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source: trunk/python/asapplotter.py@ 1895

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Last change on this file since 1895 was 1862, checked in by Malte Marquarding, 14 years ago
renamed print_log_dec to more explicit asaplog_post_dec
Property svn:eol-style set to `native` Property svn:keywords set to `Author Date Id Revision`
File size: 52.0 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)
[1023]	53
[920]	54	def _translate(self, instr):
	55	keys = "s b i p t".split()
	56	if isinstance(instr, str):
	57	for key in keys:
	58	if instr.lower().startswith(key):
	59	return key
	60	return None
	61
[1563]	62	def _newplotter(self, **kwargs):
[1819]	63	backend=matplotlib.get_backend()
	64	if not self._visible:
	65	from asap.asaplot import asaplot
	66	elif backend == 'TkAgg':
[710]	67	from asap.asaplotgui import asaplotgui as asaplot
[1819]	68	elif backend == 'Qt4Agg':
	69	from asap.asaplotgui_qt4 import asaplotgui as asaplot
	70	elif backend == 'GTkAgg':
	71	from asap.asaplotgui_gtk import asaplotgui as asaplot
[710]	72	else:
	73	from asap.asaplot import asaplot
[1563]	74	return asaplot(**kwargs)
[710]	75
[1819]	76	def _newcasabar(self):
	77	backend=matplotlib.get_backend()
	78	if self._visible and backend == "TkAgg":
	79	from asap.casatoolbar import CustomToolbarTkAgg
	80	return CustomToolbarTkAgg(self)
	81	else: return None
	82
[1862]	83	@asaplog_post_dec
[935]	84	def plot(self, scan=None):
[203]	85	"""
[920]	86	Plot a scantable.
[203]	87	Parameters:
[920]	88	scan: a scantable
[203]	89	Note:
[920]	90	If a scantable was specified in a previous call
[203]	91	to plot, no argument has to be given to 'replot'
[920]	92	NO checking is done that the abcissas of the scantable
[203]	93	are consistent e.g. all 'channel' or all 'velocity' etc.
	94	"""
[710]	95	if self._plotter.is_dead:
[1819]	96	if hasattr(self._plotter.figmgr,'casabar'):
	97	del self._plotter.figmgr.casabar
[710]	98	self._plotter = self._newplotter()
[1819]	99	self._plotter.figmgr.casabar=self._newcasabar()
[600]	100	self._plotter.hold()
[203]	101	self._plotter.clear()
[935]	102	if not self._data and not scan:
[1101]	103	msg = "Input is not a scantable"
	104	raise TypeError(msg)
[1819]	105	if scan: self.set_data(scan,refresh=False)
[920]	106	self._plot(self._data)
[709]	107	if self._minmaxy is not None:
	108	self._plotter.set_limits(ylim=self._minmaxy)
[1819]	109	if self._plotter.figmgr.casabar: self._plotter.figmgr.casabar.enable_button()
[203]	110	self._plotter.release()
[1153]	111	self._plotter.tidy()
	112	self._plotter.show(hardrefresh=False)
[203]	113	return
	114
[1572]	115	def gca(self):
	116	return self._plotter.figure.gca()
	117
[1550]	118	def refresh(self):
[1572]	119	"""Do a soft refresh"""
[1550]	120	self._plotter.figure.show()
	121
[1555]	122	def create_mask(self, nwin=1, panel=0, color=None):
[1597]	123	"""
	124	Interactively define a mask.It retruns a mask that is equivalent to
	125	the one created manually with scantable.create_mask.
	126	Parameters:
	127	nwin: The number of mask windows to create interactively
	128	default is 1.
	129	panel: Which panel to use for mask selection. This is useful
	130	if different IFs are spread over panels (default 0)
	131	"""
[1555]	132	if self._data is None:
	133	return []
[1547]	134	outmask = []
[1549]	135	self._plotter.subplot(panel)
	136	xmin, xmax = self._plotter.axes.get_xlim()
[1548]	137	marg = 0.05*(xmax-xmin)
[1549]	138	self._plotter.axes.set_xlim(xmin-marg, xmax+marg)
[1550]	139	self.refresh()
[1695]	140
[1555]	141	def cleanup(lines=False, texts=False, refresh=False):
	142	if lines:
	143	del self._plotter.axes.lines[-1]
	144	if texts:
	145	del self._plotter.axes.texts[-1]
	146	if refresh:
	147	self.refresh()
	148
	149	for w in xrange(nwin):
[1547]	150	wpos = []
[1695]	151	self.text(0.05,1.0, "Add start boundary",
[1555]	152	coords="relative", fontsize=10)
	153	point = self._plotter.get_point()
	154	cleanup(texts=True)
	155	if point is None:
	156	continue
	157	wpos.append(point[0])
[1695]	158	self.axvline(wpos[0], color=color)
[1551]	159	self.text(0.05,1.0, "Add end boundary", coords="relative", fontsize=10)
[1555]	160	point = self._plotter.get_point()
	161	cleanup(texts=True, lines=True)
	162	if point is None:
	163	self.refresh()
	164	continue
	165	wpos.append(point[0])
	166	self.axvspan(wpos[0], wpos[1], alpha=0.1,
	167	edgecolor=color, facecolor=color)
	168	ymin, ymax = self._plotter.axes.get_ylim()
[1547]	169	outmask.append(wpos)
[1153]	170
[1555]	171	self._plotter.axes.set_xlim(xmin, xmax)
	172	self.refresh()
	173	if len(outmask) > 0:
	174	return self._data.create_mask(*outmask)
	175	return []
	176
[1153]	177	# forwards to matplotlib axes
	178	def text(self, args, *kwargs):
[1547]	179	if kwargs.has_key("interactive"):
	180	if kwargs.pop("interactive"):
	181	pos = self._plotter.get_point()
	182	args = tuple(pos)+args
[1153]	183	self._axes_callback("text", args, *kwargs)
[1547]	184
[1358]	185	text.__doc__ = matplotlib.axes.Axes.text.__doc__
[1559]	186
[1153]	187	def arrow(self, args, *kwargs):
[1547]	188	if kwargs.has_key("interactive"):
	189	if kwargs.pop("interactive"):
	190	pos = self._plotter.get_region()
	191	dpos = (pos[0][0], pos[0][1],
	192	pos[1][0]-pos[0][0],
	193	pos[1][1] - pos[0][1])
	194	args = dpos + args
[1153]	195	self._axes_callback("arrow", args, *kwargs)
[1547]	196
[1358]	197	arrow.__doc__ = matplotlib.axes.Axes.arrow.__doc__
[1559]	198
	199	def annotate(self, text, xy=None, xytext=None, **kwargs):
	200	if kwargs.has_key("interactive"):
	201	if kwargs.pop("interactive"):
	202	xy = self._plotter.get_point()
	203	xytext = self._plotter.get_point()
	204	if not kwargs.has_key("arrowprops"):
	205	kwargs["arrowprops"] = dict(arrowstyle="->")
	206	self._axes_callback("annotate", text, xy, xytext, **kwargs)
	207
	208	annotate.__doc__ = matplotlib.axes.Axes.annotate.__doc__
	209
[1153]	210	def axvline(self, args, *kwargs):
[1547]	211	if kwargs.has_key("interactive"):
	212	if kwargs.pop("interactive"):
	213	pos = self._plotter.get_point()
	214	args = (pos[0],)+args
[1153]	215	self._axes_callback("axvline", args, *kwargs)
[1559]	216
[1358]	217	axvline.__doc__ = matplotlib.axes.Axes.axvline.__doc__
[1547]	218
[1153]	219	def axhline(self, args, *kwargs):
[1547]	220	if kwargs.has_key("interactive"):
	221	if kwargs.pop("interactive"):
	222	pos = self._plotter.get_point()
	223	args = (pos[1],)+args
[1153]	224	self._axes_callback("axhline", args, *kwargs)
[1559]	225
[1358]	226	axhline.__doc__ = matplotlib.axes.Axes.axhline.__doc__
[1547]	227
[1153]	228	def axvspan(self, args, *kwargs):
[1547]	229	if kwargs.has_key("interactive"):
	230	if kwargs.pop("interactive"):
	231	pos = self._plotter.get_region()
	232	dpos = (pos[0][0], pos[1][0])
	233	args = dpos + args
[1153]	234	self._axes_callback("axvspan", args, *kwargs)
	235	# hack to preventy mpl from redrawing the patch
	236	# it seem to convert the patch into lines on every draw.
	237	# This doesn't happen in a test script???
[1547]	238	#del self._plotter.axes.patches[-1]
	239
[1358]	240	axvspan.__doc__ = matplotlib.axes.Axes.axvspan.__doc__
[1232]	241
[1153]	242	def axhspan(self, args, *kwargs):
[1547]	243	if kwargs.has_key("interactive"):
	244	if kwargs.pop("interactive"):
	245	pos = self._plotter.get_region()
	246	dpos = (pos[0][1], pos[1][1])
	247	args = dpos + args
[1232]	248	self._axes_callback("axhspan", args, *kwargs)
[1153]	249	# hack to preventy mpl from redrawing the patch
	250	# it seem to convert the patch into lines on every draw.
	251	# This doesn't happen in a test script???
[1547]	252	#del self._plotter.axes.patches[-1]
[1559]	253
[1358]	254	axhspan.__doc__ = matplotlib.axes.Axes.axhspan.__doc__
[1153]	255
	256	def _axes_callback(self, axesfunc, args, *kwargs):
	257	panel = 0
	258	if kwargs.has_key("panel"):
	259	panel = kwargs.pop("panel")
	260	coords = None
	261	if kwargs.has_key("coords"):
	262	coords = kwargs.pop("coords")
	263	if coords.lower() == 'world':
	264	kwargs["transform"] = self._plotter.axes.transData
	265	elif coords.lower() == 'relative':
	266	kwargs["transform"] = self._plotter.axes.transAxes
	267	self._plotter.subplot(panel)
	268	self._plotter.axes.set_autoscale_on(False)
	269	getattr(self._plotter.axes, axesfunc)(args, *kwargs)
	270	self._plotter.show(False)
	271	self._plotter.axes.set_autoscale_on(True)
	272	# end matplotlib.axes fowarding functions
	273
[1862]	274	@asaplog_post_dec
[1819]	275	def set_data(self, scan, refresh=True):
	276	"""
[1824]	277	Set a scantable to plot.
[1819]	278	Parameters:
	279	scan: a scantable
	280	refresh: True (default) or False. If True, the plot is
[1824]	281	replotted based on the new parameter setting(s).
[1819]	282	Otherwise,the parameter(s) are set without replotting.
	283	Note:
	284	The user specified masks and data selections will be reset
	285	if a new scantable is set. This method should be called before
[1824]	286	setting data selections (set_selection) and/or masks (set_mask).
[1819]	287	"""
	288	from asap import scantable
	289	if isinstance(scan, scantable):
	290	if self._data is not None:
	291	if scan != self._data:
	292	self._data = scan
	293	# reset
	294	self._reset()
	295	msg = "A new scantable is set to the plotter. The masks and data selections are reset."
	296	asaplog.push( msg )
	297	else:
	298	self._data = scan
	299	self._reset()
	300	else:
	301	msg = "Input is not a scantable"
	302	raise TypeError(msg)
[1547]	303
[1819]	304	# ranges become invalid when unit changes
	305	if self._abcunit and self._abcunit != self._data.get_unit():
	306	self._minmaxx = None
	307	self._minmaxy = None
	308	self._abcunit = self._data.get_unit()
	309	self._datamask = None
	310	if refresh: self.plot()
	311
[1862]	312	@asaplog_post_dec
[1819]	313	def set_mode(self, stacking=None, panelling=None, refresh=True):
[203]	314	"""
[377]	315	Set the plots look and feel, i.e. what you want to see on the plot.
[203]	316	Parameters:
	317	stacking: tell the plotter which variable to plot
[1217]	318	as line colour overlays (default 'pol')
[203]	319	panelling: tell the plotter which variable to plot
	320	across multiple panels (default 'scan'
[1819]	321	refresh: True (default) or False. If True, the plot is
[1824]	322	replotted based on the new parameter setting(s).
[1819]	323	Otherwise,the parameter(s) are set without replotting.
[203]	324	Note:
	325	Valid modes are:
	326	'beam' 'Beam' 'b': Beams
	327	'if' 'IF' 'i': IFs
	328	'pol' 'Pol' 'p': Polarisations
	329	'scan' 'Scan' 's': Scans
	330	'time' 'Time' 't': Times
	331	"""
[753]	332	msg = "Invalid mode"
	333	if not self.set_panelling(panelling) or \
	334	not self.set_stacking(stacking):
[1859]	335	raise TypeError(msg)
[1819]	336	if refresh and self._data: self.plot(self._data)
[203]	337	return
	338
[554]	339	def set_panelling(self, what=None):
[1858]	340	"""Set the 'panelling' mode i.e. which type of spectra should be
	341	spread across different panels.
	342	"""
	343
[554]	344	mode = what
	345	if mode is None:
	346	mode = rcParams['plotter.panelling']
	347	md = self._translate(mode)
[203]	348	if md:
[554]	349	self._panelling = md
[226]	350	self._title = None
[203]	351	return True
	352	return False
	353
[1819]	354	def set_layout(self,rows=None,cols=None,refresh=True):
[377]	355	"""
	356	Set the multi-panel layout, i.e. how many rows and columns plots
	357	are visible.
	358	Parameters:
	359	rows: The number of rows of plots
	360	cols: The number of columns of plots
[1819]	361	refresh: True (default) or False. If True, the plot is
[1824]	362	replotted based on the new parameter setting(s).
[1819]	363	Otherwise,the parameter(s) are set without replotting.
[377]	364	Note:
	365	If no argument is given, the potter reverts to its auto-plot
	366	behaviour.
	367	"""
	368	self._rows = rows
	369	self._cols = cols
[1819]	370	if refresh and self._data: self.plot(self._data)
[377]	371	return
	372
[709]	373	def set_stacking(self, what=None):
[1858]	374	"""Set the 'stacking' mode i.e. which type of spectra should be
	375	overlayed.
	376	"""
[554]	377	mode = what
[709]	378	if mode is None:
	379	mode = rcParams['plotter.stacking']
[554]	380	md = self._translate(mode)
[203]	381	if md:
	382	self._stacking = md
[226]	383	self._lmap = None
[203]	384	return True
	385	return False
	386
[1819]	387	def set_range(self,xstart=None,xend=None,ystart=None,yend=None,refresh=True):
[203]	388	"""
	389	Set the range of interest on the abcissa of the plot
	390	Parameters:
[525]	391	[x,y]start,[x,y]end: The start and end points of the 'zoom' window
[1819]	392	refresh: True (default) or False. If True, the plot is
[1824]	393	replotted based on the new parameter setting(s).
[1819]	394	Otherwise,the parameter(s) are set without replotting.
[203]	395	Note:
	396	These become non-sensical when the unit changes.
	397	use plotter.set_range() without parameters to reset
	398
	399	"""
[525]	400	if xstart is None and xend is None:
	401	self._minmaxx = None
[600]	402	else:
	403	self._minmaxx = [xstart,xend]
[525]	404	if ystart is None and yend is None:
	405	self._minmaxy = None
[600]	406	else:
[709]	407	self._minmaxy = [ystart,yend]
[1819]	408	if refresh and self._data: self.plot(self._data)
[203]	409	return
[709]	410
[1819]	411	def set_legend(self, mp=None, fontsize = None, mode = 0, refresh=True):
[203]	412	"""
	413	Specify a mapping for the legend instead of using the default
	414	indices:
	415	Parameters:
[1101]	416	mp: a list of 'strings'. This should have the same length
	417	as the number of elements on the legend and then maps
	418	to the indeces in order. It is possible to uses latex
	419	math expression. These have to be enclosed in r'',
	420	e.g. r'$x^{2}$'
	421	fontsize: The font size of the label (default None)
	422	mode: where to display the legend
	423	Any other value for loc else disables the legend:
[1096]	424	0: auto
	425	1: upper right
	426	2: upper left
	427	3: lower left
	428	4: lower right
	429	5: right
	430	6: center left
	431	7: center right
	432	8: lower center
	433	9: upper center
	434	10: center
[1819]	435	refresh: True (default) or False. If True, the plot is
[1824]	436	replotted based on the new parameter setting(s).
[1819]	437	Otherwise,the parameter(s) are set without replotting.
[203]	438
	439	Example:
[485]	440	If the data has two IFs/rest frequencies with index 0 and 1
[203]	441	for CO and SiO:
	442	plotter.set_stacking('i')
[710]	443	plotter.set_legend(['CO','SiO'])
[203]	444	plotter.plot()
[710]	445	plotter.set_legend([r'$^{12}CO$', r'SiO'])
[203]	446	"""
	447	self._lmap = mp
[1096]	448	self._plotter.legend(mode)
[1101]	449	if isinstance(fontsize, int):
	450	from matplotlib import rc as rcp
	451	rcp('legend', fontsize=fontsize)
[1819]	452	if refresh and self._data: self.plot(self._data)
[226]	453	return
	454
[1819]	455	def set_title(self, title=None, fontsize=None, refresh=True):
[710]	456	"""
	457	Set the title of the plot. If multiple panels are plotted,
	458	multiple titles have to be specified.
[1819]	459	Parameters:
	460	refresh: True (default) or False. If True, the plot is
[1824]	461	replotted based on the new parameter setting(s).
[1819]	462	Otherwise,the parameter(s) are set without replotting.
[710]	463	Example:
	464	# two panels are visible on the plotter
	465	plotter.set_title(["First Panel","Second Panel"])
	466	"""
[226]	467	self._title = title
[1101]	468	if isinstance(fontsize, int):
	469	from matplotlib import rc as rcp
	470	rcp('axes', titlesize=fontsize)
[1819]	471	if refresh and self._data: self.plot(self._data)
[226]	472	return
	473
[1819]	474	def set_ordinate(self, ordinate=None, fontsize=None, refresh=True):
[710]	475	"""
	476	Set the y-axis label of the plot. If multiple panels are plotted,
	477	multiple labels have to be specified.
[1021]	478	Parameters:
	479	ordinate: a list of ordinate labels. None (default) let
	480	data determine the labels
[1819]	481	refresh: True (default) or False. If True, the plot is
[1824]	482	replotted based on the new parameter setting(s).
[1819]	483	Otherwise,the parameter(s) are set without replotting.
[710]	484	Example:
	485	# two panels are visible on the plotter
	486	plotter.set_ordinate(["First Y-Axis","Second Y-Axis"])
	487	"""
[257]	488	self._ordinate = ordinate
[1101]	489	if isinstance(fontsize, int):
	490	from matplotlib import rc as rcp
	491	rcp('axes', labelsize=fontsize)
	492	rcp('ytick', labelsize=fontsize)
[1819]	493	if refresh and self._data: self.plot(self._data)
[257]	494	return
	495
[1819]	496	def set_abcissa(self, abcissa=None, fontsize=None, refresh=True):
[710]	497	"""
	498	Set the x-axis label of the plot. If multiple panels are plotted,
	499	multiple labels have to be specified.
[1021]	500	Parameters:
	501	abcissa: a list of abcissa labels. None (default) let
	502	data determine the labels
[1819]	503	refresh: True (default) or False. If True, the plot is
[1824]	504	replotted based on the new parameter setting(s).
[1819]	505	Otherwise,the parameter(s) are set without replotting.
[710]	506	Example:
	507	# two panels are visible on the plotter
	508	plotter.set_ordinate(["First X-Axis","Second X-Axis"])
	509	"""
[257]	510	self._abcissa = abcissa
[1101]	511	if isinstance(fontsize, int):
	512	from matplotlib import rc as rcp
	513	rcp('axes', labelsize=fontsize)
	514	rcp('xtick', labelsize=fontsize)
[1819]	515	if refresh and self._data: self.plot(self._data)
[257]	516	return
	517
[1819]	518	def set_colors(self, colmap, refresh=True):
[377]	519	"""
[1217]	520	Set the colours to be used. The plotter will cycle through
	521	these colours when lines are overlaid (stacking mode).
[1021]	522	Parameters:
[1217]	523	colmap: a list of colour names
[1819]	524	refresh: True (default) or False. If True, the plot is
[1824]	525	replotted based on the new parameter setting(s).
[1819]	526	Otherwise,the parameter(s) are set without replotting.
[710]	527	Example:
	528	plotter.set_colors("red green blue")
	529	# If for example four lines are overlaid e.g I Q U V
	530	# 'I' will be 'red', 'Q' will be 'green', U will be 'blue'
	531	# and 'V' will be 'red' again.
	532	"""
[1217]	533	if isinstance(colmap,str):
	534	colmap = colmap.split()
	535	self._plotter.palette(0, colormap=colmap)
[1819]	536	if refresh and self._data: self.plot(self._data)
[710]	537
[1217]	538	# alias for english speakers
	539	set_colours = set_colors
	540
[1819]	541	def set_histogram(self, hist=True, linewidth=None, refresh=True):
[1021]	542	"""
	543	Enable/Disable histogram-like plotting.
	544	Parameters:
	545	hist: True (default) or False. The fisrt default
	546	is taken from the .asaprc setting
	547	plotter.histogram
[1819]	548	refresh: True (default) or False. If True, the plot is
[1824]	549	replotted based on the new parameter setting(s).
[1819]	550	Otherwise,the parameter(s) are set without replotting.
[1021]	551	"""
[1023]	552	self._hist = hist
[1101]	553	if isinstance(linewidth, float) or isinstance(linewidth, int):
	554	from matplotlib import rc as rcp
	555	rcp('lines', linewidth=linewidth)
[1819]	556	if refresh and self._data: self.plot(self._data)
[1023]	557
[1819]	558	def set_linestyles(self, linestyles=None, linewidth=None, refresh=True):
[710]	559	"""
[734]	560	Set the linestyles to be used. The plotter will cycle through
	561	these linestyles when lines are overlaid (stacking mode) AND
	562	only one color has been set.
[710]	563	Parameters:
	564	linestyles: a list of linestyles to use.
	565	'line', 'dashed', 'dotted', 'dashdot',
	566	'dashdotdot' and 'dashdashdot' are
	567	possible
[1819]	568	refresh: True (default) or False. If True, the plot is
[1824]	569	replotted based on the new parameter setting(s).
[1819]	570	Otherwise,the parameter(s) are set without replotting.
[710]	571	Example:
	572	plotter.set_colors("black")
	573	plotter.set_linestyles("line dashed dotted dashdot")
	574	# If for example four lines are overlaid e.g I Q U V
	575	# 'I' will be 'solid', 'Q' will be 'dashed',
	576	# U will be 'dotted' and 'V' will be 'dashdot'.
	577	"""
	578	if isinstance(linestyles,str):
	579	linestyles = linestyles.split()
	580	self._plotter.palette(color=0,linestyle=0,linestyles=linestyles)
[1101]	581	if isinstance(linewidth, float) or isinstance(linewidth, int):
	582	from matplotlib import rc as rcp
	583	rcp('lines', linewidth=linewidth)
[1819]	584	if refresh and self._data: self.plot(self._data)
[710]	585
[1819]	586	def set_font(self, refresh=True,**kwargs):
[1101]	587	"""
	588	Set font properties.
	589	Parameters:
	590	family: one of 'sans-serif', 'serif', 'cursive', 'fantasy', 'monospace'
	591	style: one of 'normal' (or 'roman'), 'italic' or 'oblique'
	592	weight: one of 'normal or 'bold'
	593	size: the 'general' font size, individual elements can be adjusted
	594	seperately
[1819]	595	refresh: True (default) or False. If True, the plot is
[1824]	596	replotted based on the new parameter setting(s).
[1819]	597	Otherwise,the parameter(s) are set without replotting.
[1101]	598	"""
	599	from matplotlib import rc as rcp
[1547]	600	fdict = {}
	601	for k,v in kwargs.iteritems():
	602	if v:
	603	fdict[k] = v
[1556]	604	self._fp = FontProperties(**fdict)
[1819]	605	if refresh and self._data: self.plot(self._data)
[1101]	606
[1819]	607	def set_panellayout(self,layout=[],refresh=True):
	608	"""
	609	Set the layout of subplots.
	610	Parameters:
	611	layout: a list of subplots layout in figure coordinate (0-1),
[1824]	612	i.e., fraction of the figure width or height.
[1819]	613	The order of elements should be:
	614	[left, bottom, right, top, horizontal space btw panels,
[1824]	615	vertical space btw panels].
[1819]	616	refresh: True (default) or False. If True, the plot is
[1824]	617	replotted based on the new parameter setting(s).
[1819]	618	Otherwise,the parameter(s) are set without replotting.
	619	Note
	620	* When layout is not specified, the values are reset to the defaults
	621	of matplotlib.
[1824]	622	* If any element is set to be None, the current value is adopted.
[1819]	623	"""
	624	if layout == []: self._panellayout=self._reset_panellayout()
[1824]	625	else:
[1819]	626	self._panellayout=[None]*6
	627	self._panellayout[0:len(layout)]=layout
	628	#print "panel layout set to ",self._panellayout
	629	if refresh and self._data: self.plot(self._data)
	630
	631	def _reset_panellayout(self):
	632	ks=map(lambda x: 'figure.subplot.'+x,
	633	['left','bottom','right','top','hspace','wspace'])
	634	return map(matplotlib.rcParams.get,ks)
	635
[1259]	636	def plot_lines(self, linecat=None, doppler=0.0, deltachan=10, rotate=90.0,
[1146]	637	location=None):
	638	"""
[1158]	639	Plot a line catalog.
	640	Parameters:
	641	linecat: the linecatalog to plot
[1168]	642	doppler: the velocity shift to apply to the frequencies
[1158]	643	deltachan: the number of channels to include each side of the
	644	line to determine a local maximum/minimum
[1259]	645	rotate: the rotation (in degrees) )for the text label (default 90.0)
[1158]	646	location: the location of the line annotation from the 'top',
	647	'bottom' or alternate (None - the default)
[1165]	648	Notes:
	649	If the spectrum is flagged no line will be drawn in that location.
[1146]	650	"""
[1259]	651	if not self._data:
	652	raise RuntimeError("No scantable has been plotted yet.")
[1146]	653	from asap._asap import linecatalog
[1259]	654	if not isinstance(linecat, linecatalog):
	655	raise ValueError("'linecat' isn't of type linecatalog.")
	656	if not self._data.get_unit().endswith("Hz"):
	657	raise RuntimeError("Can only overlay linecatalogs when data is in frequency.")
[1739]	658	from numpy import ma
[1146]	659	for j in range(len(self._plotter.subplots)):
	660	self._plotter.subplot(j)
	661	lims = self._plotter.axes.get_xlim()
[1153]	662	for row in range(linecat.nrow()):
[1259]	663	# get_frequency returns MHz
	664	base = { "GHz": 1000.0, "MHz": 1.0, "Hz": 1.0e-6 }
	665	restf = linecat.get_frequency(row)/base[self._data.get_unit()]
[1165]	666	c = 299792.458
[1174]	667	freq = restf*(1.0-doppler/c)
[1146]	668	if lims[0] < freq < lims[1]:
	669	if location is None:
	670	loc = 'bottom'
[1153]	671	if row%2: loc='top'
[1146]	672	else: loc = location
[1153]	673	maxys = []
	674	for line in self._plotter.axes.lines:
	675	v = line._x
	676	asc = v[0] < v[-1]
	677
	678	idx = None
	679	if not asc:
	680	if v[len(v)-1] <= freq <= v[0]:
	681	i = len(v)-1
	682	while i>=0 and v[i] < freq:
	683	idx = i
	684	i-=1
	685	else:
	686	if v[0] <= freq <= v[len(v)-1]:
	687	i = 0
	688	while i<len(v) and v[i] < freq:
	689	idx = i
	690	i+=1
	691	if idx is not None:
	692	lower = idx - deltachan
	693	upper = idx + deltachan
	694	if lower < 0: lower = 0
	695	if upper > len(v): upper = len(v)
	696	s = slice(lower, upper)
[1167]	697	y = line._y[s]
[1165]	698	maxy = ma.maximum(y)
	699	if isinstance( maxy, float):
	700	maxys.append(maxy)
[1164]	701	if len(maxys):
	702	peak = max(maxys)
[1165]	703	if peak > self._plotter.axes.get_ylim()[1]:
	704	loc = 'bottom'
[1164]	705	else:
	706	continue
[1157]	707	self._plotter.vline_with_label(freq, peak,
	708	linecat.get_name(row),
	709	location=loc, rotate=rotate)
[1153]	710	self._plotter.show(hardrefresh=False)
[1146]	711
[1153]	712
[710]	713	def save(self, filename=None, orientation=None, dpi=None):
	714	"""
[377]	715	Save the plot to a file. The know formats are 'png', 'ps', 'eps'.
	716	Parameters:
	717	filename: The name of the output file. This is optional
	718	and autodetects the image format from the file
	719	suffix. If non filename is specified a file
	720	called 'yyyymmdd_hhmmss.png' is created in the
	721	current directory.
[709]	722	orientation: optional parameter for postscript only (not eps).
	723	'landscape', 'portrait' or None (default) are valid.
	724	If None is choosen for 'ps' output, the plot is
	725	automatically oriented to fill the page.
[710]	726	dpi: The dpi of the output non-ps plot
[377]	727	"""
[709]	728	self._plotter.save(filename,orientation,dpi)
[377]	729	return
[709]	730
[1862]	731	@asaplog_post_dec
[1819]	732	def set_mask(self, mask=None, selection=None, refresh=True):
[525]	733	"""
[734]	734	Set a plotting mask for a specific polarization.
	735	This is useful for masking out "noise" Pangle outside a source.
	736	Parameters:
[920]	737	mask: a mask from scantable.create_mask
	738	selection: the spectra to apply the mask to.
[1819]	739	refresh: True (default) or False. If True, the plot is
[1824]	740	replotted based on the new parameter setting(s).
[1819]	741	Otherwise,the parameter(s) are set without replotting.
[734]	742	Example:
[920]	743	select = selector()
	744	select.setpolstrings("Pangle")
	745	plotter.set_mask(mymask, select)
[734]	746	"""
[710]	747	if not self._data:
[920]	748	msg = "Can only set mask after a first call to plot()"
[1859]	749	raise RuntimeError(msg)
[920]	750	if len(mask):
	751	if isinstance(mask, list) or isinstance(mask, tuple):
	752	self._usermask = array(mask)
[710]	753	else:
[920]	754	self._usermask = mask
	755	if mask is None and selection is None:
	756	self._usermask = []
	757	self._maskselection = None
	758	if isinstance(selection, selector):
[947]	759	self._maskselection = {'b': selection.get_beams(),
	760	's': selection.get_scans(),
	761	'i': selection.get_ifs(),
	762	'p': selection.get_pols(),
[920]	763	't': [] }
[710]	764	else:
[920]	765	self._maskselection = None
[1819]	766	if refresh: self.plot(self._data)
[710]	767
[709]	768	def _slice_indeces(self, data):
	769	mn = self._minmaxx[0]
	770	mx = self._minmaxx[1]
	771	asc = data[0] < data[-1]
	772	start=0
	773	end = len(data)-1
	774	inc = 1
	775	if not asc:
	776	start = len(data)-1
	777	end = 0
	778	inc = -1
	779	# find min index
[1819]	780	#while start > 0 and data[start] < mn:
	781	# start+= inc
	782	minind=start
	783	for ind in xrange(start,end+inc,inc):
	784	if data[ind] > mn: break
	785	minind=ind
[709]	786	# find max index
[1819]	787	#while end > 0 and data[end] > mx:
	788	# end-=inc
	789	#if end > 0: end +=1
	790	maxind=end
	791	for ind in xrange(end,start-inc,-inc):
	792	if data[ind] < mx: break
	793	maxind=ind
	794	start=minind
	795	end=maxind
[709]	796	if start > end:
[1819]	797	return end,start+1
	798	elif start < end:
	799	return start,end+1
	800	else:
	801	return start,end
[709]	802
[710]	803	def _reset(self):
[920]	804	self._usermask = []
[710]	805	self._usermaskspectra = None
[920]	806	self.set_selection(None, False)
	807
	808	def _plot(self, scan):
[947]	809	savesel = scan.get_selection()
	810	sel = savesel + self._selection
	811	d0 = {'s': 'SCANNO', 'b': 'BEAMNO', 'i':'IFNO',
	812	'p': 'POLNO', 'c': 'CYCLENO', 't' : 'TIME' }
	813	order = [d0[self._panelling],d0[self._stacking]]
	814	sel.set_order(order)
	815	scan.set_selection(sel)
[920]	816	d = {'b': scan.getbeam, 's': scan.getscan,
	817	'i': scan.getif, 'p': scan.getpol, 't': scan._gettime }
	818
[1148]	819	polmodes = dict(zip(self._selection.get_pols(),
	820	self._selection.get_poltypes()))
	821	# this returns either a tuple of numbers or a length (ncycles)
	822	# convert this into lengths
	823	n0,nstack0 = self._get_selected_n(scan)
	824	if isinstance(n0, int): n = n0
[1175]	825	else: n = len(n0)
[1148]	826	if isinstance(nstack0, int): nstack = nstack0
[1175]	827	else: nstack = len(nstack0)
[1582]	828	maxpanel, maxstack = 16,16
[920]	829	if n > maxpanel or nstack > maxstack:
[1148]	830	maxn = 0
	831	if nstack > maxstack: maxn = maxstack
	832	if n > maxpanel: maxn = maxpanel
[920]	833	msg ="Scan to be plotted contains more than %d selections.\n" \
[1148]	834	"Selecting first %d selections..." % (maxn, maxn)
[920]	835	asaplog.push(msg)
[1861]	836	asaplog.post('WARN')
[920]	837	n = min(n,maxpanel)
[998]	838	nstack = min(nstack,maxstack)
[920]	839	if n > 1:
	840	ganged = rcParams['plotter.ganged']
[1819]	841	if self._panelling == 'i':
	842	ganged = False
[920]	843	if self._rows and self._cols:
	844	n = min(n,self._rows*self._cols)
	845	self._plotter.set_panels(rows=self._rows,cols=self._cols,
[1819]	846	# nplots=n,ganged=ganged)
	847	nplots=n,layout=self._panellayout,ganged=ganged)
[920]	848	else:
[1819]	849	# self._plotter.set_panels(rows=n,cols=0,nplots=n,ganged=ganged)
	850	self._plotter.set_panels(rows=n,cols=0,nplots=n,layout=self._panellayout,ganged=ganged)
[920]	851	else:
[1819]	852	# self._plotter.set_panels()
	853	self._plotter.set_panels(layout=self._panellayout)
[920]	854	r=0
	855	nr = scan.nrow()
	856	a0,b0 = -1,-1
	857	allxlim = []
[1018]	858	allylim = []
[920]	859	newpanel=True
	860	panelcount,stackcount = 0,0
[1002]	861	while r < nr:
[920]	862	a = d[self._panelling](r)
	863	b = d[self._stacking](r)
	864	if a > a0 and panelcount < n:
	865	if n > 1:
	866	self._plotter.subplot(panelcount)
	867	self._plotter.palette(0)
	868	#title
	869	xlab = self._abcissa and self._abcissa[panelcount] \
	870	or scan._getabcissalabel()
	871	ylab = self._ordinate and self._ordinate[panelcount] \
	872	or scan._get_ordinate_label()
[1547]	873	self._plotter.set_axes('xlabel', xlab)
	874	self._plotter.set_axes('ylabel', ylab)
[920]	875	lbl = self._get_label(scan, r, self._panelling, self._title)
	876	if isinstance(lbl, list) or isinstance(lbl, tuple):
	877	if 0 <= panelcount < len(lbl):
	878	lbl = lbl[panelcount]
	879	else:
	880	# get default label
	881	lbl = self._get_label(scan, r, self._panelling, None)
	882	self._plotter.set_axes('title',lbl)
	883	newpanel = True
	884	stackcount =0
	885	panelcount += 1
	886	if (b > b0 or newpanel) and stackcount < nstack:
	887	y = []
	888	if len(polmodes):
	889	y = scan._getspectrum(r, polmodes[scan.getpol(r)])
	890	else:
	891	y = scan._getspectrum(r)
	892	m = scan._getmask(r)
[1739]	893	from numpy import logical_not, logical_and
[920]	894	if self._maskselection and len(self._usermask) == len(m):
	895	if d[self._stacking](r) in self._maskselection[self._stacking]:
	896	m = logical_and(m, self._usermask)
	897	x = scan._getabcissa(r)
[1739]	898	from numpy import ma, array
[1116]	899	y = ma.masked_array(y,mask=logical_not(array(m,copy=False)))
[920]	900	if self._minmaxx is not None:
	901	s,e = self._slice_indeces(x)
	902	x = x[s:e]
	903	y = y[s:e]
[1096]	904	if len(x) > 1024 and rcParams['plotter.decimate']:
	905	fac = len(x)/1024
[920]	906	x = x[::fac]
	907	y = y[::fac]
	908	llbl = self._get_label(scan, r, self._stacking, self._lmap)
	909	if isinstance(llbl, list) or isinstance(llbl, tuple):
	910	if 0 <= stackcount < len(llbl):
	911	# use user label
	912	llbl = llbl[stackcount]
	913	else:
	914	# get default label
	915	llbl = self._get_label(scan, r, self._stacking, None)
	916	self._plotter.set_line(label=llbl)
[1023]	917	plotit = self._plotter.plot
	918	if self._hist: plotit = self._plotter.hist
[1146]	919	if len(x) > 0:
	920	plotit(x,y)
	921	xlim= self._minmaxx or [min(x),max(x)]
	922	allxlim += xlim
	923	ylim= self._minmaxy or [ma.minimum(y),ma.maximum(y)]
	924	allylim += ylim
[1819]	925	else:
	926	xlim = self._minmaxx or []
	927	allxlim += xlim
	928	ylim= self._minmaxy or []
	929	allylim += ylim
[920]	930	stackcount += 1
	931	# last in colour stack -> autoscale x
[1819]	932	if stackcount == nstack and len(allxlim) > 0:
[920]	933	allxlim.sort()
[1819]	934	self._plotter.subplots[panelcount-1]['axes'].set_xlim([allxlim[0],allxlim[-1]])
[920]	935	# clear
	936	allxlim =[]
	937
	938	newpanel = False
	939	a0=a
	940	b0=b
	941	# ignore following rows
	942	if (panelcount == n) and (stackcount == nstack):
[1018]	943	# last panel -> autoscale y if ganged
[1819]	944	if rcParams['plotter.ganged'] and len(allylim) > 0:
[1018]	945	allylim.sort()
	946	self._plotter.set_limits(ylim=[allylim[0],allylim[-1]])
[998]	947	break
[920]	948	r+=1 # next row
[947]	949	#reset the selector to the scantable's original
	950	scan.set_selection(savesel)
[1824]	951
[1819]	952	#temporary switch-off for older matplotlib
	953	#if self._fp is not None:
	954	if self._fp is not None and getattr(self._plotter.figure,'findobj',False):
[1556]	955	for o in self._plotter.figure.findobj(Text):
	956	o.set_fontproperties(self._fp)
[920]	957
[1582]	958	def set_selection(self, selection=None, refresh=True, **kw):
[1819]	959	"""
	960	Parameters:
	961	selection: a selector object (default unset the selection)
	962	refresh: True (default) or False. If True, the plot is
[1824]	963	replotted based on the new parameter setting(s).
[1819]	964	Otherwise,the parameter(s) are set without replotting.
	965	"""
[1582]	966	if selection is None:
	967	# reset
	968	if len(kw) == 0:
	969	self._selection = selector()
	970	else:
	971	# try keywords
	972	for k in kw:
	973	if k not in selector.fields:
	974	raise KeyError("Invalid selection key '%s', valid keys are %s" % (k, selector.fields))
	975	self._selection = selector(**kw)
	976	elif isinstance(selection, selector):
	977	self._selection = selection
	978	else:
	979	raise TypeError("'selection' is not of type selector")
	980
[920]	981	d0 = {'s': 'SCANNO', 'b': 'BEAMNO', 'i':'IFNO',
	982	'p': 'POLNO', 'c': 'CYCLENO', 't' : 'TIME' }
	983	order = [d0[self._panelling],d0[self._stacking]]
[947]	984	self._selection.set_order(order)
[1819]	985	if refresh and self._data: self.plot(self._data)
[920]	986
	987	def _get_selected_n(self, scan):
[1148]	988	d1 = {'b': scan.getbeamnos, 's': scan.getscannos,
	989	'i': scan.getifnos, 'p': scan.getpolnos, 't': scan.ncycle }
	990	d2 = { 'b': self._selection.get_beams(),
	991	's': self._selection.get_scans(),
	992	'i': self._selection.get_ifs(),
	993	'p': self._selection.get_pols(),
	994	't': self._selection.get_cycles() }
[920]	995	n = d2[self._panelling] or d1[self._panelling]()
	996	nstack = d2[self._stacking] or d1[self._stacking]()
	997	return n,nstack
	998
	999	def _get_label(self, scan, row, mode, userlabel=None):
[1153]	1000	if isinstance(userlabel, list) and len(userlabel) == 0:
	1001	userlabel = " "
[947]	1002	pms = dict(zip(self._selection.get_pols(),self._selection.get_poltypes()))
[920]	1003	if len(pms):
	1004	poleval = scan._getpollabel(scan.getpol(row),pms[scan.getpol(row)])
	1005	else:
	1006	poleval = scan._getpollabel(scan.getpol(row),scan.poltype())
	1007	d = {'b': "Beam "+str(scan.getbeam(row)),
[1819]	1008	#'s': scan._getsourcename(row),
	1009	's': "Scan "+str(scan.getscan(row))+\
	1010	" ("+str(scan._getsourcename(row))+")",
[920]	1011	'i': "IF"+str(scan.getif(row)),
[964]	1012	'p': poleval,
[1175]	1013	't': str(scan.get_time(row)) }
[920]	1014	return userlabel or d[mode]
[1153]	1015
[1819]	1016	def plotazel(self, scan=None, outfile=None):
	1017	#def plotazel(self):
[1391]	1018	"""
[1696]	1019	plot azimuth and elevation versus time of a scantable
[1391]	1020	"""
[1696]	1021	from matplotlib import pylab as PL
	1022	from matplotlib.dates import DateFormatter, timezone
	1023	from matplotlib.dates import HourLocator, MinuteLocator,SecondLocator, DayLocator
[1391]	1024	from matplotlib.ticker import MultipleLocator
[1739]	1025	from numpy import array, pi
[1819]	1026	self._data = scan
	1027	self._outfile = outfile
[1556]	1028	dates = self._data.get_time(asdatetime=True)
[1391]	1029	t = PL.date2num(dates)
	1030	tz = timezone('UTC')
	1031	PL.cla()
	1032	PL.ioff()
	1033	PL.clf()
[1819]	1034	# Adjust subplot layouts
	1035	if len(self._panellayout) !=6: self.set_panellayout(refresh=False)
	1036	lef, bot, rig, top, wsp, hsp = self._panellayout
	1037	PL.gcf().subplots_adjust(left=lef,bottom=bot,right=rig,top=top,
	1038	wspace=wsp,hspace=hsp)
[1824]	1039
[1391]	1040	tdel = max(t) - min(t)
	1041	ax = PL.subplot(2,1,1)
	1042	el = array(self._data.get_elevation())*180./pi
	1043	PL.ylabel('El [deg.]')
	1044	dstr = dates[0].strftime('%Y/%m/%d')
	1045	if tdel > 1.0:
	1046	dstr2 = dates[len(dates)-1].strftime('%Y/%m/%d')
	1047	dstr = dstr + " - " + dstr2
	1048	majloc = DayLocator()
	1049	minloc = HourLocator(range(0,23,12))
	1050	timefmt = DateFormatter("%b%d")
[1696]	1051	elif tdel > 24./60.:
	1052	timefmt = DateFormatter('%H:%M')
	1053	majloc = HourLocator()
	1054	minloc = MinuteLocator(30)
[1391]	1055	else:
[1696]	1056	timefmt = DateFormatter('%H:%M')
	1057	majloc = MinuteLocator(interval=5)
	1058	minloc = SecondLocator(30)
	1059
[1391]	1060	PL.title(dstr)
[1819]	1061	if tdel == 0.0:
	1062	th = (t - PL.floor(t))*24.0
	1063	PL.plot(th,el,'o',markersize=2, markerfacecolor='b', markeredgecolor='b')
	1064	else:
	1065	PL.plot_date(t,el,'o', markersize=2, markerfacecolor='b', markeredgecolor='b',tz=tz)
	1066	#ax.grid(True)
	1067	ax.xaxis.set_major_formatter(timefmt)
	1068	ax.xaxis.set_major_locator(majloc)
	1069	ax.xaxis.set_minor_locator(minloc)
[1391]	1070	ax.yaxis.grid(True)
[1819]	1071	yloc = MultipleLocator(30)
	1072	ax.set_ylim(0,90)
	1073	ax.yaxis.set_major_locator(yloc)
[1391]	1074	if tdel > 1.0:
	1075	labels = ax.get_xticklabels()
	1076	# PL.setp(labels, fontsize=10, rotation=45)
	1077	PL.setp(labels, fontsize=10)
[1819]	1078
[1391]	1079	# Az plot
	1080	az = array(self._data.get_azimuth())*180./pi
	1081	if min(az) < 0:
	1082	for irow in range(len(az)):
	1083	if az[irow] < 0: az[irow] += 360.0
	1084
[1819]	1085	ax2 = PL.subplot(2,1,2)
	1086	#PL.xlabel('Time (UT [hour])')
	1087	PL.ylabel('Az [deg.]')
	1088	if tdel == 0.0:
	1089	PL.plot(th,az,'o',markersize=2, markeredgecolor='b',markerfacecolor='b')
	1090	else:
	1091	PL.plot_date(t,az,'o', markersize=2,markeredgecolor='b',markerfacecolor='b',tz=tz)
	1092	ax2.xaxis.set_major_formatter(timefmt)
	1093	ax2.xaxis.set_major_locator(majloc)
	1094	ax2.xaxis.set_minor_locator(minloc)
	1095	#ax2.grid(True)
	1096	ax2.set_ylim(0,360)
[1696]	1097	ax2.yaxis.grid(True)
[1819]	1098	#hfmt = DateFormatter('%H')
	1099	#hloc = HourLocator()
	1100	yloc = MultipleLocator(60)
	1101	ax2.yaxis.set_major_locator(yloc)
	1102	if tdel > 1.0:
	1103	labels = ax2.get_xticklabels()
	1104	PL.setp(labels, fontsize=10)
	1105	PL.xlabel('Time (UT [day])')
	1106	else:
	1107	PL.xlabel('Time (UT [hour])')
	1108
[1391]	1109	PL.ion()
	1110	PL.draw()
[1819]	1111	if (self._outfile is not None):
	1112	PL.savefig(self._outfile)
[1391]	1113
[1819]	1114	def plotpointing(self, scan=None, outfile=None):
	1115	#def plotpointing(self):
[1391]	1116	"""
	1117	plot telescope pointings
	1118	"""
[1696]	1119	from matplotlib import pylab as PL
[1819]	1120	from numpy import array, pi
	1121	self._data = scan
	1122	self._outfile = outfile
[1391]	1123	dir = array(self._data.get_directionval()).transpose()
	1124	ra = dir[0]*180./pi
	1125	dec = dir[1]*180./pi
	1126	PL.cla()
[1819]	1127	#PL.ioff()
[1391]	1128	PL.clf()
[1819]	1129	# Adjust subplot layouts
	1130	if len(self._panellayout) !=6: self.set_panellayout(refresh=False)
	1131	lef, bot, rig, top, wsp, hsp = self._panellayout
	1132	PL.gcf().subplots_adjust(left=lef,bottom=bot,right=rig,top=top,
	1133	wspace=wsp,hspace=hsp)
	1134	ax = PL.gca()
	1135	#ax = PL.axes([0.1,0.1,0.8,0.8])
	1136	#ax = PL.axes([0.1,0.1,0.8,0.8])
[1391]	1137	ax.set_aspect('equal')
[1696]	1138	PL.plot(ra, dec, 'b,')
[1391]	1139	PL.xlabel('RA [deg.]')
	1140	PL.ylabel('Declination [deg.]')
	1141	PL.title('Telescope pointings')
	1142	[xmin,xmax,ymin,ymax] = PL.axis()
	1143	PL.axis([xmax,xmin,ymin,ymax])
[1819]	1144	#PL.ion()
[1391]	1145	PL.draw()
[1819]	1146	if (self._outfile is not None):
	1147	PL.savefig(self._outfile)
	1148
	1149	# plot total power data
	1150	# plotting in time is not yet implemented..
[1862]	1151	@asaplog_post_dec
[1819]	1152	def plottp(self, scan=None, outfile=None):
	1153	if self._plotter.is_dead:
	1154	if hasattr(self._plotter.figmgr,'casabar'):
	1155	del self._plotter.figmgr.casabar
	1156	self._plotter = self._newplotter()
	1157	self._plotter.figmgr.casabar=self._newcasabar()
	1158	self._plotter.hold()
	1159	self._plotter.clear()
	1160	from asap import scantable
	1161	if not self._data and not scan:
	1162	msg = "Input is not a scantable"
	1163	raise TypeError(msg)
	1164	if isinstance(scan, scantable):
	1165	if self._data is not None:
	1166	if scan != self._data:
	1167	self._data = scan
	1168	# reset
	1169	self._reset()
	1170	else:
	1171	self._data = scan
	1172	self._reset()
	1173	# ranges become invalid when abcissa changes?
	1174	#if self._abcunit and self._abcunit != self._data.get_unit():
	1175	# self._minmaxx = None
	1176	# self._minmaxy = None
	1177	# self._abcunit = self._data.get_unit()
	1178	# self._datamask = None
	1179
	1180	# Adjust subplot layouts
	1181	if len(self._panellayout) !=6: self.set_panellayout(refresh=False)
	1182	lef, bot, rig, top, wsp, hsp = self._panellayout
	1183	self._plotter.figure.subplots_adjust(
	1184	left=lef,bottom=bot,right=rig,top=top,wspace=wsp,hspace=hsp)
	1185	if self._plotter.figmgr.casabar: self._plotter.figmgr.casabar.disable_button()
	1186	self._plottp(self._data)
	1187	if self._minmaxy is not None:
	1188	self._plotter.set_limits(ylim=self._minmaxy)
	1189	self._plotter.release()
	1190	self._plotter.tidy()
	1191	self._plotter.show(hardrefresh=False)
	1192	return
	1193
	1194	def _plottp(self,scan):
	1195	"""
	1196	private method for plotting total power data
	1197	"""
	1198	from numpy import ma, array, arange, logical_not
	1199	r=0
	1200	nr = scan.nrow()
	1201	a0,b0 = -1,-1
	1202	allxlim = []
	1203	allylim = []
	1204	y=[]
	1205	self._plotter.set_panels()
	1206	self._plotter.palette(0)
	1207	#title
	1208	#xlab = self._abcissa and self._abcissa[panelcount] \
	1209	# or scan._getabcissalabel()
	1210	#ylab = self._ordinate and self._ordinate[panelcount] \
	1211	# or scan._get_ordinate_label()
	1212	xlab = self._abcissa or 'row number' #or Time
	1213	ylab = self._ordinate or scan._get_ordinate_label()
	1214	self._plotter.set_axes('xlabel',xlab)
	1215	self._plotter.set_axes('ylabel',ylab)
	1216	lbl = self._get_label(scan, r, 's', self._title)
	1217	if isinstance(lbl, list) or isinstance(lbl, tuple):
	1218	# if 0 <= panelcount < len(lbl):
	1219	# lbl = lbl[panelcount]
	1220	# else:
	1221	# get default label
	1222	lbl = self._get_label(scan, r, self._panelling, None)
	1223	self._plotter.set_axes('title',lbl)
	1224	y=array(scan._get_column(scan._getspectrum,-1))
	1225	m = array(scan._get_column(scan._getmask,-1))
	1226	y = ma.masked_array(y,mask=logical_not(array(m,copy=False)))
	1227	x = arange(len(y))
	1228	# try to handle spectral data somewhat...
	1229	l,m = y.shape
	1230	if m > 1:
	1231	y=y.mean(axis=1)
	1232	plotit = self._plotter.plot
	1233	llbl = self._get_label(scan, r, self._stacking, None)
	1234	self._plotter.set_line(label=llbl)
	1235	if len(x) > 0:
	1236	plotit(x,y)
	1237
	1238
	1239	# forwards to matplotlib.Figure.text
	1240	def figtext(self, args, *kwargs):
	1241	"""
	1242	Add text to figure at location x,y (relative 0-1 coords).
	1243	This method forwards args and *kwargs to a Matplotlib method,
	1244	matplotlib.Figure.text.
	1245	See the method help for detailed information.
	1246	"""
	1247	self._plotter.text(args, *kwargs)
	1248	# end matplotlib.Figure.text forwarding function
	1249
	1250
	1251	# printing header information
[1862]	1252	@asaplog_post_dec
[1819]	1253	def print_header(self, plot=True, fontsize=9, logger=False, selstr='', extrastr=''):
	1254	"""
	1255	print data (scantable) header on the plot and/or logger.
	1256	Parameters:
[1824]	1257	plot: whether or not print header info on the plot.
[1819]	1258	fontsize: header font size (valid only plot=True)
	1259	autoscale: whether or not autoscale the plot (valid only plot=True)
	1260	logger: whether or not print header info on the logger.
	1261	selstr: additional selection string (not verified)
	1262	extrastr: additional string to print (not verified)
	1263	"""
[1859]	1264	if not plot and not logger:
	1265	return
	1266	if not self._data:
	1267	raise RuntimeError("No scantable has been set yet.")
[1824]	1268	# Now header will be printed on plot and/or logger.
	1269	# Get header information and format it.
[1819]	1270	ssum=self._data.__str__()
	1271	# Print Observation header to the upper-left corner of plot
	1272	if plot:
	1273	headstr=[ssum[ssum.find('Observer:'):ssum.find('Flux Unit:')]]
	1274	headstr.append(ssum[ssum.find('Beams:'):ssum.find('Observer:')]
	1275	+ssum[ssum.find('Rest Freqs:'):ssum.find('Abcissa:')])
	1276	if extrastr != '': headstr[0]=extrastr+'\n'+headstr[0]
	1277	#headstr[1]='Data File: '+(filestr or 'unknown')+'\n'+headstr[1]
	1278	ssel='*Selections*\n'+(selstr+self._data.get_selection().__str__() or 'none')
	1279	headstr.append(ssel)
	1280	nstcol=len(headstr)
[1824]	1281
[1819]	1282	self._plotter.hold()
	1283	for i in range(nstcol):
	1284	self._plotter.figure.text(0.03+float(i)/nstcol,0.98,
	1285	headstr[i],
	1286	horizontalalignment='left',
	1287	verticalalignment='top',
	1288	fontsize=fontsize)
	1289	import time
	1290	self._plotter.figure.text(0.99,0.0,
	1291	time.strftime("%a %d %b %Y %H:%M:%S %Z"),
	1292	horizontalalignment='right',
	1293	verticalalignment='bottom',fontsize=8)
	1294	self._plotter.release()
	1295	del headstr, ssel
	1296	if logger:
	1297	asaplog.push("----------------\n Plot Summary\n----------------")
	1298	asaplog.push(extrastr)
	1299	asaplog.push(ssum[ssum.find('Beams:'):])
	1300	del ssum

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