def plot_icd_vs_mass():
galaxies = pickle.load(open('galaxies.pickle', 'rb'))
arrow_up = [[0, 0], [-1, -1], [0, 0], [0, -2], [0, 0], [1, -1], [0, 0]]
# Make figure
f1 = pyl.figure(1, figsize=(4, 6))
f1s1 = f1.add_subplot(211)
f1s2 = f1.add_subplot(212)
for galaxy in galaxies:
if galaxy.ston_I > 30. and galaxy.ICD_IH != None:
f1s1.scatter(galaxy.z,
galaxy.ICD_IH * 100,
c='0.8',
marker='o',
s=25,
edgecolor='0.8')
if galaxy.ston_V > 30. and galaxy.ICD_VJ != None:
f1s2.scatter(galaxy.z,
galaxy.ICD_VJ * 100,
c='0.8',
marker='o',
s=25,
edgecolor='0.8')
# Add the box and whiskers
galaxies2 = filter(lambda galaxy: galaxy.ston_I > 30., galaxies)
galaxies2 = pyl.asarray(galaxies2)
x = [galaxy.z for galaxy in galaxies2]
ll = 1.5
ul = 4
bins_x = pyl.arange(ll, ul, 0.5)
grid = []
for i in range(bins_x.size - 1):
xmin = bins_x[i]
xmax = bins_x[i + 1]
cond = [cond1 and cond2 for cond1, cond2 in zip(x >= xmin, x < xmax)]
grid.append(galaxies2.compress(cond))
icd = []
for i in range(len(grid)):
icd.append([galaxy.ICD_IH * 100 for galaxy in grid[i]])
from boxplot_percentile import percentile_box_plot as pbp
pbp(f1s1,
icd,
indexer=list(pyl.delete(bins_x, -1) + 0.25),
whisker_top=None,
whisker_bottom=None)
# Add the box and whiskers
galaxies = pickle.load(open('galaxies.pickle', 'rb'))
galaxies2 = filter(lambda galaxy: galaxy.ston_V > 30., galaxies)
galaxies2 = pyl.asarray(galaxies2)
x = [galaxy.z for galaxy in galaxies2]
ll = 1.5
ul = 4
bins_x = pyl.arange(ll, ul, 0.5)
grid = []
for i in range(bins_x.size - 1):
xmin = bins_x[i]
xmax = bins_x[i + 1]
cond = [cond1 and cond2 for cond1, cond2 in zip(x >= xmin, x < xmax)]
grid.append(galaxies2.compress(cond))
icd = []
for i in range(len(grid)):
icd.append([galaxy.ICD_VJ * 100 for galaxy in grid[i]])
pbp(f1s2,
icd,
indexer=list(pyl.delete(bins_x, -1) + 0.25),
whisker_top=None,
whisker_bottom=None)
f1s1.set_xlim(1.5, 3.5)
f1s2.set_xlim(1.5, 3.5)
f1s1.set_ylim(-1, 10)
f1s2.set_ylim(-1, 10)
f1s1.set_xticklabels([])
f1s2.set_xticks([1.5, 2, 2.5, 3, 3.5])
f1s1.set_ylabel(r"$\xi[i_{775},H_{160}]$ (%)")
f1s2.set_xlabel("Redshift")
f1s2.set_ylabel(r"$\xi[V_{606},J_{125}]$ (%)")
import matplotlib.font_manager
line1 = pyl.Line2D([], [],
marker='o',
mfc='0.8',
mec='0.8',
markersize=8,
linewidth=0)
line2 = pyl.Line2D([], [],
marker='s',
mec='#348ABD',
mfc='None',
markersize=10,
linewidth=0,
markeredgewidth=2)
line3 = pyl.Line2D([], [], color='#A60628', linewidth=2)
prop = matplotlib.font_manager.FontProperties(size='small')
pyl.figlegend((line1, line2, line3), ('Data', 'Quartiles', 'Medians'),
'lower center',
prop=prop,
ncol=3)
pyl.show()
def plot_icd_vs_mass():
galaxies = pickle.load(open('galaxies.pickle','rb'))
# Make figure
f1 = pyl.figure(1, figsize=(6,4))
f1s1 = f1.add_subplot(221)
f1s2 = f1.add_subplot(222)
f1s3 = f1.add_subplot(223)
f1s4 = f1.add_subplot(224)
#Upper and Lower limit arrow verts
arrowup_verts = [[0.,0.], [-1., -1], [0.,0.],
[0.,-2.], [0.,0.], [1,-1], [0,0]]
#arrowdown_verts = [[0.,0.], [-1., 1], [0.,0.],
# [0.,2.], [0.,0.], [1, 1]]
for galaxy in galaxies:
if galaxy.ston_I > 30. and galaxy.ICD_IH != None:
# Add arrows first
if galaxy.ICD_IH > 0.5:
f1s1.scatter(galaxy.Mass, 0.5*100, s=100, marker=None,
verts=arrowup_verts)
else:
f1s1.scatter(galaxy.Mass, galaxy.ICD_IH * 100, c='0.8',
marker='o', s=25, edgecolor='0.8')
f1s2.scatter(galaxy.Mass, galaxy.ICD_IH * 100, c='0.8',
marker='o', s=25, edgecolor='0.8')
if galaxy.ston_J > 30. and galaxy.ICD_JH != None:
# Add arrows first
if galaxy.ICD_JH > 0.12:
f1s3.scatter(galaxy.Mass, 12, s=100, marker=None,
verts=arrowup_verts)
else:
f1s3.scatter(galaxy.Mass, galaxy.ICD_JH * 100, c='0.8',
marker='o', s=25, edgecolor='0.8')
f1s4.scatter(galaxy.Mass, galaxy.ICD_JH * 100, c='0.8',
marker='o', s=25, edgecolor='0.8')
# Add the box and whiskers
galaxies2 = filter(lambda galaxy: galaxy.ston_I > 30., galaxies)
galaxies2 = pyl.asarray(galaxies2)
x = [galaxy.Mass for galaxy in galaxies2]
ll = 8.5
ul= 12
#bins_x =pyl.arange(8.5, 12.5, 0.5)
bins_x =pyl.array([8.5, 9., 9.5, 10., 10.5, 11., 12.])
grid = []
for i in range(bins_x.size-1):
xmin = bins_x[i]
xmax = bins_x[i+1]
cond=[cond1 and cond2 for cond1, cond2 in zip(x>=xmin, x<xmax)]
grid.append(galaxies2.compress(cond))
icd = []
for i in range(len(grid)):
icd.append([galaxy.ICD_IH*100 for galaxy in grid[i]])
from boxplot_percentile import percentile_box_plot as pbp
#bp1 = f1s1.boxplot(icd, positions=pyl.delete(bins_x,-1)+0.25, sym='')
pbp(f1s1, icd, indexer=list(pyl.delete(bins_x,-1)+0.25))
pbp(f1s2, icd, indexer=list(pyl.delete(bins_x,-1)+0.25))
# Add the box and whiskers
galaxies2 = filter(lambda galaxy: galaxy.ston_J > 30., galaxies)
galaxies2 = pyl.asarray(galaxies2)
x = [galaxy.Mass for galaxy in galaxies2]
ll = 8.5
ul= 12
#bins_x =pyl.linspace(ll, ul, 7)
#bins_x =pyl.arange(8.5, 12.5, 0.5)
bins_x =pyl.array([8.5, 9., 9.5, 10., 10.5, 11., 12.])
grid = []
for i in range(bins_x.size-1):
xmin = bins_x[i]
xmax = bins_x[i+1]
cond=[cond1 and cond2 for cond1, cond2 in zip(x>=xmin, x<xmax)]
grid.append(galaxies2.compress(cond))
icd = []
for i in range(len(grid)):
icd.append([galaxy.ICD_JH*100 for galaxy in grid[i]])
#bp2 = f1s2.boxplot(icd, positions=pyl.delete(bins_x,-1)+0.25, sym='')
pbp(f1s3, icd, indexer=list(pyl.delete(bins_x,-1)+0.25))
pbp(f1s4, icd, indexer=list(pyl.delete(bins_x,-1)+0.25))
# Finish Plot
# Tweak colors on the boxplot
#pyl.setp(bp1['boxes'], lw=2)
#pyl.setp(bp1['whiskers'], lw=2)
#pyl.setp(bp1['medians'], lw=2)
#pyl.setp(bp2['boxes'], lw=2)
#pyl.setp(bp2['whiskers'], lw=2)
#pyl.setp(bp2['medians'], lw=2)
#pyl.setp(bp['fliers'], color='#8CFF6F', marker='+')
#f1s1.axvspan(7.477, 9, facecolor='#FFFDD0', ec='None', zorder=0)
#f1s1.axvspan(11, 12, facecolor='#FFFDD0', ec='None', zorder=0)
#f1s2.axvspan(7.477, 9, facecolor='#FFFDD0', ec='None', zorder=0)
#f1s2.axvspan(11, 12, facecolor='#FFFDD0', ec='None', zorder=0)
f1s1.set_xlim(8,12)
f1s2.set_xlim(8,12)
f1s3.set_xlim(8,12)
f1s4.set_xlim(8,12)
f1s1.set_ylim(-10,50)
f1s2.set_ylim(0,15)
f1s3.set_ylim(-5,12)
f1s4.set_ylim(-1,3)
f1s1.set_xticks([8,9,10,11,12])
f1s1.set_xticklabels([])
f1s2.set_xticks([8,9,10,11,12])
f1s2.set_xticklabels([])
f1s3.set_xticks([8,9,10,11,12])
f1s4.set_xticks([8,9,10,11,12])
f1s4.set_yticks([-1, 0, 1, 2, 3])
f1s3.set_xlabel(r"Log Mass ($M_{\odot})$")
f1s1.set_ylabel(r"$\xi[i_{775},H_{160}]$ (%)")
f1s4.set_xlabel(r"Log Mass ($M_{\odot})$")
f1s3.set_ylabel(r"$\xi[J_{125},H_{160}]$ (%)")
import matplotlib.font_manager
line1 = pyl.Line2D([], [], marker='o', mfc='0.8', mec='0.8', markersize=8,
linewidth=0)
line2 = pyl.Line2D([], [], marker='s', mec='blue', mfc='None',
markersize=10, linewidth=0, markeredgewidth=2)
line3 = pyl.Line2D([], [], color='r', linewidth=2)
prop = matplotlib.font_manager.FontProperties(size='small')
pyl.figlegend((line1, line2, line3), ('Data', 'Quartiles',
'Medians'), 'lower center', prop=prop, ncol=3)
from matplotlib.patches import ConnectionPatch
xy = (12, 15)
xy2 = (8, 15)
con = ConnectionPatch(xyA=xy, xyB=xy2, coordsA='data', coordsB='data',
axesA=f1s1, axesB=f1s2)
xy = (12, 0)
xy2 = (8, 0)
con2 = ConnectionPatch(xyA=xy, xyB=xy2, coordsA='data', coordsB='data',
axesA=f1s1, axesB=f1s2)
f1s1.add_artist(con)
f1s1.add_artist(con2)
xy = (12, 3)
xy2 = (8, 3)
con = ConnectionPatch(xyA=xy, xyB=xy2, coordsA='data', coordsB='data',
axesA=f1s3, axesB=f1s4)
xy = (12, -1)
xy2 = (8, -1)
con2 = ConnectionPatch(xyA=xy, xyB=xy2, coordsA='data', coordsB='data',
axesA=f1s3, axesB=f1s4)
f1s3.add_artist(con)
f1s3.add_artist(con2)
pyl.draw()
pyl.show()
def plot_icd_vs_mass():
galaxies = pickle.load(open('galaxies.pickle','rb'))
arrow_up = [[0,0], [-1,-1], [0,0], [0,-2], [0,0], [1,-1], [0,0]]
# Make figure
f1 = pyl.figure(1, figsize=(6,4))
f1s1 = f1.add_subplot(221)
f1s2 = f1.add_subplot(222)
f1s3 = f1.add_subplot(223)
f1s4 = f1.add_subplot(224)
for galaxy in galaxies:
if galaxy.ston_I > 30. and galaxy.ICD_IH != None:
if galaxy.ICD_IH*100 < 50:
f1s1.scatter(galaxy.z, galaxy.ICD_IH * 100, c='0.8',
marker='o', s=25, edgecolor='0.8')
else:
f1s1.scatter(galaxy.z, 50, s=100, marker=None, verts=arrow_up)
f1s2.scatter(galaxy.z, galaxy.ICD_IH * 100, c='0.8',
marker='o', s=25, edgecolor='0.8')
if galaxy.ston_V > 30. and galaxy.ICD_VJ != None:
f1s3.scatter(galaxy.z, galaxy.ICD_VJ * 100, c='0.8',
marker='o', s=25, edgecolor='0.8')
f1s4.scatter(galaxy.z, galaxy.ICD_VJ * 100, c='0.8',
marker='o', s=25, edgecolor='0.8')
# Add the box and whiskers
galaxies2 = filter(lambda galaxy: galaxy.ston_I > 30., galaxies)
galaxies2 = pyl.asarray(galaxies2)
x = [galaxy.z for galaxy in galaxies2]
ll = 1.5
ul= 4
bins_x =pyl.arange(ll, ul, 0.5)
grid = []
for i in range(bins_x.size-1):
xmin = bins_x[i]
xmax = bins_x[i+1]
cond=[cond1 and cond2 for cond1, cond2 in zip(x>=xmin, x<xmax)]
grid.append(galaxies2.compress(cond))
icd = []
for i in range(len(grid)):
icd.append([galaxy.ICD_IH*100 for galaxy in grid[i]])
from boxplot_percentile import percentile_box_plot as pbp
pbp(f1s1, icd, indexer=list(pyl.delete(bins_x,-1)+0.25))
pbp(f1s2, icd, indexer=list(pyl.delete(bins_x,-1)+0.25))
# Add the box and whiskers
galaxies = pickle.load(open('galaxies.pickle','rb'))
galaxies2 = filter(lambda galaxy: galaxy.ston_V > 30., galaxies)
galaxies2 = pyl.asarray(galaxies2)
x = [galaxy.z for galaxy in galaxies2]
ll = 1.5
ul= 4
bins_x =pyl.arange(ll, ul, 0.5)
grid = []
for i in range(bins_x.size-1):
xmin = bins_x[i]
xmax = bins_x[i+1]
cond=[cond1 and cond2 for cond1, cond2 in zip(x>=xmin, x<xmax)]
grid.append(galaxies2.compress(cond))
icd = []
for i in range(len(grid)):
icd.append([galaxy.ICD_VJ*100 for galaxy in grid[i]])
pbp(f1s3, icd, indexer=list(pyl.delete(bins_x,-1)+0.25))
pbp(f1s4, icd, indexer=list(pyl.delete(bins_x,-1)+0.25))
f1s1.set_xlim(1.5, 3.5)
f1s2.set_xlim(1.5, 3.5)
f1s3.set_xlim(1.5, 3.5)
f1s4.set_xlim(1.5, 3.5)
f1s1.set_ylim(-5, 50)
f1s2.set_ylim(-1, 10)
f1s3.set_ylim(-5, 50)
f1s4.set_ylim(-1, 10)
f1s1.set_xticks([1.5,2,2.5,3,3.5])
f1s2.set_xticks([1.5,2,2.5,3,3.5])
f1s1.set_xticklabels([])
f1s2.set_xticklabels([])
f1s3.set_xticks([1.5,2,2.5,3,3.5])
f1s4.set_xticks([1.5,2,2.5,3,3.5])
f1s1.axhline(0.0, lw=2, c='b', zorder=0)
f1s2.axhline(0.0, lw=2, c='b', zorder=0)
f1s3.axhline(0.0, lw=2, c='b', zorder=0)
f1s4.axhline(0.0, lw=2, c='b', zorder=0)
f1s3.set_xlabel("Redshift")
f1s1.set_ylabel(r"$\xi[i_{775},H_{160}]$ (%)")
f1s4.set_xlabel("Redshift")
f1s3.set_ylabel(r"$\xi[V_{606},J_{125}]$ (%)")
import matplotlib.font_manager
line1 = pyl.Line2D([], [], marker='o', mfc='0.8', mec='0.8', markersize=8,
linewidth=0)
line2 = pyl.Line2D([], [], marker='s', mec='blue', mfc='None',
markersize=10, linewidth=0, markeredgewidth=2)
line3 = pyl.Line2D([], [], color='r', linewidth=2)
prop = matplotlib.font_manager.FontProperties(size='small')
pyl.figlegend((line1, line2, line3), ('Data', 'Quartiles',
'Medians'), 'lower center', prop=prop, ncol=3)
from matplotlib.patches import ConnectionPatch
xy = (3.5, 10)
xy2 = (1.5, 10)
con = ConnectionPatch(xyA=xy, xyB=xy2, coordsA='data', coordsB='data',
axesA=f1s1, axesB=f1s2)
xy = (3.5, -1)
xy2 = (1.5, -1)
con2 = ConnectionPatch(xyA=xy, xyB=xy2, coordsA='data', coordsB='data',
axesA=f1s1, axesB=f1s2)
f1s1.add_artist(con)
f1s1.add_artist(con2)
xy = (3.5, 10)
xy2 = (1.5, 10)
con = ConnectionPatch(xyA=xy, xyB=xy2, coordsA='data', coordsB='data',
axesA=f1s3, axesB=f1s4)
xy = (3.5, -1)
xy2 = (1.5, -1)
con2 = ConnectionPatch(xyA=xy, xyB=xy2, coordsA='data', coordsB='data',
axesA=f1s3, axesB=f1s4)
f1s3.add_artist(con)
f1s3.add_artist(con2)
pyl.draw()
pyl.show()
def plot_icd_vs_mass():
galaxies = pickle.load(open('galaxies.pickle','rb'))
arrow_up = [[0,0], [-1,-1], [0,0], [0,-2], [0,0], [1,-1], [0,0]]
# Make figure
f1 = pyl.figure(1, figsize=(4,6))
f1s1 = f1.add_subplot(211)
f1s2 = f1.add_subplot(212)
for galaxy in galaxies:
if galaxy.ston_I > 30. and galaxy.ICD_IH != None:
f1s1.scatter(galaxy.z, galaxy.ICD_IH * 100, c='0.8',
marker='o', s=25, edgecolor='0.8')
if galaxy.ston_V > 30. and galaxy.ICD_VJ != None:
f1s2.scatter(galaxy.z, galaxy.ICD_VJ * 100, c='0.8',
marker='o', s=25, edgecolor='0.8')
# Add the box and whiskers
galaxies2 = filter(lambda galaxy: galaxy.ston_I > 30., galaxies)
galaxies2 = pyl.asarray(galaxies2)
x = [galaxy.z for galaxy in galaxies2]
ll = 1.5
ul= 4
bins_x =pyl.arange(ll, ul, 0.5)
grid = []
for i in range(bins_x.size-1):
xmin = bins_x[i]
xmax = bins_x[i+1]
cond=[cond1 and cond2 for cond1, cond2 in zip(x>=xmin, x<xmax)]
grid.append(galaxies2.compress(cond))
icd = []
for i in range(len(grid)):
icd.append([galaxy.ICD_IH*100 for galaxy in grid[i]])
from boxplot_percentile import percentile_box_plot as pbp
pbp(f1s1, icd, indexer=list(pyl.delete(bins_x,-1)+0.25), whisker_top=None,
whisker_bottom=None)
# Add the box and whiskers
galaxies = pickle.load(open('galaxies.pickle','rb'))
galaxies2 = filter(lambda galaxy: galaxy.ston_V > 30., galaxies)
galaxies2 = pyl.asarray(galaxies2)
x = [galaxy.z for galaxy in galaxies2]
ll = 1.5
ul= 4
bins_x =pyl.arange(ll, ul, 0.5)
grid = []
for i in range(bins_x.size-1):
xmin = bins_x[i]
xmax = bins_x[i+1]
cond=[cond1 and cond2 for cond1, cond2 in zip(x>=xmin, x<xmax)]
grid.append(galaxies2.compress(cond))
icd = []
for i in range(len(grid)):
icd.append([galaxy.ICD_VJ*100 for galaxy in grid[i]])
pbp(f1s2, icd, indexer=list(pyl.delete(bins_x,-1)+0.25), whisker_top=None,
whisker_bottom=None)
f1s1.set_xlim(1.5, 3.5)
f1s2.set_xlim(1.5, 3.5)
f1s1.set_ylim(-1, 10)
f1s2.set_ylim(-1, 10)
f1s1.set_xticklabels([])
f1s2.set_xticks([1.5,2,2.5,3,3.5])
f1s1.set_ylabel(r"$\xi[i_{775},H_{160}]$ (%)")
f1s2.set_xlabel("Redshift")
f1s2.set_ylabel(r"$\xi[V_{606},J_{125}]$ (%)")
import matplotlib.font_manager
line1 = pyl.Line2D([], [], marker='o', mfc='0.8', mec='0.8', markersize=8,
linewidth=0)
line2 = pyl.Line2D([], [], marker='s', mec='#348ABD', mfc='None',
markersize=10, linewidth=0, markeredgewidth=2)
line3 = pyl.Line2D([], [], color='#A60628', linewidth=2)
prop = matplotlib.font_manager.FontProperties(size='small')
pyl.figlegend((line1, line2, line3), ('Data', 'Quartiles',
'Medians'), 'lower center', prop=prop, ncol=3)
pyl.show()
def plot_uvj_vs_icd():
galaxies = pickle.load(open('galaxies.pickle', 'rb'))
galaxies = filter(lambda galaxy: galaxy.ICD_IH != None, galaxies)
galaxies = filter(lambda galaxy: galaxy.sersic != None and \
galaxy.ston_I > 30, galaxies)
#Upper and Lower limit arrow verts
arrowup_verts = [[0., 0.], [-1., -1], [0., 0.], [0., -2.], [0., 0.],
[1, -1]]
#arrowdown_verts = [[0.,0.], [-1., 1], [0.,0.],
# [0.,2.], [0.,0.], [1, 1]]
F = pyl.figure(1, figsize=(8, 3))
grid = AxesGrid(F,
111,
nrows_ncols=(1, 4),
axes_pad=0.1,
add_all=True,
aspect=False,
share_all=True)
ax1 = grid[0]
ax2 = grid[1]
ax3 = grid[2]
ax4 = grid[3]
for galaxy in galaxies:
if galaxy.sersic < 1.:
col1 = ax1.scatter(galaxy.Mass,
galaxy.Color_grad,
s=25,
c='0.8',
edgecolor='0.8')
if 1. < galaxy.sersic < 2.:
col2 = ax2.scatter(galaxy.Mass,
galaxy.Color_grad,
s=25,
c='0.8',
edgecolor='0.8')
if 2. < galaxy.sersic < 3.:
col3 = ax3.scatter(galaxy.Mass,
galaxy.Color_grad,
s=25,
c='0.8',
edgecolor='0.8')
if 3. < galaxy.sersic:
if galaxy.Color_grad < 50:
col4 = ax4.scatter(galaxy.Mass,
galaxy.Color_grad,
s=25,
c='0.8',
edgecolor='0.8')
else:
col4 = ax4.scatter(galaxy.Mass,
50,
marker=None,
s=100,
verts=arrowup_verts)
# Add the box and whiskers
galaxies1 = filter(lambda galaxy: galaxy.ston_I > 30. and \
galaxy.sersic < 1, galaxies)
galaxies1 = pyl.asarray(galaxies1)
galaxies2 = filter(lambda galaxy: galaxy.ston_I > 30. and \
1 < galaxy.sersic < 2, galaxies)
galaxies2 = pyl.asarray(galaxies2)
galaxies3 = filter(lambda galaxy: galaxy.ston_I > 30. and \
2 < galaxy.sersic < 3, galaxies)
galaxies3 = pyl.asarray(galaxies3)
galaxies4 = filter(lambda galaxy: galaxy.ston_I > 30. and \
3 < galaxy.sersic, galaxies)
galaxies4 = pyl.asarray(galaxies4)
x1 = [galaxy.Mass for galaxy in galaxies1]
x2 = [galaxy.Mass for galaxy in galaxies2]
x3 = [galaxy.Mass for galaxy in galaxies3]
x4 = [galaxy.Mass for galaxy in galaxies4]
ll = 8.5
ul = 12
bins_x = pyl.arange(8.5, 12.5, 0.5)
grid1 = []
grid2 = []
grid3 = []
grid4 = []
for i in range(bins_x.size - 1):
xmin = bins_x[i]
xmax = bins_x[i + 1]
cond = [cond1 and cond2 for cond1, cond2 in zip(x1 >= xmin, x1 < xmax)]
grid1.append(galaxies1.compress(cond))
cond = [cond1 and cond2 for cond1, cond2 in zip(x2 >= xmin, x2 < xmax)]
grid2.append(galaxies2.compress(cond))
cond = [cond1 and cond2 for cond1, cond2 in zip(x3 >= xmin, x3 < xmax)]
grid3.append(galaxies3.compress(cond))
cond = [cond1 and cond2 for cond1, cond2 in zip(x4 >= xmin, x4 < xmax)]
grid4.append(galaxies4.compress(cond))
icd1 = []
icd2 = []
icd3 = []
icd4 = []
for i in range(len(grid1)):
icd1.append([galaxy.Color_grad for galaxy in grid1[i]])
icd2.append([galaxy.Color_grad for galaxy in grid2[i]])
icd3.append([galaxy.Color_grad for galaxy in grid3[i]])
icd4.append([galaxy.Color_grad for galaxy in grid4[i]])
from boxplot_percentile import percentile_box_plot as pbp
bp1 = pbp(ax1, icd1, indexer=list(pyl.delete(bins_x, -1) + 0.25))
bp2 = pbp(ax2, icd2, indexer=list(pyl.delete(bins_x, -1) + 0.25))
bp3 = pbp(ax3, icd3, indexer=list(pyl.delete(bins_x, -1) + 0.25))
bp4 = pbp(ax4, icd4, indexer=list(pyl.delete(bins_x, -1) + 0.25))
ax1.set_xticks([8, 9, 10, 11])
ax2.set_xticks([8, 9, 10, 11])
ax3.set_xticks([8, 9, 10, 11])
ax4.set_xticks([8, 9, 10, 11])
# ax1.set_xlim(8, 12)
# ax2.set_xlim(8, 12)
# ax3.set_xlim(8, 12)
# ax4.set_xlim(8, 12)
# ax1.set_ylim(0, 50)
# ax2.set_ylim(0, 50)
# ax3.set_ylim(0, 50)
# ax4.set_ylim(0, 50)
ax1.set_ylabel(r'$\xi[i_{775},H_{160}]$ (%)')
ax1.set_title('n < 1')
ax2.set_title('1 < n < 2')
ax3.set_title('2 < n < 3')
ax4.set_title('3 < n')
pyl.figtext(.5,
.05,
r'Log Mass $(M_{\odot})$',
fontsize=18,
horizontalalignment='center')
ax1.axhline(0, lw=2, zorder=0)
ax2.axhline(0, lw=2, zorder=0)
ax3.axhline(0, lw=2, zorder=0)
ax4.axhline(0, lw=2, zorder=0)
import matplotlib.font_manager
line1 = pyl.Line2D([], [],
marker='o',
mfc='0.8',
mec='0.8',
markersize=8,
linewidth=0)
line2 = pyl.Line2D([], [],
marker='s',
mec='blue',
mfc='None',
markersize=10,
linewidth=0,
markeredgewidth=2)
line3 = pyl.Line2D([], [], color='r', linewidth=2)
prop = matplotlib.font_manager.FontProperties(size='small')
ax3.legend((line1, line2, line3), ('Data', 'Quartiles', 'Medians'),
'upper center',
prop=prop,
ncol=1)
pyl.tight_layout()
pyl.subplots_adjust(bottom=0.21, left=0.11)
pyl.show()
def plot_uvj_vs_icd():
galaxies = pickle.load(open("galaxies.pickle", "rb"))
galaxies = filter(lambda galaxy: galaxy.ICD_IH != None, galaxies)
galaxies = filter(lambda galaxy: galaxy.sersic != None and galaxy.ston_I > 30, galaxies)
# Upper and Lower limit arrow verts
arrowup_verts = [[0.0, 0.0], [-1.0, -1], [0.0, 0.0], [0.0, -2.0], [0.0, 0.0], [1, -1]]
# arrowdown_verts = [[0.,0.], [-1., 1], [0.,0.],
# [0.,2.], [0.,0.], [1, 1]]
F = pyl.figure(1, figsize=(8, 3))
grid = AxesGrid(F, 111, nrows_ncols=(1, 4), axes_pad=0.1, add_all=True, aspect=False, share_all=True)
ax1 = grid[0]
ax2 = grid[1]
ax3 = grid[2]
ax4 = grid[3]
for galaxy in galaxies:
if galaxy.sersic < 1.0:
col1 = ax1.scatter(galaxy.Mass, galaxy.Color_grad, s=25, c="0.8", edgecolor="0.8")
if 1.0 < galaxy.sersic < 2.0:
col2 = ax2.scatter(galaxy.Mass, galaxy.Color_grad, s=25, c="0.8", edgecolor="0.8")
if 2.0 < galaxy.sersic < 3.0:
col3 = ax3.scatter(galaxy.Mass, galaxy.Color_grad, s=25, c="0.8", edgecolor="0.8")
if 3.0 < galaxy.sersic:
if galaxy.Color_grad < 50:
col4 = ax4.scatter(galaxy.Mass, galaxy.Color_grad, s=25, c="0.8", edgecolor="0.8")
else:
col4 = ax4.scatter(galaxy.Mass, 50, marker=None, s=100, verts=arrowup_verts)
# Add the box and whiskers
galaxies1 = filter(lambda galaxy: galaxy.ston_I > 30.0 and galaxy.sersic < 1, galaxies)
galaxies1 = pyl.asarray(galaxies1)
galaxies2 = filter(lambda galaxy: galaxy.ston_I > 30.0 and 1 < galaxy.sersic < 2, galaxies)
galaxies2 = pyl.asarray(galaxies2)
galaxies3 = filter(lambda galaxy: galaxy.ston_I > 30.0 and 2 < galaxy.sersic < 3, galaxies)
galaxies3 = pyl.asarray(galaxies3)
galaxies4 = filter(lambda galaxy: galaxy.ston_I > 30.0 and 3 < galaxy.sersic, galaxies)
galaxies4 = pyl.asarray(galaxies4)
x1 = [galaxy.Mass for galaxy in galaxies1]
x2 = [galaxy.Mass for galaxy in galaxies2]
x3 = [galaxy.Mass for galaxy in galaxies3]
x4 = [galaxy.Mass for galaxy in galaxies4]
ll = 8.5
ul = 12
bins_x = pyl.arange(8.5, 12.5, 0.5)
grid1 = []
grid2 = []
grid3 = []
grid4 = []
for i in range(bins_x.size - 1):
xmin = bins_x[i]
xmax = bins_x[i + 1]
cond = [cond1 and cond2 for cond1, cond2 in zip(x1 >= xmin, x1 < xmax)]
grid1.append(galaxies1.compress(cond))
cond = [cond1 and cond2 for cond1, cond2 in zip(x2 >= xmin, x2 < xmax)]
grid2.append(galaxies2.compress(cond))
cond = [cond1 and cond2 for cond1, cond2 in zip(x3 >= xmin, x3 < xmax)]
grid3.append(galaxies3.compress(cond))
cond = [cond1 and cond2 for cond1, cond2 in zip(x4 >= xmin, x4 < xmax)]
grid4.append(galaxies4.compress(cond))
icd1 = []
icd2 = []
icd3 = []
icd4 = []
for i in range(len(grid1)):
icd1.append([galaxy.Color_grad for galaxy in grid1[i]])
icd2.append([galaxy.Color_grad for galaxy in grid2[i]])
icd3.append([galaxy.Color_grad for galaxy in grid3[i]])
icd4.append([galaxy.Color_grad for galaxy in grid4[i]])
from boxplot_percentile import percentile_box_plot as pbp
bp1 = pbp(ax1, icd1, indexer=list(pyl.delete(bins_x, -1) + 0.25))
bp2 = pbp(ax2, icd2, indexer=list(pyl.delete(bins_x, -1) + 0.25))
bp3 = pbp(ax3, icd3, indexer=list(pyl.delete(bins_x, -1) + 0.25))
bp4 = pbp(ax4, icd4, indexer=list(pyl.delete(bins_x, -1) + 0.25))
ax1.set_xticks([8, 9, 10, 11])
ax2.set_xticks([8, 9, 10, 11])
ax3.set_xticks([8, 9, 10, 11])
ax4.set_xticks([8, 9, 10, 11])
# ax1.set_xlim(8, 12)
# ax2.set_xlim(8, 12)
# ax3.set_xlim(8, 12)
# ax4.set_xlim(8, 12)
# ax1.set_ylim(0, 50)
# ax2.set_ylim(0, 50)
# ax3.set_ylim(0, 50)
# ax4.set_ylim(0, 50)
ax1.set_ylabel(r"$\xi[i_{775},H_{160}]$ (%)")
ax1.set_title("n < 1")
ax2.set_title("1 < n < 2")
ax3.set_title("2 < n < 3")
ax4.set_title("3 < n")
pyl.figtext(0.5, 0.05, r"Log Mass $(M_{\odot})$", fontsize=18, horizontalalignment="center")
ax1.axhline(0, lw=2, zorder=0)
ax2.axhline(0, lw=2, zorder=0)
ax3.axhline(0, lw=2, zorder=0)
ax4.axhline(0, lw=2, zorder=0)
import matplotlib.font_manager
line1 = pyl.Line2D([], [], marker="o", mfc="0.8", mec="0.8", markersize=8, linewidth=0)
line2 = pyl.Line2D([], [], marker="s", mec="blue", mfc="None", markersize=10, linewidth=0, markeredgewidth=2)
line3 = pyl.Line2D([], [], color="r", linewidth=2)
prop = matplotlib.font_manager.FontProperties(size="small")
ax3.legend((line1, line2, line3), ("Data", "Quartiles", "Medians"), "upper center", prop=prop, ncol=1)
pyl.tight_layout()
pyl.subplots_adjust(bottom=0.21, left=0.11)
pyl.show()
ll = 1.5
ul = 4
bins_x = pyl.arange(ll, ul, 0.5)
grid = []
for i in range(bins_x.size - 1):
xmin = bins_x[i]
xmax = bins_x[i + 1]
cond = [cond1 and cond2 for cond1, cond2 in zip(x >= xmin, x < xmax)]
grid.append(galaxies2.compress(cond))
icd = []
for i in range(len(grid)):
icd.append([galaxy.ICD_IH * 100 for galaxy in grid[i]])
from boxplot_percentile import percentile_box_plot as pbp
pbp(f1s1, icd, indexer=list(pyl.delete(bins_x, -1) + 0.25))
pbp(f1s2, icd, indexer=list(pyl.delete(bins_x, -1) + 0.25))
# Add the box and whiskers
galaxies = pickle.load(open('galaxies.pickle', 'rb'))
galaxies2 = filter(lambda galaxy: galaxy.ston_V > 30., galaxies)
galaxies2 = pyl.asarray(galaxies2)
x = [galaxy.z for galaxy in galaxies2]
ll = 1.5
ul = 4
bins_x = pyl.arange(ll, ul, 0.5)
grid = []
for i in range(bins_x.size - 1):
xmin = bins_x[i]
xmax = bins_x[i + 1]
ll = 1.5
ul= 4
bins_x =pyl.arange(ll, ul, 0.5)
grid = []
for i in range(bins_x.size-1):
xmin = bins_x[i]
xmax = bins_x[i+1]
cond=[cond1 and cond2 for cond1, cond2 in zip(x>=xmin, x<xmax)]
grid.append(galaxies2.compress(cond))
icd = []
for i in range(len(grid)):
icd.append([galaxy.ICD_IH*100 for galaxy in grid[i]])
from boxplot_percentile import percentile_box_plot as pbp
pbp(f1s1, icd, indexer=list(pyl.delete(bins_x,-1)+0.25))
pbp(f1s2, icd, indexer=list(pyl.delete(bins_x,-1)+0.25))
# Add the box and whiskers
galaxies = pickle.load(open('galaxies.pickle','rb'))
galaxies2 = filter(lambda galaxy: galaxy.ston_V > 30., galaxies)
galaxies2 = pyl.asarray(galaxies2)
x = [galaxy.z for galaxy in galaxies2]
ll = 1.5
ul= 4
bins_x =pyl.arange(ll, ul, 0.5)
grid = []
for i in range(bins_x.size-1):
xmin = bins_x[i]
xmax = bins_x[i+1]
