1247	plotit(x,y)
	1248
	1249
	1250	# forwards to matplotlib.Figure.text
	1251	def figtext(self, args, *kwargs):
	1252	"""
	1253	Add text to figure at location x,y (relative 0-1 coords).
	1254	This method forwards args and *kwargs to a Matplotlib method,
	1255	matplotlib.Figure.text.
	1256	See the method help for detailed information.
	1257	"""
	1258	self._plotter.text(args, *kwargs)
	1259	# end matplotlib.Figure.text forwarding function
	1260
	1261
	1262	# printing header information
[1862]	1263	@asaplog_post_dec
[1819]	1264	def print_header(self, plot=True, fontsize=9, logger=False, selstr='', extrastr=''):
	1265	"""
	1266	print data (scantable) header on the plot and/or logger.
	1267	Parameters:
[1824]	1268	plot: whether or not print header info on the plot.
[1819]	1269	fontsize: header font size (valid only plot=True)
	1270	autoscale: whether or not autoscale the plot (valid only plot=True)
	1271	logger: whether or not print header info on the logger.
	1272	selstr: additional selection string (not verified)
	1273	extrastr: additional string to print (not verified)
	1274	"""
[1859]	1275	if not plot and not logger:
	1276	return
	1277	if not self._data:
	1278	raise RuntimeError("No scantable has been set yet.")
[1824]	1279	# Now header will be printed on plot and/or logger.
	1280	# Get header information and format it.
[1819]	1281	ssum=self._data.__str__()
	1282	# Print Observation header to the upper-left corner of plot
	1283	if plot:
	1284	headstr=[ssum[ssum.find('Observer:'):ssum.find('Flux Unit:')]]
	1285	headstr.append(ssum[ssum.find('Beams:'):ssum.find('Observer:')]
	1286	+ssum[ssum.find('Rest Freqs:'):ssum.find('Abcissa:')])
	1287	if extrastr != '': headstr[0]=extrastr+'\n'+headstr[0]
	1288	#headstr[1]='Data File: '+(filestr or 'unknown')+'\n'+headstr[1]
	1289	ssel='*Selections*\n'+(selstr+self._data.get_selection().__str__() or 'none')
	1290	headstr.append(ssel)
	1291	nstcol=len(headstr)
[1824]	1292
[1819]	1293	self._plotter.hold()
	1294	for i in range(nstcol):
	1295	self._plotter.figure.text(0.03+float(i)/nstcol,0.98,
	1296	headstr[i],
	1297	horizontalalignment='left',
	1298	verticalalignment='top',
	1299	fontsize=fontsize)
	1300	import time
	1301	self._plotter.figure.text(0.99,0.0,
	1302	time.strftime("%a %d %b %Y %H:%M:%S %Z"),
	1303	horizontalalignment='right',
	1304	verticalalignment='bottom',fontsize=8)
	1305	self._plotter.release()
	1306	del headstr, ssel
	1307	if logger:
	1308	asaplog.push("----------------\n Plot Summary\n----------------")
	1309	asaplog.push(extrastr)
	1310	asaplog.push(ssum[ssum.find('Beams:'):])
	1311	del ssum

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