Revision: 8959
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=8959&view=rev
Author: jswhit
Date: 2011-02-08 12:58:49 +0000 (Tue, 08 Feb 2011)
Log Message:
-----------
celestial allsky map example from Tom Loredo.
Added Paths:
-----------
trunk/toolkits/basemap/examples/allskymap.py
trunk/toolkits/basemap/examples/allskymap_cr_example.py
Added: trunk/toolkits/basemap/examples/allskymap.py
===================================================================
--- trunk/toolkits/basemap/examples/allskymap.py
(rev 0)
+++ trunk/toolkits/basemap/examples/allskymap.py 2011-02-08 12:58:49 UTC
(rev 8959)
@@ -0,0 +1,390 @@
+"""
+AllSkyMap is a subclass of Basemap, specialized for handling common plotting
+tasks for celestial data.
+
+It is essentially equivalent to using Basemap with full-sphere projections
+(e.g., 'hammer' or 'moll') and the `celestial` keyword set to `True`, but
+it adds a few new methods:
+
+* label_meridians for, well, labeling meridians with their longitude values;
+
+* geodesic, a replacement for Basemap.drawgreatcircle, that can correctly
+ handle geodesics that cross the limb of the map, and providing the user
+ easy control over clipping (which affects thick lines at or near the limb);
+
+* tissot, which overrides Basemap.tissot, correctly handling geodesics that
+ cross the limb of the map.
+
+Created Jan 2011 by Tom Loredo, based on Jeff Whitaker's code in Basemap's
+__init__.py module.
+"""
+
+from numpy import *
+import matplotlib.pyplot as pl
+from matplotlib.pyplot import *
+from mpl_toolkits.basemap import Basemap, pyproj
+from mpl_toolkits.basemap.pyproj import Geod
+
+__all__ = ['AllSkyMap']
+
+def angle_symbol(angle, round_to=1.0):
+ """
+ Return a string representing an angle, rounded and with a degree symbol.
+
+ This is adapted from code in mpl's projections.geo module.
+ """
+ value = np.round(angle / round_to) * round_to
+ if pl.rcParams['text.usetex'] and not pl.rcParams['text.latex.unicode']:
+ return r"$%0.0f^\circ$" % value
+ else:
+ return u"%0.0f\u00b0" % value
+
+
+class AllSkyMap(Basemap):
+ """
+ AllSkyMap is a subclass of Basemap, specialized for handling common
plotting
+ tasks for celestial data.
+
+ It is essentially equivalent to using Basemap with full-sphere projections
+ (e.g., 'hammer' or 'moll') and the `celestial` keyword set to `True`, but
+ it adds a few new methods:
+
+ * label_meridians for, well, labeling meridians with their longitude
values;
+
+ * geodesic, a replacement for Basemap.drawgreatcircle, that can correctly
+ handle geodesics that cross the limb of the map, and providing the user
+ easy control over clipping (which affects thick lines at or near the
+ limb);
+
+ * tissot, which overrides Basemap.tissot, correctly handling geodesics that
+ cross the limb of the map.
+ """
+
+ # Longitudes corresponding to east and west edges, reflecting the
+ # convention that 180 deg is the eastern edge, according to basemap's
+ # underlying projections:
+ east_lon = 180.
+ west_lon = 180.+1.e-10
+
+ def __init__(self,
+ projection='hammer',
+ lat_0=0., lon_0=0.,
+ suppress_ticks=True,
+ boundinglat=None,
+ fix_aspect=True,
+ anchor='C',
+ ax=None):
+
+ if projection != 'hammer' and projection !='moll':
+ raise ValueError('Only hammer and moll projections supported!')
+
+ # Use Basemap's init, enforcing the values of many parameters that
+ # aren't used or whose Basemap defaults would not be altered for
all-sky
+ # celestial maps.
+ Basemap.__init__(self, llcrnrlon=None, llcrnrlat=None,
+ urcrnrlon=None, urcrnrlat=None,
+ llcrnrx=None, llcrnry=None,
+ urcrnrx=None, urcrnry=None,
+ width=None, height=None,
+ projection=projection, resolution=None,
+ area_thresh=None, rsphere=1.,
+ lat_ts=None,
+ lat_1=None, lat_2=None,
+ lat_0=lat_0, lon_0=lon_0,
+ suppress_ticks=suppress_ticks,
+ satellite_height=1.,
+ boundinglat=None,
+ fix_aspect=True,
+ anchor=anchor,
+ celestial=True,
+ ax=ax)
+
+ # Keep a local ref to lon_0 for hemisphere checking.
+ self._lon_0 = self.projparams['lon_0']
+ self._limb = None
+
+ def drawmapboundary(self,color='k',linewidth=1.0,fill_color=None,\
+ zorder=None,ax=None):
+ """
+ draw boundary around map projection region, optionally
+ filling interior of region.
+
+ .. tabularcolumns:: |l|L|
+
+ ============== ====================================================
+ Keyword Description
+ ============== ====================================================
+ linewidth line width for boundary (default 1.)
+ color color of boundary line (default black)
+ fill_color fill the map region background with this
+ color (default is no fill or fill with axis
+ background color).
+ zorder sets the zorder for filling map background
+ (default 0).
+ ax axes instance to use
+ (default None, use default axes instance).
+ ============== ====================================================
+
+ returns matplotlib.collections.PatchCollection representing map
boundary.
+ """
+ # Just call the base class version, but keep a copy of the limb
+ # polygon for clipping.
+ self._limb = Basemap.drawmapboundary(self, color=color,
+ linewidth=linewidth, fill_color=fill_color, zorder=zorder, ax=ax)
+ return self._limb
+
+ def label_meridians(self, lons, fontsize=10, valign='bottom', vnudge=0,
+ halign='center', hnudge=0):
+ """
+ Label meridians with their longitude values in degrees.
+
+ This labels meridians with negative longitude l with the value 360-l;
+ for maps in celestial orientation, this means meridians to the right
+ of the central meridian are labeled from 360 to 180 (left to right).
+
+ `vnudge` and `hnudge` specify amounts in degress to nudge the labels
+ from their default placements, vertically and horizontally. This
+ values obey the map orientation, so to nudge to the right, use a
+ negative `hnudge` value.
+ """
+ # Run through (lon, lat) pairs, with lat=0 in each pair.
+ lats = len(lons)*[0.]
+ for lon,lat in zip(lons, lats):
+ x, y = self(lon+hnudge, lat+vnudge)
+ if lon < 0:
+ lon_lbl = 360 + lon
+ else:
+ lon_lbl = lon
+ pl.text(x, y, angle_symbol(lon_lbl), fontsize=fontsize,
+ verticalalignment=valign,
+ horizontalalignment=halign)
+
+ def east_hem(self, lon):
+ """
+ Return True if lon is in the eastern hemisphere of the map wrt lon_0.
+ """
+ if (lon-self._lon_0) % 360. <= self.east_lon:
+ return True
+ else:
+ return False
+
+ def geodesic(self, lon1, lat1, lon2, lat2, del_s=.01, clip=True, **kwargs):
+ """
+ Plot a geodesic curve from (lon1, lat1) to (lon2, lat2), with
+ points separated by arc length del_s. Return a list of Line2D
+ instances for the curves comprising the geodesic. If the geodesic does
+ not cross the map limb, there will be only a single curve; if it
+ crosses the limb, there will be two curves.
+ """
+
+ # TODO: Perhaps return a single Line2D instance when there is only a
+ # single segment, and a list of segments only when there are two segs?
+
+ # TODO: Check the units of del_s.
+
+ # This is based on Basemap.drawgreatcircle (which draws an *arc* of a
+ # great circle), but addresses a limitation of that method, supporting
+ # geodesics that cross the map boundary by breaking them into two
+ # segments, one in the eastern hemisphere and the other in the western.
+ gc = pyproj.Geod(a=self.rmajor,b=self.rminor)
+ az12,az21,dist = gc.inv(lon1,lat1,lon2,lat2)
+ npoints = int((dist+0.5**del_s)/del_s)
+ # Calculate lon & lat for points on the arc.
+ lonlats = gc.npts(lon1,lat1,lon2,lat2,npoints)
+ lons = [lon1]; lats = [lat1]
+ for lon, lat in lonlats:
+ lons.append(lon)
+ lats.append(lat)
+ lons.append(lon2); lats.append(lat2)
+ # Break the arc into segments as needed, when there is a longitudinal
+ # hemisphere crossing.
+ segs = []
+ seg_lons, seg_lats = [lon1], [lat1]
+ cur_hem = self.east_hem(lon1)
+ for lon, lat in zip(lons[1:], lats[1:]):
+ if self.east_hem(lon) == cur_hem:
+ seg_lons.append(lon)
+ seg_lats.append(lat)
+ else:
+ # We should interpolate a new pt at the boundary, but in
+ # the mean time just rely on the step size being small.
+ segs.append( (seg_lons, seg_lats) )
+ seg_lons, seg_lats = [lon], [lat]
+ cur_hem = not cur_hem
+ segs.append( (seg_lons, seg_lats) )
+ # Plot each segment; return a list of the mpl lines.
+ lines = []
+ for lons, lats in segs:
+ x, y = self(lons, lats)
+ if clip and self._limb:
+ line = plot(x, y, clip_path=self._limb, **kwargs)[0]
+ else:
+ line = plot(x, y, **kwargs)[0]
+ lines.append(line)
+ # If there are multiple segments and no color args, reconcile the
+ # colors, which mpl will have autoset to different values.
+ # *** Does this screw up mpl's color set sequence for later lines?
+ if not kwargs.has_key('c') or kwargs.has_key('color'):
+ if len(lines) > 1:
+ c1 = lines[0].get_color()
+ for line in lines[1:]:
+ line.set_color(c1)
+ return lines
+
+ def tissot(self,lon_0,lat_0,radius_deg,npts,ax=None,**kwargs):
+ """
+ Draw a polygon centered at ``lon_0,lat_0``. The polygon
+ approximates a circle on the surface of the earth with radius
+ ``radius_deg`` degrees latitude along longitude ``lon_0``,
+ made up of ``npts`` vertices.
+
+ The polygon represents a Tissot's indicatrix
+ (http://en.wikipedia.org/wiki/Tissot's_Indicatrix),
+ which when drawn on a map shows the distortion inherent in the map
+ projection. Tissots can be used to display azimuthally symmetric
+ directional uncertainties ("error circles").
+
+ Extra keyword ``ax`` can be used to override the default axis instance.
+
+ Other \**kwargs passed on to matplotlib.patches.Polygon.
+
+ returns a list of matplotlib.patches.Polygon objects, with two polygons
+ when the tissot crosses the limb, and just one polygon otherwise.
+ """
+
+ # TODO: Just return the polygon (not a list) when there is only one
+ # polygon? Or stick with the list for consistency?
+
+ # This is based on Basemap.tissot, but addresses a limitation of that
+ # method by handling tissots that cross the limb of the map by finding
+ # separate polygons in the eastern and western hemispheres comprising
+ # the tissot.
+ ax = kwargs.pop('ax', None) or self._check_ax()
+ g = pyproj.Geod(a=self.rmajor,b=self.rminor)
+ az12,az21,dist = g.inv(lon_0,lat_0,lon_0,lat_0+radius_deg)
+ start_hem = self.east_hem(lon_0)
+ segs1 = [self(lon_0,lat_0+radius_deg)]
+ over, segs2 = [], []
+ delaz = 360./npts
+ az = az12
+ last_lon = lon_0
+ # Note adjacent and opposite edge longitudes, in case the tissot
+ # runs over the edge.
+ if start_hem: # eastern case
+ adj_lon = self.east_lon
+ opp_lon = self.west_lon
+ else:
+ adj_lon = self.west_lon
+ opp_lon = self.east_lon
+ for n in range(npts):
+ az = az+delaz
+ # skip segments along equator (Geod can't handle equatorial arcs)
+ if np.allclose(0.,lat_0) and (np.allclose(90.,az) or
np.allclose(270.,az)):
+ continue
+ else:
+ lon, lat, az21 = g.fwd(lon_0, lat_0, az, dist)
+ # If in the starting hemisphere, add to 1st polygon seg list.
+ if self.east_hem(lon) == start_hem:
+ x, y = self(lon, lat)
+ # Add segment if it is in the map projection region.
+ if x < 1.e20 and y < 1.e20:
+ segs1.append( (x, y) )
+ last_lon = lon
+ # Otherwise, we cross hemispheres.
+ else:
+ # Trace the edge of each hemisphere.
+ x, y = self(adj_lon, lat)
+ if x < 1.e20 and y < 1.e20:
+ segs1.append( (x, y) )
+ # We presume if adj projection is okay, opposite is.
+ segs2.append( self(opp_lon, lat) )
+ # Also store the overlap in the opposite hemisphere.
+ x, y = self(lon, lat)
+ if x < 1.e20 and y < 1.e20:
+ over.append( (x, y) )
+ last_lon = lon
+ poly1 = Polygon(segs1, **kwargs)
+ ax.add_patch(poly1)
+ if segs2:
+ over.reverse()
+ segs2.extend(over)
+ poly2 = Polygon(segs2, **kwargs)
+ ax.add_patch(poly2)
+ return [poly1, poly2]
+ else:
+ return [poly1]
+
+
+if __name__ == '__main__':
+
+ # Note that Hammer & Mollweide projections enforce a 2:1 aspect ratio.
+ # Use figure size good for a 2:1 plot.
+ fig = figure(figsize=(12,6))
+
+ # Set up the projection and draw a grid.
+ map = AllSkyMap(projection='hammer')
+ # Save the bounding limb to use as a clip path later.
+ limb = map.drawmapboundary(fill_color='white')
+ map.drawparallels(np.arange(-75,76,15), linewidth=0.5, dashes=[1,2],
+ labels=[1,0,0,0], fontsize=9)
+ map.drawmeridians(np.arange(-150,151,30), linewidth=0.5, dashes=[1,2])
+
+ # Label a subset of meridians.
+ lons = np.arange(-150,151,30)
+ map.label_meridians(lons, fontsize=9, vnudge=1,
+ halign='left', hnudge=-1) # hnudge<0 shifts to right
+
+ # x, y limits are [0, 4*rt2], [0, 2*rt2].
+ rt2 = sqrt(2)
+
+ # Draw a slanted green line crossing the map limb.
+ line = plot([rt2,0], [rt2,2*rt2], 'g-')
+
+ # Draw a slanted magenta line crossing the map limb but clipped.
+ line = plot([rt2+.1,0+.1], [rt2,2*rt2], 'm-', clip_path=limb)
+
+ # Draw some geodesics.
+ # First a transparent thick blue geodesic crossing the limb but not
clipped,
+ # overlayed by a thinner red geodesic that is clipped (by default), to
+ # illustrate the effect of clipping.
+ lines = map.geodesic(120, 30, 240, 60, clip=False, c='b', lw=7, alpha=.5)
+ lines = map.geodesic(240, 60, 120, 30, c='r', lw=3, alpha=.5)
+
+ # Next two large limb-crossing geodesics with the same path, but rendered
+ # in opposite directions, one transparent blue, the other transparent
+ # yellow. They should be right on top of each other, giving a greenish
+ # brown hue.
+ lines = map.geodesic(240, -60, 120, 30, c='b', lw=2, alpha=.5)
+ lines = map.geodesic(120, 30, 240, -60, c='y', lw=2, alpha=.5)
+
+ # What happens if a geodesic is given coordinates spanning more than
+ # a single rotation? Not sure what to expect, but it shoots off the
+ # map (clipped here). Perhaps we should ensure lons are in [0, 360].
+ #lines = map.geodesic(120, 20, 240+360, 50, del_s=.2, c='g')
+
+ # Two tissots fully within the limb.
+ poly = map.tissot(60, -15, 10, 100)
+ poly = map.tissot(280, 60, 10, 100)
+ #poly = map.tissot(90, -85, 10, 100)
+
+ # Limb-spanning tissots in each quadrant.
+ # lower left:
+ poly = map.tissot(170, -60, 15, 100)
+ # upper left:
+ poly = map.tissot(175, 70, 15, 100)
+ # upper right (note negative longitude):
+ poly = map.tissot(-175, 30, 15, 100, color='r', alpha=.6)
+ # lower right:
+ poly = map.tissot(185, -40, 10, 100)
+
+ # Plot the tissot centers as "+" symbols. Note the top left symbol
+ # would cross the limb without the clip_path argument; this might be
+ # desired to enhance visibility.
+ lons = [170, 175, -175, 185]
+ lats = [-60, 70, 30, -40]
+ x, y = map(lons, lats)
+ map.scatter(x, y, s=40, marker='+', linewidths=1, edgecolors='g',
+ facecolors='none', clip_path=limb, zorder=10) # hi zorder -> top
+
+ title('AllSkyMap demo: Clipped lines, markers, geodesics, tissots')
+ show()
Added: trunk/toolkits/basemap/examples/allskymap_cr_example.py
===================================================================
--- trunk/toolkits/basemap/examples/allskymap_cr_example.py
(rev 0)
+++ trunk/toolkits/basemap/examples/allskymap_cr_example.py 2011-02-08
12:58:49 UTC (rev 8959)
@@ -0,0 +1,225 @@
+"""
+Example of astronomical use of AllSkyMap class in allskymap.py module
+
+Plot an all-sky map showing locations of the 27 highest-energy ultra-high
+energy cosmic rays detected by the Auger (south) experiment as of Aug 2007,
+and locations of 18 (fictitious!) candidate sources. Indicate CR direction
+uncertainties and source scattering scales with tissots, and show the
+nearest candidate source to each CR with geodesics.
+
+Created 2011-02-07 by Tom Loredo
+"""
+
+from cStringIO import StringIO
+import numpy as np
+from numpy import cos, sin, arccos, deg2rad, rad2deg
+import csv, re
+
+import matplotlib.pyplot as plt
+from allskymap import AllSkyMap
+from matplotlib.colors import Normalize
+from matplotlib.colorbar import ColorbarBase
+import matplotlib.ticker as ticker
+
+
+class Source:
+ """
+ Parse and store data for a celestial source.
+ """
+
+ int_re = re.compile(r'^[-+]?[0-9]+$')
+ # float_re = re.compile(r'^[-+]?[0-9]*\.?[0-9]+([eE][-+]?[0-9]+)?$')
+
+ def __init__(self, id, year, day, l, b, sig=None, **kwds):
+ self.id = int(id)
+ self.year = int(year)
+ self.day = int(day)
+ self.l = float(l)
+ self._l = deg2rad(self.l) # radians
+ self.b = float(b)
+ self._b = deg2rad(self.b) # radians
+ if sig is not None:
+ self.sig = float(sig)
+ self._sig = deg2rad(self.sig)
+ else:
+ self.sig, self._sig = None, None
+ # If extra values are specified as keywords, set them as
+ # attributes. The quick way is to use self.__dict__.update(kwds),
+ # but we want to convert to int or float values if possible.
+ # *** Consider using matplotlib.cbook.converter.
+ if kwds:
+ for key, val in kwds.items():
+ try:
+ nval = float(val)
+ # It's a number; but it may be an int.
+ if self.int_re.match(str(val)):
+ nval = int(val)
+ setattr(self, key, nval)
+ except ValueError: # non-numerical value
+ setattr(self, key, val)
+
+ def gcangle(self, src):
+ """
+ Calculate the great circle angle to another source.
+ """
+ # Use the law of cosines; note it is usually expressed with
colattitude.
+ c = sin(self._b)*sin(src._b) + \
+ cos(self._b)*cos(src._b)*cos(self._l - src._l)
+ return rad2deg(arccos(c))
+
+
+# Auger UHE cosmic ray data, Jan 2004 to Aug 2007
+# From Appendix A of Abraham et al. (2008); "Correlation of the highest-energy
+# cosmic rays with the positions of nearby active galactic nuclei,"
+# Astropart.Phys.29:188-204,2008; Erratum-ibid.30:45,2008
+
+# Year day ang S(1000) E (EeV) RA Dec Longitude Latitude
+# * = w/i 3.2 deg of AGN
+AugerData = StringIO(
+"""2004 125 47.7 252 70 267.1 -11.4 15.4 8.4
+2004 142 59.2 212 84 199.7 -34.9 -50.8 27.6 *
+2004 282 26.5 328 66 208.0 -60.3 -49.6 1.7 *
+2004 339 44.7 316 83 268.5 -61.0 -27.7 -17.0 *
+2004 343 23.4 323 63 224.5 -44.2 -34.4 13.0 *
+2005 54 35.0 373 84 17.4 -37.9 -75.6 -78.6 *
+2005 63 54.5 214 71 331.2 -1.2 58.8 -42.4 *
+2005 81 17.2 308 58 199.1 -48.6 -52.8 14.1 *
+2005 295 15.4 311 57 332.9 -38.2 4.2 -54.9 *
+2005 306 40.1 248 59 315.3 -0.3 48.8 -28.7 *
+2005 306 14.2 445 84 114.6 -43.1 -103.7 -10.3
+2006 35 30.8 398 85 53.6 -7.8 -165.9 -46.9 *
+2006 55 37.9 255 59 267.7 -60.7 -27.6 -16.5 *
+2006 81 34.0 357 79 201.1 -55.3 -52.3 7.3
+2006 185 59.1 211 83 350.0 9.6 88.8 -47.1 *
+2006 296 54.0 208 69 52.8 -4.5 -170.6 -45.7 *
+2006 299 26.0 344 69 200.9 -45.3 -51.2 17.2 *
+2007 13 14.3 762 148 192.7 -21.0 -57.2 41.8
+2007 51 39.2 247 58 331.7 2.9 63.5 -40.2 *
+2007 69 30.4 332 70 200.2 -43.4 -51.4 19.2 **
+2007 84 17.3 340 64 143.2 -18.3 -109.4 23.8 *
+2007 145 23.9 392 78 47.7 -12.8 -163.8 -54.4 *
+2007 186 44.8 248 64 219.3 -53.8 -41.7 5.9
+2007 193 18.0 469 90 325.5 -33.5 12.1 -49.0 *
+2007 221 35.3 318 71 212.7 -3.3 -21.8 54.1 *
+2007 234 33.2 365 80 185.4 -27.9 -65.1 34.5
+2007 235 42.6 276 69 105.9 -22.9 -125.2 -7.7
+""")
+AugerTable = csv.reader(AugerData, dialect='excel-tab')
+CRs = {}
+for id, row in enumerate(AugerTable):
+ # Make an integer ID from Year+Day (presumes none on same day!).
+ src = Source(id, row[0], row[1], row[7], row[8], E=float(row[4]))
+ CRs[src.id] = src
+print 'Parsed data for', len(CRs), 'UHE CRs...'
+
+# Partly fictitious candidate source locations.
+# src.id src.l_deg src.b_deg src.xProj src.yProj
+# tab-delimited
+CandData = StringIO(
+"""1 270. -28.
+2 229. -80.
+3 141. -47.
+4 172. -51.
+5 251. -51.
+6 241. -36.
+7 281. 26.
+8 241. 64.
+9 240. 64.
+10 148. 70.
+11 305. 13.
+12 98. 79.
+13 309. 19.
+14 104. 68.
+15 104. 68.
+16 321. 15.
+17 328. -14.
+18 177.5 -35.
+""")
+# Add this line above to see a tissot overlapping the map limb.
+CandTable = csv.reader(CandData, dialect='excel-tab')
+cands = {}
+for row in CandTable:
+ src = Source(row[0], 0, 0, row[1], row[2])
+ cands[src.id] = src
+print 'Parsed data for', len(cands), 'candidate sources...'
+
+# Calculate the separation matrix; track the closest candidate to each CR.
+sepn = {}
+for cr in CRs.values():
+ id, sep = None, 181.
+ for cand in cands.values():
+ val = cr.gcangle(cand)
+ sepn[cr.id, cand.id] = val
+ if val < sep:
+ id, sep = cand.id, val
+ # Store the closest candidate id and separation as a CR attribute.
+ cr.near_id = id
+ cr.near_ang = sep
+
+
+# Note that Hammer & Mollweide projections enforce a 2:1 aspect ratio.
+# Choose figure size for a 2:1 plot, with room at bottom for colorbar.
+fig = plt.figure(figsize=(12,7))
+main_ax = plt.axes([0.05, .19, .9, .75]) # rect=L,B,W,H
+
+# Set up the projection and draw a grid.
+m = AllSkyMap(ax=main_ax, projection='hammer')
+m.drawmapboundary(fill_color='white')
+m.drawparallels(np.arange(-75,76,15), linewidth=0.5, dashes=[1,2],
+ labels=[1,0,0,0], fontsize=9)
+m.drawmeridians(np.arange(-150,151,30), linewidth=0.5, dashes=[1,2])
+
+# Label a subset of meridians.
+lons = np.arange(-150,151,30)
+m.label_meridians(lons, fontsize=9, vnudge=1,
+ halign='left', hnudge=-1) # nudge<0 shifts to right
+
+# Plot CR directions.
+lvals = [src.l for src in CRs.values()]
+bvals = [src.b for src in CRs.values()]
+x, y = m(lvals, bvals)
+# These symbols will be covered by opaque tissots; plot them anyway
+# so there is a collection for the legend.
+cr_pts = m.scatter(x, y, s=8, c='r', marker='o', linewidths=.5,
+ edgecolors='none')
+
+# Plot tissots showing uncertainties, colored by energy.
+# We use 1 deg uncertainties, which are probably ~2 sigma for most events.
+Evals = np.array([src.E for src in CRs.values()])
+norm_E = Normalize(Evals.min()-10, Evals.max()+20) # -+ for jet_r for brt clrs
+# jet_r color map is in spectral sequence, with a small unsaturated
+# green range, helping to distinguish CRs from candidates.
+cmap = plt.cm.get_cmap('jet_r')
+for cr in CRs.values():
+ color = cmap(norm_E(cr.E))[0:3] # ignore alpha
+ m.tissot(cr.l, cr.b, 2., 30, ec='none', color=color, alpha=1)
+
+# Plot candidate directions.
+lvals = [src.l for src in cands.values()]
+bvals = [src.b for src in cands.values()]
+x, y = m(lvals, bvals)
+cand_pts = m.scatter(x, y, marker='+', linewidths=.5,
+ edgecolors='k', facecolors='none', zorder=10) # hi zorder -> top
+
+# Plot tissots showing possible scale of candidate scatter.
+for l, b in zip(lvals, bvals):
+ m.tissot(l, b, 5., 30, ec='none', color='g', alpha=0.25)
+
+# Show the closest candidate to each CR.
+for cr in CRs.values():
+ cand = cands[cr.near_id]
+ m.geodesic(cr.l, cr.b, cand.l, cand.b, lw=0.5, ls='-', c='g')
+
+plt.title('UHE Cosmic Rays and Candidate Sources')
+plt.legend([cr_pts, cand_pts], ['UHE CR', 'Candidate'],
+ frameon=False, loc='lower right', scatterpoints=1)
+
+# Plot a colorbar for the CR energies.
+cb_ax = plt.axes([0.25, .1, .5, .03], frameon=False) # rect=L,B,W,H
+#bar = ColorbarBase(cb_ax, cmap=cmap, orientation='horizontal',
drawedges=False)
+vals = np.linspace(Evals.min(), Evals.max(), 100)
+bar = ColorbarBase(cb_ax, values=vals, norm=norm_E, cmap=cmap,
+ orientation='horizontal', drawedges=False)
+bar.set_label('CR Energy (EeV)')
+
+plt.show()
This was sent by the SourceForge.net collaborative development platform, the
world's largest Open Source development site.
------------------------------------------------------------------------------
The ultimate all-in-one performance toolkit: Intel(R) Parallel Studio XE:
Pinpoint memory and threading errors before they happen.
Find and fix more than 250 security defects in the development cycle.
Locate bottlenecks in serial and parallel code that limit performance.
http://p.sf.net/sfu/intel-dev2devfeb
_______________________________________________
Matplotlib-checkins mailing list
Matplotlib-checkins@lists.sourceforge.net
https://lists.sourceforge.net/lists/listinfo/matplotlib-checkins
