Context Navigation

asapplotter.py@ 1987

Visit:

Last change on this file since 1987 was 1984, checked in by Kana Sugimoto, 14 years ago

New Development: No

JIRA Issue: Yes (CAS-1822/ASAP-204)

Ready for Test: Yes

Interface Changes: No

What Interface Changed:

Test Programs:

Put in Release Notes: No

Module(s): asapplotter & sdplot

Description:

for got to commit this. The previous commit of casatoolbar.py depends on this code.

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

File size: 55.5 KB

Rev	Line
[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
[1981]	54	self._startrow = 0
	55	self._ipanel = -1
	56	self._panelrows = []
[1023]	57
[920]	58	def _translate(self, instr):
[1910]	59	keys = "s b i p t r".split()
[920]	60	if isinstance(instr, str):
	61	for key in keys:
	62	if instr.lower().startswith(key):
	63	return key
	64	return None
	65
[1563]	66	def _newplotter(self, **kwargs):
[1819]	67	backend=matplotlib.get_backend()
	68	if not self._visible:
	69	from asap.asaplot import asaplot
	70	elif backend == 'TkAgg':
[710]	71	from asap.asaplotgui import asaplotgui as asaplot
[1819]	72	elif backend == 'Qt4Agg':
	73	from asap.asaplotgui_qt4 import asaplotgui as asaplot
	74	elif backend == 'GTkAgg':
	75	from asap.asaplotgui_gtk import asaplotgui as asaplot
[710]	76	else:
	77	from asap.asaplot import asaplot
[1563]	78	return asaplot(**kwargs)
[710]	79
[1819]	80	def _newcasabar(self):
	81	backend=matplotlib.get_backend()
	82	if self._visible and backend == "TkAgg":
	83	from asap.casatoolbar import CustomToolbarTkAgg
	84	return CustomToolbarTkAgg(self)
	85	else: return None
	86
[1862]	87	@asaplog_post_dec
[935]	88	def plot(self, scan=None):
[203]	89	"""
[920]	90	Plot a scantable.
[203]	91	Parameters:
[920]	92	scan: a scantable
[203]	93	Note:
[920]	94	If a scantable was specified in a previous call
[203]	95	to plot, no argument has to be given to 'replot'
[920]	96	NO checking is done that the abcissas of the scantable
[203]	97	are consistent e.g. all 'channel' or all 'velocity' etc.
	98	"""
[1981]	99	self._startrow = 0
	100	self._ipanel = -1
[710]	101	if self._plotter.is_dead:
[1819]	102	if hasattr(self._plotter.figmgr,'casabar'):
	103	del self._plotter.figmgr.casabar
[710]	104	self._plotter = self._newplotter()
[1819]	105	self._plotter.figmgr.casabar=self._newcasabar()
[1981]	106	if self._plotter.figmgr.casabar:
[1984]	107	self._plotter.figmgr.casabar.set_pagecounter(1)
[1981]	108	self._panelrows = []
[600]	109	self._plotter.hold()
[1945]	110	#self._plotter.clear()
[935]	111	if not self._data and not scan:
[1101]	112	msg = "Input is not a scantable"
	113	raise TypeError(msg)
[1897]	114	if scan:
	115	self.set_data(scan, refresh=False)
[920]	116	self._plot(self._data)
[709]	117	if self._minmaxy is not None:
	118	self._plotter.set_limits(ylim=self._minmaxy)
[1819]	119	if self._plotter.figmgr.casabar: self._plotter.figmgr.casabar.enable_button()
[203]	120	self._plotter.release()
[1153]	121	self._plotter.tidy()
	122	self._plotter.show(hardrefresh=False)
[203]	123	return
	124
[1572]	125	def gca(self):
	126	return self._plotter.figure.gca()
	127
[1550]	128	def refresh(self):
[1572]	129	"""Do a soft refresh"""
[1550]	130	self._plotter.figure.show()
	131
[1555]	132	def create_mask(self, nwin=1, panel=0, color=None):
[1597]	133	"""
[1927]	134	Interactively define a mask. It retruns a mask that is equivalent to
[1597]	135	the one created manually with scantable.create_mask.
	136	Parameters:
	137	nwin: The number of mask windows to create interactively
	138	default is 1.
	139	panel: Which panel to use for mask selection. This is useful
	140	if different IFs are spread over panels (default 0)
	141	"""
[1555]	142	if self._data is None:
	143	return []
[1547]	144	outmask = []
[1549]	145	self._plotter.subplot(panel)
	146	xmin, xmax = self._plotter.axes.get_xlim()
[1548]	147	marg = 0.05*(xmax-xmin)
[1549]	148	self._plotter.axes.set_xlim(xmin-marg, xmax+marg)
[1550]	149	self.refresh()
[1695]	150
[1555]	151	def cleanup(lines=False, texts=False, refresh=False):
	152	if lines:
	153	del self._plotter.axes.lines[-1]
	154	if texts:
	155	del self._plotter.axes.texts[-1]
	156	if refresh:
	157	self.refresh()
	158
	159	for w in xrange(nwin):
[1547]	160	wpos = []
[1695]	161	self.text(0.05,1.0, "Add start boundary",
[1555]	162	coords="relative", fontsize=10)
	163	point = self._plotter.get_point()
	164	cleanup(texts=True)
	165	if point is None:
	166	continue
	167	wpos.append(point[0])
[1695]	168	self.axvline(wpos[0], color=color)
[1551]	169	self.text(0.05,1.0, "Add end boundary", coords="relative", fontsize=10)
[1555]	170	point = self._plotter.get_point()
	171	cleanup(texts=True, lines=True)
	172	if point is None:
	173	self.refresh()
	174	continue
	175	wpos.append(point[0])
	176	self.axvspan(wpos[0], wpos[1], alpha=0.1,
	177	edgecolor=color, facecolor=color)
	178	ymin, ymax = self._plotter.axes.get_ylim()
[1547]	179	outmask.append(wpos)
[1153]	180
[1555]	181	self._plotter.axes.set_xlim(xmin, xmax)
	182	self.refresh()
	183	if len(outmask) > 0:
	184	return self._data.create_mask(*outmask)
	185	return []
	186
[1153]	187	# forwards to matplotlib axes
	188	def text(self, args, *kwargs):
[1547]	189	if kwargs.has_key("interactive"):
	190	if kwargs.pop("interactive"):
	191	pos = self._plotter.get_point()
	192	args = tuple(pos)+args
[1153]	193	self._axes_callback("text", args, *kwargs)
[1547]	194
[1358]	195	text.__doc__ = matplotlib.axes.Axes.text.__doc__
[1559]	196
[1153]	197	def arrow(self, args, *kwargs):
[1547]	198	if kwargs.has_key("interactive"):
	199	if kwargs.pop("interactive"):
	200	pos = self._plotter.get_region()
	201	dpos = (pos[0][0], pos[0][1],
	202	pos[1][0]-pos[0][0],
	203	pos[1][1] - pos[0][1])
	204	args = dpos + args
[1153]	205	self._axes_callback("arrow", args, *kwargs)
[1547]	206
[1358]	207	arrow.__doc__ = matplotlib.axes.Axes.arrow.__doc__
[1559]	208
	209	def annotate(self, text, xy=None, xytext=None, **kwargs):
	210	if kwargs.has_key("interactive"):
	211	if kwargs.pop("interactive"):
	212	xy = self._plotter.get_point()
	213	xytext = self._plotter.get_point()
	214	if not kwargs.has_key("arrowprops"):
	215	kwargs["arrowprops"] = dict(arrowstyle="->")
	216	self._axes_callback("annotate", text, xy, xytext, **kwargs)
	217
	218	annotate.__doc__ = matplotlib.axes.Axes.annotate.__doc__
	219
[1153]	220	def axvline(self, args, *kwargs):
[1547]	221	if kwargs.has_key("interactive"):
	222	if kwargs.pop("interactive"):
	223	pos = self._plotter.get_point()
	224	args = (pos[0],)+args
[1153]	225	self._axes_callback("axvline", args, *kwargs)
[1559]	226
[1358]	227	axvline.__doc__ = matplotlib.axes.Axes.axvline.__doc__
[1547]	228
[1153]	229	def axhline(self, args, *kwargs):
[1547]	230	if kwargs.has_key("interactive"):
	231	if kwargs.pop("interactive"):
	232	pos = self._plotter.get_point()
	233	args = (pos[1],)+args
[1153]	234	self._axes_callback("axhline", args, *kwargs)
[1559]	235
[1358]	236	axhline.__doc__ = matplotlib.axes.Axes.axhline.__doc__
[1547]	237
[1153]	238	def axvspan(self, args, *kwargs):
[1547]	239	if kwargs.has_key("interactive"):
	240	if kwargs.pop("interactive"):
	241	pos = self._plotter.get_region()
	242	dpos = (pos[0][0], pos[1][0])
	243	args = dpos + args
[1153]	244	self._axes_callback("axvspan", args, *kwargs)
	245	# hack to preventy mpl from redrawing the patch
	246	# it seem to convert the patch into lines on every draw.
	247	# This doesn't happen in a test script???
[1547]	248	#del self._plotter.axes.patches[-1]
	249
[1358]	250	axvspan.__doc__ = matplotlib.axes.Axes.axvspan.__doc__
[1232]	251
[1153]	252	def axhspan(self, args, *kwargs):
[1547]	253	if kwargs.has_key("interactive"):
	254	if kwargs.pop("interactive"):
	255	pos = self._plotter.get_region()
	256	dpos = (pos[0][1], pos[1][1])
	257	args = dpos + args
[1232]	258	self._axes_callback("axhspan", args, *kwargs)
[1153]	259	# hack to preventy mpl from redrawing the patch
	260	# it seem to convert the patch into lines on every draw.
	261	# This doesn't happen in a test script???
[1547]	262	#del self._plotter.axes.patches[-1]
[1559]	263
[1358]	264	axhspan.__doc__ = matplotlib.axes.Axes.axhspan.__doc__
[1153]	265
	266	def _axes_callback(self, axesfunc, args, *kwargs):
	267	panel = 0
	268	if kwargs.has_key("panel"):
	269	panel = kwargs.pop("panel")
	270	coords = None
	271	if kwargs.has_key("coords"):
	272	coords = kwargs.pop("coords")
	273	if coords.lower() == 'world':
	274	kwargs["transform"] = self._plotter.axes.transData
	275	elif coords.lower() == 'relative':
	276	kwargs["transform"] = self._plotter.axes.transAxes
	277	self._plotter.subplot(panel)
	278	self._plotter.axes.set_autoscale_on(False)
	279	getattr(self._plotter.axes, axesfunc)(args, *kwargs)
	280	self._plotter.show(False)
	281	self._plotter.axes.set_autoscale_on(True)
	282	# end matplotlib.axes fowarding functions
	283
[1862]	284	@asaplog_post_dec
[1819]	285	def set_data(self, scan, refresh=True):
	286	"""
[1824]	287	Set a scantable to plot.
[1819]	288	Parameters:
	289	scan: a scantable
	290	refresh: True (default) or False. If True, the plot is
[1824]	291	replotted based on the new parameter setting(s).
[1819]	292	Otherwise,the parameter(s) are set without replotting.
	293	Note:
	294	The user specified masks and data selections will be reset
	295	if a new scantable is set. This method should be called before
[1824]	296	setting data selections (set_selection) and/or masks (set_mask).
[1819]	297	"""
	298	from asap import scantable
	299	if isinstance(scan, scantable):
	300	if self._data is not None:
	301	if scan != self._data:
	302	self._data = scan
	303	# reset
	304	self._reset()
[1897]	305	msg = "A new scantable is set to the plotter. "\
	306	"The masks and data selections are reset."
[1819]	307	asaplog.push( msg )
	308	else:
	309	self._data = scan
	310	self._reset()
	311	else:
	312	msg = "Input is not a scantable"
	313	raise TypeError(msg)
[1547]	314
[1819]	315	# ranges become invalid when unit changes
	316	if self._abcunit and self._abcunit != self._data.get_unit():
	317	self._minmaxx = None
	318	self._minmaxy = None
	319	self._abcunit = self._data.get_unit()
	320	self._datamask = None
	321	if refresh: self.plot()
	322
[1862]	323	@asaplog_post_dec
[1819]	324	def set_mode(self, stacking=None, panelling=None, refresh=True):
[203]	325	"""
[377]	326	Set the plots look and feel, i.e. what you want to see on the plot.
[203]	327	Parameters:
	328	stacking: tell the plotter which variable to plot
[1217]	329	as line colour overlays (default 'pol')
[203]	330	panelling: tell the plotter which variable to plot
	331	across multiple panels (default 'scan'
[1819]	332	refresh: True (default) or False. If True, the plot is
[1824]	333	replotted based on the new parameter setting(s).
[1819]	334	Otherwise,the parameter(s) are set without replotting.
[203]	335	Note:
	336	Valid modes are:
	337	'beam' 'Beam' 'b': Beams
	338	'if' 'IF' 'i': IFs
	339	'pol' 'Pol' 'p': Polarisations
	340	'scan' 'Scan' 's': Scans
	341	'time' 'Time' 't': Times
	342	"""
[753]	343	msg = "Invalid mode"
	344	if not self.set_panelling(panelling) or \
	345	not self.set_stacking(stacking):
[1859]	346	raise TypeError(msg)
[1910]	347	if self._panelling == 'r':
	348	self._stacking = '_r'
[1913]	349	elif self._stacking == 'r':
	350	self._panelling = '_r'
[1819]	351	if refresh and self._data: self.plot(self._data)
[203]	352	return
	353
[554]	354	def set_panelling(self, what=None):
[1858]	355	"""Set the 'panelling' mode i.e. which type of spectra should be
	356	spread across different panels.
	357	"""
	358
[554]	359	mode = what
	360	if mode is None:
	361	mode = rcParams['plotter.panelling']
	362	md = self._translate(mode)
[203]	363	if md:
[554]	364	self._panelling = md
[226]	365	self._title = None
[1913]	366	if md == 'r':
[1910]	367	self._stacking = '_r'
[1981]	368	# you need to reset counters for multi page plotting
	369	self._reset_counters()
[203]	370	return True
	371	return False
	372
[1819]	373	def set_layout(self,rows=None,cols=None,refresh=True):
[377]	374	"""
	375	Set the multi-panel layout, i.e. how many rows and columns plots
	376	are visible.
	377	Parameters:
	378	rows: The number of rows of plots
	379	cols: The number of columns of plots
[1819]	380	refresh: True (default) or False. If True, the plot is
[1824]	381	replotted based on the new parameter setting(s).
[1819]	382	Otherwise,the parameter(s) are set without replotting.
[377]	383	Note:
	384	If no argument is given, the potter reverts to its auto-plot
	385	behaviour.
	386	"""
	387	self._rows = rows
	388	self._cols = cols
[1819]	389	if refresh and self._data: self.plot(self._data)
[377]	390	return
	391
[709]	392	def set_stacking(self, what=None):
[1858]	393	"""Set the 'stacking' mode i.e. which type of spectra should be
	394	overlayed.
	395	"""
[554]	396	mode = what
[709]	397	if mode is None:
	398	mode = rcParams['plotter.stacking']
[554]	399	md = self._translate(mode)
[203]	400	if md:
	401	self._stacking = md
[226]	402	self._lmap = None
[1913]	403	if md == 'r':
	404	self._panelling = '_r'
[1981]	405	# you need to reset counters for multi page plotting
	406	self._reset_counters()
[203]	407	return True
	408	return False
	409
[1981]	410	def _reset_counters(self):
	411	self._startrow = 0
	412	self._ipanel = -1
	413	self._panelrows = []
	414
[1897]	415	def set_range(self,xstart=None,xend=None,ystart=None,yend=None,refresh=True, offset=None):
[203]	416	"""
	417	Set the range of interest on the abcissa of the plot
	418	Parameters:
[525]	419	[x,y]start,[x,y]end: The start and end points of the 'zoom' window
[1819]	420	refresh: True (default) or False. If True, the plot is
[1824]	421	replotted based on the new parameter setting(s).
[1819]	422	Otherwise,the parameter(s) are set without replotting.
[1897]	423	offset: shift the abcissa by the given amount. The abcissa label will
	424	have '(relative)' appended to it.
[203]	425	Note:
	426	These become non-sensical when the unit changes.
	427	use plotter.set_range() without parameters to reset
	428
	429	"""
[1897]	430	self._offset = offset
[525]	431	if xstart is None and xend is None:
	432	self._minmaxx = None
[600]	433	else:
	434	self._minmaxx = [xstart,xend]
[525]	435	if ystart is None and yend is None:
	436	self._minmaxy = None
[600]	437	else:
[709]	438	self._minmaxy = [ystart,yend]
[1819]	439	if refresh and self._data: self.plot(self._data)
[203]	440	return
[709]	441
[1819]	442	def set_legend(self, mp=None, fontsize = None, mode = 0, refresh=True):
[203]	443	"""
	444	Specify a mapping for the legend instead of using the default
	445	indices:
	446	Parameters:
[1101]	447	mp: a list of 'strings'. This should have the same length
	448	as the number of elements on the legend and then maps
	449	to the indeces in order. It is possible to uses latex
	450	math expression. These have to be enclosed in r'',
	451	e.g. r'$x^{2}$'
	452	fontsize: The font size of the label (default None)
	453	mode: where to display the legend
	454	Any other value for loc else disables the legend:
[1096]	455	0: auto
	456	1: upper right
	457	2: upper left
	458	3: lower left
	459	4: lower right
	460	5: right
	461	6: center left
	462	7: center right
	463	8: lower center
	464	9: upper center
	465	10: center
[1819]	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.
[203]	469
	470	Example:
[485]	471	If the data has two IFs/rest frequencies with index 0 and 1
[203]	472	for CO and SiO:
	473	plotter.set_stacking('i')
[710]	474	plotter.set_legend(['CO','SiO'])
[203]	475	plotter.plot()
[710]	476	plotter.set_legend([r'$^{12}CO$', r'SiO'])
[203]	477	"""
	478	self._lmap = mp
[1096]	479	self._plotter.legend(mode)
[1101]	480	if isinstance(fontsize, int):
	481	from matplotlib import rc as rcp
	482	rcp('legend', fontsize=fontsize)
[1819]	483	if refresh and self._data: self.plot(self._data)
[226]	484	return
	485
[1819]	486	def set_title(self, title=None, fontsize=None, refresh=True):
[710]	487	"""
	488	Set the title of the plot. If multiple panels are plotted,
	489	multiple titles have to be specified.
[1819]	490	Parameters:
	491	refresh: True (default) or False. If True, the plot is
[1824]	492	replotted based on the new parameter setting(s).
[1819]	493	Otherwise,the parameter(s) are set without replotting.
[710]	494	Example:
	495	# two panels are visible on the plotter
	496	plotter.set_title(["First Panel","Second Panel"])
	497	"""
[226]	498	self._title = title
[1101]	499	if isinstance(fontsize, int):
	500	from matplotlib import rc as rcp
	501	rcp('axes', titlesize=fontsize)
[1819]	502	if refresh and self._data: self.plot(self._data)
[226]	503	return
	504
[1819]	505	def set_ordinate(self, ordinate=None, fontsize=None, refresh=True):
[710]	506	"""
	507	Set the y-axis label of the plot. If multiple panels are plotted,
	508	multiple labels have to be specified.
[1021]	509	Parameters:
	510	ordinate: a list of ordinate labels. None (default) let
	511	data determine the labels
[1819]	512	refresh: True (default) or False. If True, the plot is
[1824]	513	replotted based on the new parameter setting(s).
[1819]	514	Otherwise,the parameter(s) are set without replotting.
[710]	515	Example:
	516	# two panels are visible on the plotter
	517	plotter.set_ordinate(["First Y-Axis","Second Y-Axis"])
	518	"""
[257]	519	self._ordinate = ordinate
[1101]	520	if isinstance(fontsize, int):
	521	from matplotlib import rc as rcp
	522	rcp('axes', labelsize=fontsize)
	523	rcp('ytick', labelsize=fontsize)
[1819]	524	if refresh and self._data: self.plot(self._data)
[257]	525	return
	526
[1819]	527	def set_abcissa(self, abcissa=None, fontsize=None, refresh=True):
[710]	528	"""
	529	Set the x-axis label of the plot. If multiple panels are plotted,
	530	multiple labels have to be specified.
[1021]	531	Parameters:
	532	abcissa: a list of abcissa labels. None (default) let
	533	data determine the labels
[1819]	534	refresh: True (default) or False. If True, the plot is
[1824]	535	replotted based on the new parameter setting(s).
[1819]	536	Otherwise,the parameter(s) are set without replotting.
[710]	537	Example:
	538	# two panels are visible on the plotter
	539	plotter.set_ordinate(["First X-Axis","Second X-Axis"])
	540	"""
[257]	541	self._abcissa = abcissa
[1101]	542	if isinstance(fontsize, int):
	543	from matplotlib import rc as rcp
	544	rcp('axes', labelsize=fontsize)
	545	rcp('xtick', labelsize=fontsize)
[1819]	546	if refresh and self._data: self.plot(self._data)
[257]	547	return
	548
[1819]	549	def set_colors(self, colmap, refresh=True):
[377]	550	"""
[1217]	551	Set the colours to be used. The plotter will cycle through
	552	these colours when lines are overlaid (stacking mode).
[1021]	553	Parameters:
[1217]	554	colmap: a list of colour names
[1819]	555	refresh: True (default) or False. If True, the plot is
[1824]	556	replotted based on the new parameter setting(s).
[1819]	557	Otherwise,the parameter(s) are set without replotting.
[710]	558	Example:
	559	plotter.set_colors("red green blue")
	560	# If for example four lines are overlaid e.g I Q U V
	561	# 'I' will be 'red', 'Q' will be 'green', U will be 'blue'
	562	# and 'V' will be 'red' again.
	563	"""
[1217]	564	if isinstance(colmap,str):
	565	colmap = colmap.split()
	566	self._plotter.palette(0, colormap=colmap)
[1819]	567	if refresh and self._data: self.plot(self._data)
[710]	568
[1217]	569	# alias for english speakers
	570	set_colours = set_colors
	571
[1819]	572	def set_histogram(self, hist=True, linewidth=None, refresh=True):
[1021]	573	"""
	574	Enable/Disable histogram-like plotting.
	575	Parameters:
	576	hist: True (default) or False. The fisrt default
	577	is taken from the .asaprc setting
	578	plotter.histogram
[1819]	579	refresh: True (default) or False. If True, the plot is
[1824]	580	replotted based on the new parameter setting(s).
[1819]	581	Otherwise,the parameter(s) are set without replotting.
[1021]	582	"""
[1023]	583	self._hist = hist
[1101]	584	if isinstance(linewidth, float) or isinstance(linewidth, int):
	585	from matplotlib import rc as rcp
	586	rcp('lines', linewidth=linewidth)
[1819]	587	if refresh and self._data: self.plot(self._data)
[1023]	588
[1819]	589	def set_linestyles(self, linestyles=None, linewidth=None, refresh=True):
[710]	590	"""
[734]	591	Set the linestyles to be used. The plotter will cycle through
	592	these linestyles when lines are overlaid (stacking mode) AND
	593	only one color has been set.
[710]	594	Parameters:
	595	linestyles: a list of linestyles to use.
	596	'line', 'dashed', 'dotted', 'dashdot',
	597	'dashdotdot' and 'dashdashdot' are
	598	possible
[1819]	599	refresh: True (default) or False. If True, the plot is
[1824]	600	replotted based on the new parameter setting(s).
[1819]	601	Otherwise,the parameter(s) are set without replotting.
[710]	602	Example:
	603	plotter.set_colors("black")
	604	plotter.set_linestyles("line dashed dotted dashdot")
	605	# If for example four lines are overlaid e.g I Q U V
	606	# 'I' will be 'solid', 'Q' will be 'dashed',
	607	# U will be 'dotted' and 'V' will be 'dashdot'.
	608	"""
	609	if isinstance(linestyles,str):
	610	linestyles = linestyles.split()
	611	self._plotter.palette(color=0,linestyle=0,linestyles=linestyles)
[1101]	612	if isinstance(linewidth, float) or isinstance(linewidth, int):
	613	from matplotlib import rc as rcp
	614	rcp('lines', linewidth=linewidth)
[1819]	615	if refresh and self._data: self.plot(self._data)
[710]	616
[1819]	617	def set_font(self, refresh=True,**kwargs):
[1101]	618	"""
	619	Set font properties.
	620	Parameters:
	621	family: one of 'sans-serif', 'serif', 'cursive', 'fantasy', 'monospace'
	622	style: one of 'normal' (or 'roman'), 'italic' or 'oblique'
	623	weight: one of 'normal or 'bold'
	624	size: the 'general' font size, individual elements can be adjusted
	625	seperately
[1819]	626	refresh: True (default) or False. If True, the plot is
[1824]	627	replotted based on the new parameter setting(s).
[1819]	628	Otherwise,the parameter(s) are set without replotting.
[1101]	629	"""
	630	from matplotlib import rc as rcp
[1547]	631	fdict = {}
	632	for k,v in kwargs.iteritems():
	633	if v:
	634	fdict[k] = v
[1556]	635	self._fp = FontProperties(**fdict)
[1819]	636	if refresh and self._data: self.plot(self._data)
[1101]	637
[1819]	638	def set_panellayout(self,layout=[],refresh=True):
	639	"""
	640	Set the layout of subplots.
	641	Parameters:
	642	layout: a list of subplots layout in figure coordinate (0-1),
[1824]	643	i.e., fraction of the figure width or height.
[1819]	644	The order of elements should be:
	645	[left, bottom, right, top, horizontal space btw panels,
[1824]	646	vertical space btw panels].
[1819]	647	refresh: True (default) or False. If True, the plot is
[1824]	648	replotted based on the new parameter setting(s).
[1819]	649	Otherwise,the parameter(s) are set without replotting.
	650	Note
	651	* When layout is not specified, the values are reset to the defaults
	652	of matplotlib.
[1824]	653	* If any element is set to be None, the current value is adopted.
[1819]	654	"""
	655	if layout == []: self._panellayout=self._reset_panellayout()
[1824]	656	else:
[1819]	657	self._panellayout=[None]*6
	658	self._panellayout[0:len(layout)]=layout
	659	#print "panel layout set to ",self._panellayout
	660	if refresh and self._data: self.plot(self._data)
	661
	662	def _reset_panellayout(self):
	663	ks=map(lambda x: 'figure.subplot.'+x,
	664	['left','bottom','right','top','hspace','wspace'])
	665	return map(matplotlib.rcParams.get,ks)
	666
[1259]	667	def plot_lines(self, linecat=None, doppler=0.0, deltachan=10, rotate=90.0,
[1146]	668	location=None):
	669	"""
[1158]	670	Plot a line catalog.
	671	Parameters:
	672	linecat: the linecatalog to plot
[1168]	673	doppler: the velocity shift to apply to the frequencies
[1158]	674	deltachan: the number of channels to include each side of the
	675	line to determine a local maximum/minimum
[1927]	676	rotate: the rotation (in degrees) for the text label (default 90.0)
[1158]	677	location: the location of the line annotation from the 'top',
	678	'bottom' or alternate (None - the default)
[1165]	679	Notes:
	680	If the spectrum is flagged no line will be drawn in that location.
[1146]	681	"""
[1259]	682	if not self._data:
	683	raise RuntimeError("No scantable has been plotted yet.")
[1146]	684	from asap._asap import linecatalog
[1259]	685	if not isinstance(linecat, linecatalog):
	686	raise ValueError("'linecat' isn't of type linecatalog.")
	687	if not self._data.get_unit().endswith("Hz"):
	688	raise RuntimeError("Can only overlay linecatalogs when data is in frequency.")
[1739]	689	from numpy import ma
[1146]	690	for j in range(len(self._plotter.subplots)):
	691	self._plotter.subplot(j)
	692	lims = self._plotter.axes.get_xlim()
[1153]	693	for row in range(linecat.nrow()):
[1259]	694	# get_frequency returns MHz
	695	base = { "GHz": 1000.0, "MHz": 1.0, "Hz": 1.0e-6 }
	696	restf = linecat.get_frequency(row)/base[self._data.get_unit()]
[1165]	697	c = 299792.458
[1174]	698	freq = restf*(1.0-doppler/c)
[1146]	699	if lims[0] < freq < lims[1]:
	700	if location is None:
	701	loc = 'bottom'
[1153]	702	if row%2: loc='top'
[1146]	703	else: loc = location
[1153]	704	maxys = []
	705	for line in self._plotter.axes.lines:
	706	v = line._x
	707	asc = v[0] < v[-1]
	708
	709	idx = None
	710	if not asc:
	711	if v[len(v)-1] <= freq <= v[0]:
	712	i = len(v)-1
	713	while i>=0 and v[i] < freq:
	714	idx = i
	715	i-=1
	716	else:
	717	if v[0] <= freq <= v[len(v)-1]:
	718	i = 0
	719	while i<len(v) and v[i] < freq:
	720	idx = i
	721	i+=1
	722	if idx is not None:
	723	lower = idx - deltachan
	724	upper = idx + deltachan
	725	if lower < 0: lower = 0
	726	if upper > len(v): upper = len(v)
	727	s = slice(lower, upper)
[1167]	728	y = line._y[s]
[1165]	729	maxy = ma.maximum(y)
	730	if isinstance( maxy, float):
	731	maxys.append(maxy)
[1164]	732	if len(maxys):
	733	peak = max(maxys)
[1165]	734	if peak > self._plotter.axes.get_ylim()[1]:
	735	loc = 'bottom'
[1164]	736	else:
	737	continue
[1157]	738	self._plotter.vline_with_label(freq, peak,
	739	linecat.get_name(row),
	740	location=loc, rotate=rotate)
[1153]	741	self._plotter.show(hardrefresh=False)
[1146]	742
[1153]	743
[710]	744	def save(self, filename=None, orientation=None, dpi=None):
	745	"""
[1927]	746	Save the plot to a file. The known formats are 'png', 'ps', 'eps'.
[377]	747	Parameters:
	748	filename: The name of the output file. This is optional
	749	and autodetects the image format from the file
	750	suffix. If non filename is specified a file
	751	called 'yyyymmdd_hhmmss.png' is created in the
	752	current directory.
[709]	753	orientation: optional parameter for postscript only (not eps).
	754	'landscape', 'portrait' or None (default) are valid.
	755	If None is choosen for 'ps' output, the plot is
	756	automatically oriented to fill the page.
[710]	757	dpi: The dpi of the output non-ps plot
[377]	758	"""
[709]	759	self._plotter.save(filename,orientation,dpi)
[377]	760	return
[709]	761
[1862]	762	@asaplog_post_dec
[1819]	763	def set_mask(self, mask=None, selection=None, refresh=True):
[525]	764	"""
[734]	765	Set a plotting mask for a specific polarization.
	766	This is useful for masking out "noise" Pangle outside a source.
	767	Parameters:
[920]	768	mask: a mask from scantable.create_mask
	769	selection: the spectra to apply the mask to.
[1819]	770	refresh: True (default) or False. If True, the plot is
[1824]	771	replotted based on the new parameter setting(s).
[1819]	772	Otherwise,the parameter(s) are set without replotting.
[734]	773	Example:
[920]	774	select = selector()
	775	select.setpolstrings("Pangle")
	776	plotter.set_mask(mymask, select)
[734]	777	"""
[710]	778	if not self._data:
[920]	779	msg = "Can only set mask after a first call to plot()"
[1859]	780	raise RuntimeError(msg)
[920]	781	if len(mask):
	782	if isinstance(mask, list) or isinstance(mask, tuple):
	783	self._usermask = array(mask)
[710]	784	else:
[920]	785	self._usermask = mask
	786	if mask is None and selection is None:
	787	self._usermask = []
	788	self._maskselection = None
	789	if isinstance(selection, selector):
[947]	790	self._maskselection = {'b': selection.get_beams(),
	791	's': selection.get_scans(),
	792	'i': selection.get_ifs(),
	793	'p': selection.get_pols(),
[920]	794	't': [] }
[710]	795	else:
[920]	796	self._maskselection = None
[1819]	797	if refresh: self.plot(self._data)
[710]	798
[709]	799	def _slice_indeces(self, data):
	800	mn = self._minmaxx[0]
	801	mx = self._minmaxx[1]
	802	asc = data[0] < data[-1]
	803	start=0
	804	end = len(data)-1
	805	inc = 1
	806	if not asc:
	807	start = len(data)-1
	808	end = 0
	809	inc = -1
	810	# find min index
[1819]	811	#while start > 0 and data[start] < mn:
	812	# start+= inc
	813	minind=start
	814	for ind in xrange(start,end+inc,inc):
	815	if data[ind] > mn: break
	816	minind=ind
[709]	817	# find max index
[1819]	818	#while end > 0 and data[end] > mx:
	819	# end-=inc
	820	#if end > 0: end +=1
	821	maxind=end
	822	for ind in xrange(end,start-inc,-inc):
	823	if data[ind] < mx: break
	824	maxind=ind
	825	start=minind
	826	end=maxind
[709]	827	if start > end:
[1819]	828	return end,start+1
	829	elif start < end:
	830	return start,end+1
	831	else:
	832	return start,end
[709]	833
[710]	834	def _reset(self):
[920]	835	self._usermask = []
[710]	836	self._usermaskspectra = None
[1897]	837	self._offset = None
[920]	838	self.set_selection(None, False)
	839
	840	def _plot(self, scan):
[947]	841	savesel = scan.get_selection()
	842	sel = savesel + self._selection
[1910]	843	order = self._get_sortstring([self._panelling,self._stacking])
	844	if order:
	845	sel.set_order(order)
[947]	846	scan.set_selection(sel)
[920]	847	d = {'b': scan.getbeam, 's': scan.getscan,
[1949]	848	#'i': scan.getif, 'p': scan.getpol, 't': scan._gettime,
	849	'i': scan.getif, 'p': scan.getpol, 't': scan.get_time,
[1910]	850	'r': int, '_r': int}
[920]	851
[1148]	852	polmodes = dict(zip(self._selection.get_pols(),
	853	self._selection.get_poltypes()))
	854	# this returns either a tuple of numbers or a length (ncycles)
	855	# convert this into lengths
	856	n0,nstack0 = self._get_selected_n(scan)
	857	if isinstance(n0, int): n = n0
[1175]	858	else: n = len(n0)
[1148]	859	if isinstance(nstack0, int): nstack = nstack0
[1175]	860	else: nstack = len(nstack0)
[1913]	861	nptot = n
[1582]	862	maxpanel, maxstack = 16,16
[1913]	863	if nstack > maxstack:
	864	msg ="Scan to be overlayed contains more than %d selections.\n" \
	865	"Selecting first %d selections..." % (maxstack, maxstack)
[920]	866	asaplog.push(msg)
[1861]	867	asaplog.post('WARN')
[998]	868	nstack = min(nstack,maxstack)
[1981]	869	#n = min(n,maxpanel)
	870	n = min(n-self._ipanel-1,maxpanel)
[1910]	871
[920]	872	if n > 1:
	873	ganged = rcParams['plotter.ganged']
[1819]	874	if self._panelling == 'i':
	875	ganged = False
[920]	876	if self._rows and self._cols:
	877	n = min(n,self._rows*self._cols)
	878	self._plotter.set_panels(rows=self._rows,cols=self._cols,
[1819]	879	# nplots=n,ganged=ganged)
	880	nplots=n,layout=self._panellayout,ganged=ganged)
[920]	881	else:
[1819]	882	# self._plotter.set_panels(rows=n,cols=0,nplots=n,ganged=ganged)
	883	self._plotter.set_panels(rows=n,cols=0,nplots=n,layout=self._panellayout,ganged=ganged)
[920]	884	else:
[1819]	885	# self._plotter.set_panels()
	886	self._plotter.set_panels(layout=self._panellayout)
[1913]	887	#r = 0
[1981]	888	r = self._startrow
[920]	889	nr = scan.nrow()
	890	a0,b0 = -1,-1
	891	allxlim = []
[1018]	892	allylim = []
[1981]	893	#newpanel=True
	894	newpanel=False
[920]	895	panelcount,stackcount = 0,0
[1981]	896	# If this is not the first page
	897	if r > 0:
	898	# panelling value of the prev page
	899	a0 = d[self._panelling](r-1)
	900	# set the initial stackcount large not to plot
	901	# the start row automatically
	902	stackcount = nstack
	903
[1002]	904	while r < nr:
[920]	905	a = d[self._panelling](r)
	906	b = d[self._stacking](r)
	907	if a > a0 and panelcount < n:
	908	if n > 1:
	909	self._plotter.subplot(panelcount)
	910	self._plotter.palette(0)
	911	#title
	912	xlab = self._abcissa and self._abcissa[panelcount] \
	913	or scan._getabcissalabel()
[1897]	914	if self._offset and not self._abcissa:
	915	xlab += " (relative)"
[920]	916	ylab = self._ordinate and self._ordinate[panelcount] \
	917	or scan._get_ordinate_label()
[1547]	918	self._plotter.set_axes('xlabel', xlab)
	919	self._plotter.set_axes('ylabel', ylab)
[920]	920	lbl = self._get_label(scan, r, self._panelling, self._title)
[1913]	921	#if self._panelling == 'r': lbl = ''
[920]	922	if isinstance(lbl, list) or isinstance(lbl, tuple):
	923	if 0 <= panelcount < len(lbl):
	924	lbl = lbl[panelcount]
	925	else:
	926	# get default label
	927	lbl = self._get_label(scan, r, self._panelling, None)
	928	self._plotter.set_axes('title',lbl)
	929	newpanel = True
[1913]	930	stackcount = 0
[920]	931	panelcount += 1
[1981]	932	# save the start row to plot this panel for future revisit.
	933	if self._panelling != 'r' and \
	934	len(self._panelrows) < self._ipanel+1+panelcount:
	935	self._panelrows += [r]
	936
[1944]	937	#if (b > b0 or newpanel) and stackcount < nstack:
	938	if stackcount < nstack and (newpanel or (a == a0 and b > b0)):
[920]	939	y = []
	940	if len(polmodes):
	941	y = scan._getspectrum(r, polmodes[scan.getpol(r)])
	942	else:
	943	y = scan._getspectrum(r)
	944	m = scan._getmask(r)
[1739]	945	from numpy import logical_not, logical_and
[920]	946	if self._maskselection and len(self._usermask) == len(m):
	947	if d[self._stacking](r) in self._maskselection[self._stacking]:
	948	m = logical_and(m, self._usermask)
[1739]	949	from numpy import ma, array
[1897]	950	x = array(scan._getabcissa(r))
	951	if self._offset:
	952	x += self._offset
[1116]	953	y = ma.masked_array(y,mask=logical_not(array(m,copy=False)))
[920]	954	if self._minmaxx is not None:
	955	s,e = self._slice_indeces(x)
	956	x = x[s:e]
	957	y = y[s:e]
[1096]	958	if len(x) > 1024 and rcParams['plotter.decimate']:
	959	fac = len(x)/1024
[920]	960	x = x[::fac]
	961	y = y[::fac]
	962	llbl = self._get_label(scan, r, self._stacking, self._lmap)
	963	if isinstance(llbl, list) or isinstance(llbl, tuple):
	964	if 0 <= stackcount < len(llbl):
	965	# use user label
	966	llbl = llbl[stackcount]
	967	else:
	968	# get default label
	969	llbl = self._get_label(scan, r, self._stacking, None)
	970	self._plotter.set_line(label=llbl)
[1023]	971	plotit = self._plotter.plot
	972	if self._hist: plotit = self._plotter.hist
[1146]	973	if len(x) > 0:
	974	plotit(x,y)
	975	xlim= self._minmaxx or [min(x),max(x)]
	976	allxlim += xlim
	977	ylim= self._minmaxy or [ma.minimum(y),ma.maximum(y)]
	978	allylim += ylim
[1819]	979	else:
	980	xlim = self._minmaxx or []
	981	allxlim += xlim
	982	ylim= self._minmaxy or []
	983	allylim += ylim
[920]	984	stackcount += 1
[1981]	985	a0=a
	986	b0=b
[920]	987	# last in colour stack -> autoscale x
[1819]	988	if stackcount == nstack and len(allxlim) > 0:
[920]	989	allxlim.sort()
[1819]	990	self._plotter.subplots[panelcount-1]['axes'].set_xlim([allxlim[0],allxlim[-1]])
[920]	991	# clear
	992	allxlim =[]
	993
	994	newpanel = False
[1981]	995	#a0=a
	996	#b0=b
[920]	997	# ignore following rows
[1981]	998	if (panelcount == n and stackcount == nstack) or (r == nr-1):
[1018]	999	# last panel -> autoscale y if ganged
[1819]	1000	if rcParams['plotter.ganged'] and len(allylim) > 0:
[1018]	1001	allylim.sort()
	1002	self._plotter.set_limits(ylim=[allylim[0],allylim[-1]])
[998]	1003	break
[920]	1004	r+=1 # next row
[1981]	1005
	1006	# save the current counter for multi-page plotting
	1007	self._startrow = r+1
	1008	self._ipanel += panelcount
[1913]	1009	if self._plotter.figmgr.casabar:
[1981]	1010	if self._ipanel >= nptot-1:
[1913]	1011	self._plotter.figmgr.casabar.disable_next()
	1012	else:
	1013	self._plotter.figmgr.casabar.enable_next()
[1981]	1014	if self._ipanel + 1 - panelcount > 0:
	1015	self._plotter.figmgr.casabar.enable_prev()
	1016	else:
	1017	self._plotter.figmgr.casabar.disable_prev()
	1018
[947]	1019	#reset the selector to the scantable's original
	1020	scan.set_selection(savesel)
[1824]	1021
[1819]	1022	#temporary switch-off for older matplotlib
	1023	#if self._fp is not None:
	1024	if self._fp is not None and getattr(self._plotter.figure,'findobj',False):
[1556]	1025	for o in self._plotter.figure.findobj(Text):
	1026	o.set_fontproperties(self._fp)
[920]	1027
[1910]	1028	def _get_sortstring(self, lorders):
	1029	d0 = {'s': 'SCANNO', 'b': 'BEAMNO', 'i':'IFNO',
	1030	'p': 'POLNO', 'c': 'CYCLENO', 't' : 'TIME', 'r':None, '_r':None }
[1944]	1031	if not (type(lorders) == list) and not (type(lorders) == tuple):
[1910]	1032	return None
	1033	if len(lorders) > 0:
	1034	lsorts = []
	1035	for order in lorders:
	1036	ssort = d0[order]
	1037	if ssort:
	1038	lsorts.append(ssort)
	1039	return lsorts
	1040	return None
	1041
[1582]	1042	def set_selection(self, selection=None, refresh=True, **kw):
[1819]	1043	"""
	1044	Parameters:
	1045	selection: a selector object (default unset the selection)
	1046	refresh: True (default) or False. If True, the plot is
[1824]	1047	replotted based on the new parameter setting(s).
[1819]	1048	Otherwise,the parameter(s) are set without replotting.
	1049	"""
[1582]	1050	if selection is None:
	1051	# reset
	1052	if len(kw) == 0:
	1053	self._selection = selector()
	1054	else:
	1055	# try keywords
	1056	for k in kw:
	1057	if k not in selector.fields:
	1058	raise KeyError("Invalid selection key '%s', valid keys are %s" % (k, selector.fields))
	1059	self._selection = selector(**kw)
	1060	elif isinstance(selection, selector):
	1061	self._selection = selection
	1062	else:
	1063	raise TypeError("'selection' is not of type selector")
	1064
[1910]	1065	order = self._get_sortstring([self._panelling,self._stacking])
	1066	if order:
	1067	self._selection.set_order(order)
[1819]	1068	if refresh and self._data: self.plot(self._data)
[920]	1069
	1070	def _get_selected_n(self, scan):
[1148]	1071	d1 = {'b': scan.getbeamnos, 's': scan.getscannos,
[1910]	1072	'i': scan.getifnos, 'p': scan.getpolnos, 't': scan.ncycle,
	1073	'r': scan.nrow, '_r': False}
[1148]	1074	d2 = { 'b': self._selection.get_beams(),
	1075	's': self._selection.get_scans(),
	1076	'i': self._selection.get_ifs(),
	1077	'p': self._selection.get_pols(),
[1910]	1078	't': self._selection.get_cycles(),
	1079	'r': False, '_r': 1}
[920]	1080	n = d2[self._panelling] or d1[self._panelling]()
	1081	nstack = d2[self._stacking] or d1[self._stacking]()
	1082	return n,nstack
	1083
	1084	def _get_label(self, scan, row, mode, userlabel=None):
[1153]	1085	if isinstance(userlabel, list) and len(userlabel) == 0:
	1086	userlabel = " "
[947]	1087	pms = dict(zip(self._selection.get_pols(),self._selection.get_poltypes()))
[920]	1088	if len(pms):
	1089	poleval = scan._getpollabel(scan.getpol(row),pms[scan.getpol(row)])
	1090	else:
	1091	poleval = scan._getpollabel(scan.getpol(row),scan.poltype())
	1092	d = {'b': "Beam "+str(scan.getbeam(row)),
[1819]	1093	#'s': scan._getsourcename(row),
	1094	's': "Scan "+str(scan.getscan(row))+\
	1095	" ("+str(scan._getsourcename(row))+")",
[920]	1096	'i': "IF"+str(scan.getif(row)),
[964]	1097	'p': poleval,
[1910]	1098	't': str(scan.get_time(row)),
	1099	'r': "row "+str(row),
[1913]	1100	#'_r': str(scan.get_time(row))+",\nIF"+str(scan.getif(row))+", "+poleval+", Beam"+str(scan.getbeam(row)) }
	1101	'_r': "" }
[920]	1102	return userlabel or d[mode]
[1153]	1103
[1819]	1104	def plotazel(self, scan=None, outfile=None):
[1391]	1105	"""
[1696]	1106	plot azimuth and elevation versus time of a scantable
[1391]	1107	"""
[1923]	1108	visible = rcParams['plotter.gui']
[1696]	1109	from matplotlib import pylab as PL
	1110	from matplotlib.dates import DateFormatter, timezone
	1111	from matplotlib.dates import HourLocator, MinuteLocator,SecondLocator, DayLocator
[1391]	1112	from matplotlib.ticker import MultipleLocator
[1739]	1113	from numpy import array, pi
[1923]	1114	if not visible or not self._visible:
	1115	PL.ioff()
	1116	from matplotlib.backends.backend_agg import FigureCanvasAgg
	1117	PL.gcf().canvas.switch_backends(FigureCanvasAgg)
[1819]	1118	self._data = scan
	1119	self._outfile = outfile
[1556]	1120	dates = self._data.get_time(asdatetime=True)
[1391]	1121	t = PL.date2num(dates)
	1122	tz = timezone('UTC')
	1123	PL.cla()
	1124	PL.ioff()
	1125	PL.clf()
[1819]	1126	# Adjust subplot layouts
[1923]	1127	if len(self._panellayout) != 6:
	1128	self.set_panellayout(refresh=False)
[1819]	1129	lef, bot, rig, top, wsp, hsp = self._panellayout
	1130	PL.gcf().subplots_adjust(left=lef,bottom=bot,right=rig,top=top,
	1131	wspace=wsp,hspace=hsp)
[1824]	1132
[1391]	1133	tdel = max(t) - min(t)
	1134	ax = PL.subplot(2,1,1)
	1135	el = array(self._data.get_elevation())*180./pi
	1136	PL.ylabel('El [deg.]')
	1137	dstr = dates[0].strftime('%Y/%m/%d')
	1138	if tdel > 1.0:
	1139	dstr2 = dates[len(dates)-1].strftime('%Y/%m/%d')
	1140	dstr = dstr + " - " + dstr2
	1141	majloc = DayLocator()
	1142	minloc = HourLocator(range(0,23,12))
	1143	timefmt = DateFormatter("%b%d")
[1696]	1144	elif tdel > 24./60.:
	1145	timefmt = DateFormatter('%H:%M')
	1146	majloc = HourLocator()
	1147	minloc = MinuteLocator(30)
[1391]	1148	else:
[1696]	1149	timefmt = DateFormatter('%H:%M')
	1150	majloc = MinuteLocator(interval=5)
	1151	minloc = SecondLocator(30)
	1152
[1391]	1153	PL.title(dstr)
[1819]	1154	if tdel == 0.0:
	1155	th = (t - PL.floor(t))*24.0
	1156	PL.plot(th,el,'o',markersize=2, markerfacecolor='b', markeredgecolor='b')
	1157	else:
	1158	PL.plot_date(t,el,'o', markersize=2, markerfacecolor='b', markeredgecolor='b',tz=tz)
	1159	#ax.grid(True)
	1160	ax.xaxis.set_major_formatter(timefmt)
	1161	ax.xaxis.set_major_locator(majloc)
	1162	ax.xaxis.set_minor_locator(minloc)
[1391]	1163	ax.yaxis.grid(True)
[1819]	1164	yloc = MultipleLocator(30)
	1165	ax.set_ylim(0,90)
	1166	ax.yaxis.set_major_locator(yloc)
[1391]	1167	if tdel > 1.0:
	1168	labels = ax.get_xticklabels()
	1169	# PL.setp(labels, fontsize=10, rotation=45)
	1170	PL.setp(labels, fontsize=10)
[1819]	1171
[1391]	1172	# Az plot
	1173	az = array(self._data.get_azimuth())*180./pi
	1174	if min(az) < 0:
	1175	for irow in range(len(az)):
	1176	if az[irow] < 0: az[irow] += 360.0
	1177
[1819]	1178	ax2 = PL.subplot(2,1,2)
	1179	#PL.xlabel('Time (UT [hour])')
	1180	PL.ylabel('Az [deg.]')
	1181	if tdel == 0.0:
	1182	PL.plot(th,az,'o',markersize=2, markeredgecolor='b',markerfacecolor='b')
	1183	else:
	1184	PL.plot_date(t,az,'o', markersize=2,markeredgecolor='b',markerfacecolor='b',tz=tz)
	1185	ax2.xaxis.set_major_formatter(timefmt)
	1186	ax2.xaxis.set_major_locator(majloc)
	1187	ax2.xaxis.set_minor_locator(minloc)
	1188	#ax2.grid(True)
	1189	ax2.set_ylim(0,360)
[1696]	1190	ax2.yaxis.grid(True)
[1819]	1191	#hfmt = DateFormatter('%H')
	1192	#hloc = HourLocator()
	1193	yloc = MultipleLocator(60)
	1194	ax2.yaxis.set_major_locator(yloc)
	1195	if tdel > 1.0:
	1196	labels = ax2.get_xticklabels()
	1197	PL.setp(labels, fontsize=10)
	1198	PL.xlabel('Time (UT [day])')
	1199	else:
	1200	PL.xlabel('Time (UT [hour])')
	1201
[1391]	1202	PL.ion()
	1203	PL.draw()
[1819]	1204	if (self._outfile is not None):
	1205	PL.savefig(self._outfile)
[1391]	1206
[1819]	1207	def plotpointing(self, scan=None, outfile=None):
[1391]	1208	"""
	1209	plot telescope pointings
	1210	"""
[1923]	1211	visible = rcParams['plotter.gui']
[1696]	1212	from matplotlib import pylab as PL
[1819]	1213	from numpy import array, pi
[1923]	1214	if not visible or not self._visible:
	1215	PL.ioff()
	1216	from matplotlib.backends.backend_agg import FigureCanvasAgg
	1217	PL.gcf().canvas.switch_backends(FigureCanvasAgg)
[1819]	1218	self._data = scan
	1219	self._outfile = outfile
[1391]	1220	dir = array(self._data.get_directionval()).transpose()
	1221	ra = dir[0]*180./pi
	1222	dec = dir[1]*180./pi
	1223	PL.cla()
[1819]	1224	#PL.ioff()
[1391]	1225	PL.clf()
[1819]	1226	# Adjust subplot layouts
[1923]	1227	if len(self._panellayout) != 6:
	1228	self.set_panellayout(refresh=False)
[1819]	1229	lef, bot, rig, top, wsp, hsp = self._panellayout
	1230	PL.gcf().subplots_adjust(left=lef,bottom=bot,right=rig,top=top,
	1231	wspace=wsp,hspace=hsp)
	1232	ax = PL.gca()
	1233	#ax = PL.axes([0.1,0.1,0.8,0.8])
	1234	#ax = PL.axes([0.1,0.1,0.8,0.8])
[1391]	1235	ax.set_aspect('equal')
[1696]	1236	PL.plot(ra, dec, 'b,')
[1391]	1237	PL.xlabel('RA [deg.]')
	1238	PL.ylabel('Declination [deg.]')
	1239	PL.title('Telescope pointings')
	1240	[xmin,xmax,ymin,ymax] = PL.axis()
	1241	PL.axis([xmax,xmin,ymin,ymax])
[1819]	1242	#PL.ion()
[1391]	1243	PL.draw()
[1819]	1244	if (self._outfile is not None):
	1245	PL.savefig(self._outfile)
	1246
	1247	# plot total power data
	1248	# plotting in time is not yet implemented..
[1862]	1249	@asaplog_post_dec
[1819]	1250	def plottp(self, scan=None, outfile=None):
	1251	if self._plotter.is_dead:
	1252	if hasattr(self._plotter.figmgr,'casabar'):
	1253	del self._plotter.figmgr.casabar
	1254	self._plotter = self._newplotter()
	1255	self._plotter.figmgr.casabar=self._newcasabar()
	1256	self._plotter.hold()
	1257	self._plotter.clear()
	1258	from asap import scantable
	1259	if not self._data and not scan:
	1260	msg = "Input is not a scantable"
	1261	raise TypeError(msg)
	1262	if isinstance(scan, scantable):
	1263	if self._data is not None:
	1264	if scan != self._data:
	1265	self._data = scan
	1266	# reset
	1267	self._reset()
	1268	else:
	1269	self._data = scan
	1270	self._reset()
	1271	# ranges become invalid when abcissa changes?
	1272	#if self._abcunit and self._abcunit != self._data.get_unit():
	1273	# self._minmaxx = None
	1274	# self._minmaxy = None
	1275	# self._abcunit = self._data.get_unit()
	1276	# self._datamask = None
	1277
	1278	# Adjust subplot layouts
	1279	if len(self._panellayout) !=6: self.set_panellayout(refresh=False)
	1280	lef, bot, rig, top, wsp, hsp = self._panellayout
	1281	self._plotter.figure.subplots_adjust(
	1282	left=lef,bottom=bot,right=rig,top=top,wspace=wsp,hspace=hsp)
	1283	if self._plotter.figmgr.casabar: self._plotter.figmgr.casabar.disable_button()
	1284	self._plottp(self._data)
	1285	if self._minmaxy is not None:
	1286	self._plotter.set_limits(ylim=self._minmaxy)
	1287	self._plotter.release()
	1288	self._plotter.tidy()
	1289	self._plotter.show(hardrefresh=False)
	1290	return
	1291
	1292	def _plottp(self,scan):
	1293	"""
	1294	private method for plotting total power data
	1295	"""
	1296	from numpy import ma, array, arange, logical_not
	1297	r=0
	1298	nr = scan.nrow()
	1299	a0,b0 = -1,-1
	1300	allxlim = []
	1301	allylim = []
	1302	y=[]
	1303	self._plotter.set_panels()
	1304	self._plotter.palette(0)
	1305	#title
	1306	#xlab = self._abcissa and self._abcissa[panelcount] \
	1307	# or scan._getabcissalabel()
	1308	#ylab = self._ordinate and self._ordinate[panelcount] \
	1309	# or scan._get_ordinate_label()
	1310	xlab = self._abcissa or 'row number' #or Time
	1311	ylab = self._ordinate or scan._get_ordinate_label()
	1312	self._plotter.set_axes('xlabel',xlab)
	1313	self._plotter.set_axes('ylabel',ylab)
	1314	lbl = self._get_label(scan, r, 's', self._title)
	1315	if isinstance(lbl, list) or isinstance(lbl, tuple):
	1316	# if 0 <= panelcount < len(lbl):
	1317	# lbl = lbl[panelcount]
	1318	# else:
	1319	# get default label
	1320	lbl = self._get_label(scan, r, self._panelling, None)
	1321	self._plotter.set_axes('title',lbl)
	1322	y=array(scan._get_column(scan._getspectrum,-1))
	1323	m = array(scan._get_column(scan._getmask,-1))
	1324	y = ma.masked_array(y,mask=logical_not(array(m,copy=False)))
	1325	x = arange(len(y))
	1326	# try to handle spectral data somewhat...
	1327	l,m = y.shape
	1328	if m > 1:
	1329	y=y.mean(axis=1)
	1330	plotit = self._plotter.plot
	1331	llbl = self._get_label(scan, r, self._stacking, None)
	1332	self._plotter.set_line(label=llbl)
	1333	if len(x) > 0:
	1334	plotit(x,y)
	1335
	1336
	1337	# forwards to matplotlib.Figure.text
	1338	def figtext(self, args, *kwargs):
	1339	"""
	1340	Add text to figure at location x,y (relative 0-1 coords).
	1341	This method forwards args and *kwargs to a Matplotlib method,
	1342	matplotlib.Figure.text.
	1343	See the method help for detailed information.
	1344	"""
	1345	self._plotter.text(args, *kwargs)
	1346	# end matplotlib.Figure.text forwarding function
	1347
	1348
	1349	# printing header information
[1862]	1350	@asaplog_post_dec
[1819]	1351	def print_header(self, plot=True, fontsize=9, logger=False, selstr='', extrastr=''):
	1352	"""
	1353	print data (scantable) header on the plot and/or logger.
	1354	Parameters:
[1824]	1355	plot: whether or not print header info on the plot.
[1819]	1356	fontsize: header font size (valid only plot=True)
	1357	logger: whether or not print header info on the logger.
	1358	selstr: additional selection string (not verified)
	1359	extrastr: additional string to print (not verified)
	1360	"""
[1859]	1361	if not plot and not logger:
	1362	return
	1363	if not self._data:
	1364	raise RuntimeError("No scantable has been set yet.")
[1824]	1365	# Now header will be printed on plot and/or logger.
	1366	# Get header information and format it.
[1819]	1367	ssum=self._data.__str__()
	1368	# Print Observation header to the upper-left corner of plot
	1369	if plot:
	1370	headstr=[ssum[ssum.find('Observer:'):ssum.find('Flux Unit:')]]
	1371	headstr.append(ssum[ssum.find('Beams:'):ssum.find('Observer:')]
	1372	+ssum[ssum.find('Rest Freqs:'):ssum.find('Abcissa:')])
	1373	if extrastr != '': headstr[0]=extrastr+'\n'+headstr[0]
	1374	#headstr[1]='Data File: '+(filestr or 'unknown')+'\n'+headstr[1]
	1375	ssel='*Selections*\n'+(selstr+self._data.get_selection().__str__() or 'none')
	1376	headstr.append(ssel)
	1377	nstcol=len(headstr)
[1824]	1378
[1819]	1379	self._plotter.hold()
	1380	for i in range(nstcol):
	1381	self._plotter.figure.text(0.03+float(i)/nstcol,0.98,
	1382	headstr[i],
	1383	horizontalalignment='left',
	1384	verticalalignment='top',
	1385	fontsize=fontsize)
	1386	import time
	1387	self._plotter.figure.text(0.99,0.0,
	1388	time.strftime("%a %d %b %Y %H:%M:%S %Z"),
	1389	horizontalalignment='right',
	1390	verticalalignment='bottom',fontsize=8)
	1391	self._plotter.release()
	1392	del headstr, ssel
	1393	if logger:
	1394	asaplog.push("----------------\n Plot Summary\n----------------")
	1395	asaplog.push(extrastr)
	1396	asaplog.push(ssum[ssum.find('Beams:'):])
	1397	del ssum

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

Context Navigation

source: trunk/python/asapplotter.py@ 1987

Download in other formats: