def create(self, data):
"""
Does the plotting.
"""
if len(data[0][1]) != len(data[1][1]):
raise ScatterException(
'Number of instances for each competitor must be the same')
step = int((self.x_max - self.x_min) / 10)
x = np.arange(self.x_min, self.x_max + self.x_min + step, step)
# "good" area
plt.plot(x, x, color='black', ls=':', lw=1.5, zorder=3)
plt.plot(x, 0.1 * x, 'g:', lw=1.5, zorder=3)
plt.plot(x, 10 * x, 'g:', lw=1.5, zorder=3)
plt.fill_between(x,
0.1 * x,
10 * x,
facecolor='green',
alpha=0.15,
zorder=3)
plt.xlim([self.x_min, self.x_max])
plt.ylim([self.y_min, self.y_max])
# timeout lines
if self.tol:
plt.axvline(self.timeout,
linewidth=1,
color='red',
ls=':',
label=str(self.timeout),
zorder=3)
plt.axhline(self.timeout,
linewidth=1,
color='red',
ls=':',
label=str(self.timeout),
zorder=3)
if self.tlb_loc == 'after':
plt.text(2 * self.x_min,
self.timeout + self.x_max / 40,
self.t_label,
horizontalalignment='left',
verticalalignment='bottom',
fontsize=self.f_props['size'] * 0.8)
plt.text(self.timeout + self.x_max / 40,
2 * self.x_min,
self.t_label,
horizontalalignment='left',
verticalalignment='bottom',
fontsize=self.f_props['size'] * 0.8,
rotation=90)
else:
plt.text(2 * self.x_min,
self.timeout - self.x_max / 3.5,
self.t_label,
horizontalalignment='left',
verticalalignment='bottom',
fontsize=self.f_props['size'] * 0.8)
plt.text(self.timeout - self.x_max / 3.5,
2 * self.x_min,
self.t_label,
horizontalalignment='left',
verticalalignment='bottom',
fontsize=self.f_props['size'] * 0.8,
rotation=90)
# scatter
plt.scatter(data[0][1],
data[1][1],
c=self.marker_style['color'],
marker=self.marker_style['marker'],
s=self.marker_style['size'],
alpha=self.alpha,
zorder=5)
# axes' labels
if self.x_label:
plt.xlabel(self.x_label)
else:
plt.xlabel(data[0][0])
if self.y_label:
plt.ylabel(self.y_label)
else:
plt.ylabel(data[1][0])
# turning the grid on
if not self.no_grid:
plt.grid(True, color='black', ls=':', lw=1, zorder=1)
# choosing logarithmic scales
ax = plt.gca()
ax.set_xscale('log')
ax.set_yscale('log')
# setting ticks font properties
# set_*ticklables() seems to be not needed in matplotlib 1.5.0
if float(mpl_version[:3]) < 1.5:
ax.set_xticklabels(ax.get_xticks(), self.f_props)
ax.set_yticklabels(ax.get_yticks(), self.f_props)
# formatter
majorFormatter = plt.LogFormatterMathtext(base=10)
ax.xaxis.set_major_formatter(majorFormatter)
ax.yaxis.set_major_formatter(majorFormatter)
# setting frame thickness
for i in ax.spines.itervalues():
i.set_linewidth(1)
plt.savefig(self.save_to,
bbox_inches='tight',
transparent=self.transparent)
def create(self, data):
"""
Does the plotting.
"""
# making lines
coords = []
for d in data:
coords.append(np.arange(1, len(d[1]) + 1)) # xs (separate for each line)
coords.append(np.array(sorted(d[1])))
lines = plt.plot(*coords, zorder=3)
# setting line styles
if self.byname == False: # by default, assign fist line to best tool
lmap = lambda i: i
else: # assign line styles by tool name
tnames = [(d[0], i) for i, d in enumerate(data)]
tnames.sort(key=lambda pair: pair[0])
tmap = {tn[1]: i for i, tn in enumerate(tnames)}
lmap = lambda i: tmap[i]
for i, l in enumerate(lines):
plt.setp(l, **self.linestyles[lmap(i) % len(self.linestyles)])
# turning the grid on
if not self.no_grid:
plt.grid(True, color=self.grid_color, ls=self.grid_style, lw=self.grid_width, zorder=1)
# axes limits
plt.xlim(self.x_min, self.x_max if self.x_max else math.ceil(max([d[2] for d in data]) / float(100)) * 100)
plt.ylim(self.y_min, self.y_max if self.y_max else self.timeout)
# axes labels
if self.x_label:
plt.xlabel(self.x_label)
else:
plt.xlabel('instances')
if self.y_label:
plt.ylabel(self.y_label)
else:
plt.ylabel('CPU time (s)')
# choosing logarithmic scales if needed
ax = plt.gca()
if self.x_log:
ax.set_xscale('log')
if self.y_log:
ax.set_yscale('log')
# setting ticks
# plt.xticks(np.arange(self.x_min, self.x_max + 1, 2))
# if not self.y_log:
# # plt.yticks(list(plt.yticks()[0]) + [self.timeout])
# ax.set_yticks(range(0, 2 * (int(self.y_max) if self.y_max else int(self.timeout)), 200))
# setting ticks font properties
# set_*ticklables() seems to be not needed in matplotlib 1.5.0
if float(mpl_version[:3]) < 1.5:
ax.set_xticklabels(ax.get_xticks(), self.f_props)
ax.set_yticklabels(ax.get_yticks(), self.f_props)
strFormatter = plt.FormatStrFormatter('%d')
logFormatter = plt.LogFormatterMathtext(base=10)
ax.xaxis.set_major_formatter(strFormatter if not self.x_log else logFormatter)
ax.yaxis.set_major_formatter(strFormatter if not self.y_log else logFormatter)
# making the legend
if self.lgd_loc != 'off':
lgtext = [d[0] for d in data]
lg = ax.legend(lines, lgtext, ncol=self.lgd_ncol, loc=self.lgd_loc, fancybox=self.lgd_fancy, shadow=self.lgd_shadow if self.lgd_alpha == 1.0 else False)
fr = lg.get_frame()
fr.set_lw(1)
fr.set_alpha(self.lgd_alpha)
fr.set_edgecolor('black')
# setting frame thickness
for i in six.itervalues(ax.spines):
i.set_linewidth(1)
plt.savefig(self.save_to, bbox_inches='tight', transparent=self.transparent)
def pdfout(s3d,
plane,
smoothx=0,
smoothy=0,
name='',
xmin=0,
xmax=-1,
ymin=0,
ymax=-1,
errsize=0.5,
label=None,
vmin=None,
vmax=None,
ra=None,
dec=None,
source='',
ra2=None,
dec2=None,
source2='',
median=None,
axis='WCS',
size=(11.5, 9.15),
psf=None,
cmap='viridis',
dy1=0.95,
dy2=0.97,
twoc=True,
norm='lin',
fs=24):
""" Simple 2d-image plot function
Parameters:
----------
plane : np.array
Either a 2d array for normal images, or a list of three 2d arrays for
an RGB image
smoothx, smoothy : integer
Integer values of gaussian smoothing for the input plane
xmin, xmax, ymin, ymax : integer
Zoom into the specific pixel values of the input plane
errsize : float
Size of error radius with which to highlight a specific region
label : str
Label of region
ra, dec : sexagesimal
Location of label
label2 : str
Label of region 2
ra2, dec2 : sexagesimal
Location of label 2
median : integer
median filter the input plane
axis : string
WCS axis or none
psf : float
FWHM of the PSF which we draw at the left bottom corner of the output
cmap : string
Color map, default virdis
twoc : boolean
Write text in image in black and white letters
norm : string
How to normalize the RGB image (lin, sqrt, log)
fs : integer
Fontsize (default 24)
"""
if xmax == -1:
xmax = plane.shape[0]
if ymax == -1:
ymax = plane.shape[1]
plane = plane[ymin:ymax, xmin:xmax]
if twoc == True:
myeffect = withStroke(foreground="w", linewidth=4)
kwargs = dict(path_effects=[myeffect])
else:
kwargs = {}
# hfont = {'fontname':'Helvetica'}
if smoothx > 0:
plane = blur_image(plane, smoothx, smoothy)
if median != None:
plane = sp.ndimage.filters.median_filter(plane,
median,
mode='constant')
if ra != None and dec != None:
try:
posx, posy = s3d.skytopix(ra, dec)
except TypeError:
posx, posy = s3d.sexatopix(ra, dec)
if xmin != 0:
posx -= xmin
if ymin != 0:
posy -= ymin
if ra2 != None and dec2 != None:
try:
posx2, posy2 = s3d.skytopix(ra2, dec2)
except TypeError:
posx2, posy2 = s3d.sexatopix(ra2, dec2)
if xmin != 0:
posx2 -= xmin
if ymin != 0:
posy2 -= ymin
if plane.ndim == 2:
fig = plt.figure(figsize=size)
if fs > 20 and axis == 'WCS':
fig.subplots_adjust(bottom=0.22, top=0.99, left=0.12, right=0.96)
elif axis == 'WCS':
fig.subplots_adjust(bottom=0.20, top=0.99, left=0.08, right=0.96)
else:
fig.subplots_adjust(bottom=0.005,
top=0.995,
left=0.005,
right=0.94)
else:
fig = plt.figure(figsize=(9, 9))
fig.subplots_adjust(bottom=0.18, top=0.99, left=0.19, right=0.99)
ax = fig.add_subplot(1, 1, 1)
ax.set_ylim(5, plane.shape[0] - 5)
ax.set_xlim(5, plane.shape[1] - 5)
if norm == 'lin':
plt.imshow(
plane,
vmin=vmin,
vmax=vmax, #extent=[],
cmap=cmap,
interpolation="nearest") #, aspect="auto")#, cmap='Greys')
elif norm == 'log':
plt.imshow(
plane,
vmin=vmin,
vmax=vmax, #extent=[],
cmap=cmap,
norm=LogNorm(),
interpolation="nearest") #, aspect="auto")#, cmap='Greys')
if plane.ndim == 2:
bar = plt.colorbar(shrink=0.9, pad=0.01)
if not label == None:
bar.set_label(label, size=fs + 15, family='serif')
bar.ax.tick_params(labelsize=max(24, fs - 4))
if norm == 'log':
bar.formatter = plt.LogFormatterMathtext()
labels = [item.get_text() for item in bar.ax.get_yticklabels()]
newlab = []
for label in labels:
if norm == 'log':
newl = label.replace('mathdefault', 'mathrm', 1)
else:
newl = r'$%s$' % label
newlab.append(newl)
bar.ax.set_yticklabels(newlab)
# bar.update_ticks()
if psf != None:
psfrad = psf / 2.3538 / s3d.pixsky
psfsize = plt.Circle((8 * plane.shape[0] / 9., plane.shape[1] / 9.),
psfrad,
color='black',
alpha=1,
**kwargs)
ax.add_patch(psfsize)
plt.text(8 * plane.shape[0] / 9.,
plane.shape[0] / 6.5,
r'PSF',
fontsize=fs,
ha='center',
va='center',
**kwargs)
if ra != None and dec != None:
psfrad = errsize / 2.3538 / s3d.pixsky
psfsize = plt.Circle((posx, posy),
psfrad,
lw=5,
fill=False,
color='white',
**kwargs)
ax.add_patch(psfsize)
psfsize = plt.Circle((posx, posy),
psfrad,
lw=1.5,
fill=False,
color='black',
**kwargs)
ax.add_patch(psfsize)
plt.text(posx,
posy * dy1,
source,
fontsize=fs,
ha='center',
va='top',
**kwargs)
if ra2 != None and dec2 != None:
# psfrad = 0.2*errsize/2.3538/s3d.pixsky
# psfsize = plt.Circle((posx2,posy2), psfrad, lw=5, fill=False,
# color='white', **kwargs)
# ax.add_patch(psfsize)
# psfsize = plt.Circle((posx2,posy2), psfrad, lw=1.5, fill=False,
# color='black', **kwargs)
# ax.add_patch(psfsize)
print posx2, posy2
ax.plot(posx2 + 1, posy2 + 1, 'o', ms=9, mec='black', c='black')
plt.text(posx2,
posy2 * dy2,
source2,
fontsize=fs,
ha='center',
va='top',
**kwargs)
if axis == 'WCS':
[xticks, xlabels], [yticks, ylabels] = _createaxis(s3d, plane)
sel = (xmin + 5 < xticks) * (xmax - 5 > xticks)
xticks = xticks[sel]
xlabels = xlabels[sel]
xticks -= xmin
sel = (ymin + 5 < yticks) * (ymax - 5 > yticks)
yticks = yticks[sel]
ylabels = ylabels[sel]
yticks -= ymin
plt.xticks(rotation=50)
plt.yticks(rotation=50)
ax.set_xticks(xticks)
ax.set_xticklabels(xlabels, size=fs)
ax.set_yticks(yticks)
ax.set_yticklabels(ylabels, size=fs)
ax.set_xlabel(r'Right Ascension (J2000)', size=fs)
ax.set_ylabel(r'Declination (J2000)', size=fs)
else:
ax.yaxis.set_major_formatter(plt.NullFormatter())
ax.xaxis.set_major_formatter(plt.NullFormatter())
plt.savefig('%s_%s_%s.pdf' % (s3d.inst, s3d.target, name))
plt.close(fig)