def main(argv):
if len(argv) >= 2 and argv[0].upper() in ['A', 'B', 'AB']:
protFiles = argv[1:]
vial = argv[0]
else:
sys.exit(
"\nusage: python generate_prest_report_multi.py <vial> <results_file1> (<results_file2> ...)\n where vial is one of 'A', 'B' or 'AB'."
)
color_cycle = color.colors_from_cmap(len(protFiles), 'tab10')
plt.rc('axes', prop_cycle=cycler('color', color_cycle.tolist()))
#plt.rcParams['axes.color_cycle'] =
p = plt.figure(figsize=(16, 12))
i = 0
for protFile in protFiles:
plotPrestReport(protFile, vial.upper(), p)
i += 1
handles, labels = p.get_axes()[-1].get_legend_handles_labels()
p.legend(handles,
labels,
bbox_to_anchor=(0.5, 0., 0.45, 0.45),
shadow=True,
fontsize='x-large',
loc='upper left')
#plt.show()
plt.savefig("result.svg")
def colfaxfig(simIa=None,
simIbc=None,
simII=None,
contours=True,
redshiftcircle=True,
clobber=False,
**plotargs):
from pytools import plotsetup
from matplotlib import pyplot as pl
from mpltools import color
from matplotlib import cm
fig = plotsetup.fullpaperfig([8, 4])
simIa, simIbc, simII = doublecircle('colfax',
simIa,
simIbc,
simII,
clobber=clobber,
circle1bands=['f139m', 'f127m'],
circle2bands=['f139m', 'f153m'],
contours=contours,
redshiftcircle=redshiftcircle,
**plotargs)
fig = pl.gcf()
ax1, ax2 = fig.axes
fig.subplots_adjust(left=0.1,
bottom=0.18,
right=0.89,
top=0.95,
wspace=0.1)
ax1.set_xlim(-0.5, 0.4)
ax1.set_ylim(-0.7, 0.4)
ax2.set_xlim(-0.5, 0.4)
ax2.set_ylim(-0.4, 0.4)
ax2.text(
0.95,
0.95,
'GND12Col',
transform=ax2.transAxes,
ha='right',
va='top',
color='k',
fontsize=15,
)
ax2.yaxis.labelpad = 20
colorlist = color.colors_from_cmap(2, cm.jet)
ax1.text(0.15, 0.17, 'z=1.9', ha='left', va='top', color=colorlist[0])
ax1.text(-0.23, 0.32, 'z=2.4', ha='left', va='top', color=colorlist[1])
pl.draw()
return simIa, simIbc, simII
def plot_all_annuli(self,
projection="astro degrees mollweide",
radius=None,
center=None,
cmap="Set1",
**kwargs):
assert projection in [
"astro degrees aitoff",
"astro degrees mollweide",
"astro hours aitoff",
"astro hours mollweide",
"astro globe",
"astro zoom",
]
skw_dict = dict(projection=projection)
if projection in ["astro globe", "astro zoom"]:
assert center is not None, "you must specify a center"
skw_dict = dict(projection=projection, center=center)
if projection == "astro zoom":
assert radius is not None, "you must specify a radius"
skw_dict = dict(projection=projection,
center=center,
radius=radius)
fig, ax = plt.subplots(subplot_kw=skw_dict)
# get the colors to use
n_verts = self._n_detectors * (self._n_detectors - 1) / 2
colors = mpl_color.colors_from_cmap(n_verts, cmap=cmap)
for i, (d1, d2) in enumerate(combinations(self._detectors.keys(), 2)):
_ = self.plot_annulus(d1,
d2,
projection=projection,
center=center,
radius=radius,
ax=ax,
edgecolor=colors[i],
**kwargs)
return fig
def plotData(self):
self.DataPlot.clear()
# self.plotItem = self.DataPlot.getPlotItem()
pa = self.plotAxes
an0 = self.ax_name(pa[0])
an1 = self.ax_name(pa[1])
an2 = self.ax_name(pa[2])
if self.display_items[self.display_num] == 'Waterfall':
grouped = self.item.groupby(an0)
colors = np.array(255*color.colors_from_cmap(len(grouped), cmap='gnuplot', start=0.2, stop=0.8))
colors = colors.astype(int)
i = -1
for label, data in grouped:
i += 1
pen = pg.mkPen(pg.mkColor(colors[i]))
x = np.array(data[an1])
y = np.array(data[an2])
self.plotItem.plot(x, y, pen= pen)
elif self.display_items[self.display_num] == '2d plot':
data = self.item.data
x= data[an0]
y= data[an1]
z= np.array(data[an2])
# # define grid.
nx = len(x.unique())
ny = len(y.unique())
# print(nx,ny)
# nx = 512
# ny = 500
xi = np.linspace(min(x),max(x),nx)
yi = np.linspace(min(y),max(y),ny)
# grid the data.
grid_z0 = griddata((x, y), z, (xi[None,:], yi[:,None]),method='nearest')
img = pg.ImageItem(grid_z0.T)
self.colorBar.setImageItem(img)
self.plotItem.addItem(img)
else:
data = self.item.data
x = data[an0]
y = data[an1]
self.plotItem.plot(x, y)
def plotData(self):
self.DataPlot.clear()
# self.plotItem = self.DataPlot.getPlotItem()
pa = self.plotAxes
if self.display_items[self.display_num] == 'Waterfall':
g_axis = self.ax_name(pa[0])
grouped = self.item.groupby(g_axis)
colors = np.array(255*color.colors_from_cmap(len(grouped), cmap='gnuplot', start=0.2, stop=0.8))
colors = colors.astype(int)
xax = self.ax_name(pa[1])
yax = self.ax_name(pa[2])
i = -1
for label, data in grouped:
i += 1
pen = pg.mkPen(pg.mkColor(colors[i]))
x = np.array(data[xax])
y = np.array(data[yax])
self.plotItem.plot(x, y, pen= pen)
elif self.display_items[self.display_num] == '2d plot':
data = self.item.data
values = data.ix[:, pa[2]]
x = data.ix[:, pa[0]]
y = data.ix[:, pa[1]]
nx = min(500,len(x.unique()))*1j
ny = min(500,len(y.unique()))*1j
print(nx,ny)
grid_x, grid_y = np.mgrid[0:1:nx, 0:1:ny]
grid_z0 = griddata((x,y), np.array(values), (grid_x, grid_y), method='nearest')
img = pg.ImageItem(grid_z0)
self.colorBar.setImageItem(img)
self.plotItem.addItem(img)
else:
data = self.item.data
x = data.ix[:, pa[0]]
y = data.ix[:, pa[1]]
self.plotItem.plot(x, y)
def stonefig(simIa=None,
simIbc=None,
simII=None,
contours=True,
redshiftcircle=True,
clobber=False,
**plotargs):
from pytools import plotsetup
from mpltools import color
from matplotlib import cm
fig = plotsetup.fullpaperfig(figsize=[7.5, 3.5])
fig.clf()
ax1 = fig.add_subplot(1, 2, 1)
simIa, simIbc, simII = singlecircle(
'stone',
simIa,
simIbc,
simII,
clobber=clobber,
medbandx='f139m',
medbandy='f153m',
contours=contours,
redshiftcircle=False, #redshiftcircle,
**plotargs)
fig.subplots_adjust(left=0.10,
bottom=0.15,
right=0.92,
top=0.98,
wspace=0.0)
ax1 = pl.gca()
ax1.text(
0.05,
0.95,
'GND13Sto',
transform=ax1.transAxes,
ha='left',
va='top',
color='k',
fontsize=15,
)
ax2 = fig.add_subplot(1, 2, 2, sharex=ax1, sharey=ax1)
singlecircle('stone',
medbandx='f139m',
medbandy='f153m',
contours=False,
points=False,
redshiftcircle=True,
**plotargs)
#plot_redshift_circle(z_range=STONE.z_range, tobs=STONE.tobs,
# medbandx='f139m', medbandy='f153m',
# source='salt2', coloredaxislabels=False, marker='o' )
ax2.yaxis.set_label_position('right')
ax2.yaxis.set_ticks_position('right')
ax2.yaxis.set_ticks_position('both')
pl.setp(ax2.yaxis.get_label(), rotation=-90)
colorlist = color.colors_from_cmap(9, cm.jet)
ax2.text(0.1, -0.15, 'z=1.6', ha='left', va='top', color=colorlist[0])
ax2.text(-0.06, -0.18, '1.7', ha='left', va='top', color=colorlist[1])
ax2.text(0.26, 0.06, '1.8', ha='left', va='top', color=colorlist[2])
ax2.text(0.14, 0.0, '1.9', ha='left', va='top', color='darkcyan')
ax2.text(-0.1, -0.19, '2.0', ha='right', va='top', color='limegreen')
ax2.text(-0.09,
0.23,
'2.1',
ha='right',
va='bottom',
color='darkolivegreen')
ax2.text(0.13, 0.27, '2.2', ha='left', va='top', color=colorlist[6])
ax2.text(-0.1, -0.07, '2.3', ha='center', va='center', color=colorlist[7])
ax2.text(-0.23,
-0.14,
'z=2.4',
ha='right',
va='bottom',
color=colorlist[8])
ax1.set_xlim(-0.35, 0.35)
ax1.set_ylim(-0.3, 0.45)
pl.draw()
return simIa, simIbc, simII
def plot_all_annuli(
self,
projection="astro degrees mollweide",
radius=None,
center=None,
cmap="Set1",
threeD=True,
use_all=False,
**kwargs,
):
if not threeD:
assert projection in [
"astro degrees aitoff",
"astro degrees mollweide",
"astro hours aitoff",
"astro hours mollweide",
"astro globe",
"astro zoom",
]
skw_dict = dict(projection=projection)
if projection in ["astro globe", "astro zoom"]:
assert center is not None, "you must specify a center"
skw_dict = dict(projection=projection, center=center)
if projection == "astro zoom":
assert radius is not None, "you must specify a radius"
skw_dict = dict(projection=projection,
center=center,
radius=radius)
fig, ax = plt.subplots(subplot_kw=skw_dict)
else:
fig = ipv.figure()
ipv.pylab.style.box_off()
ipv.pylab.style.axes_off()
ax = None
# get the colors to use
if use_all:
n_verts = self._n_detectors * (self._n_detectors - 1) / 2
colors = mpl_color.colors_from_cmap(int(n_verts), cmap=cmap)
for i, (d1,
d2) in enumerate(combinations(self._detectors.keys(), 2)):
_ = self.plot_annulus(
d1,
d2,
projection=projection,
center=center,
radius=radius,
ax=ax,
edgecolor=colors[i],
threeD=threeD,
color=colors[i],
**kwargs,
)
if threeD:
loc1 = self._detectors[d1].location.get_cartesian_coord(
).xyz.value
loc2 = self._detectors[d2].location.get_cartesian_coord(
).xyz.value
ipv.plot(
np.array([loc1[0], loc2[0]]),
np.array([loc1[1], loc2[1]]),
np.array([loc1[2], loc2[2]]),
color=colors[i],
)
else:
colors = mpl_color.colors_from_cmap(len(self._detectors) - 1,
cmap=cmap)
det_list = list(self._detectors.keys())
d1 = det_list[0]
for i, d2 in enumerate(det_list[1:]):
_ = self.plot_annulus(
d1,
d2,
projection=projection,
center=center,
radius=radius,
ax=ax,
edgecolor=colors[i],
threeD=threeD,
color=colors[i],
**kwargs,
)
if threeD:
loc1 = self._detectors[d1].location.get_cartesian_coord(
).xyz.value
loc2 = self._detectors[d2].location.get_cartesian_coord(
).xyz.value
ipv.plot(
np.array([loc1[0], loc2[0]]),
np.array([loc1[1], loc2[1]]),
np.array([loc1[2], loc2[2]]),
color=colors[i],
)
if threeD:
ipv.scatter(
*(self._grb_radius *
self._grb.location.get_cartesian_coord("gcrs").xyz.value /
np.linalg.norm(
self._grb.location.get_cartesian_coord("gcrs").xyz.value)
)[np.newaxis].T,
marker="sphere",
color="green",
)
ipv.show()
return fig
