def plotAll(self,
timer,
coreCut,
transform=True,
ignoreContigLengths=False):
"""Plot all contigs over a certain length which are unbinned"""
self.loadData(timer, "((length >= " + str(coreCut) + "))")
if transform:
self.transformCP(timer)
else:
if self.numStoits == 3:
self.transformedCP = self.covProfiles
else:
print("Number of stoits != 3. You need to transform")
self.transformCP(timer)
fig = plt.figure()
ax1 = fig.add_subplot(111, projection='3d')
if ignoreContigLengths:
sc = ax1.scatter(self.transformedCP[:, 0],
self.transformedCP[:, 1],
self.transformedCP[:, 2],
edgecolors='none',
c=self.contigGCs,
cmap=self.colorMapGC,
vmin=0.0,
vmax=1.0,
marker='.',
s=10.)
else:
sc = ax1.scatter(self.transformedCP[:, 0],
self.transformedCP[:, 1],
self.transformedCP[:, 2],
edgecolors='k',
c=self.contigGCs,
cmap=self.colorMapGC,
vmin=0.0,
vmax=1.0,
marker='.',
s=np_sqrt(self.contigLengths))
sc.set_edgecolors = sc.set_facecolors = lambda *args: None # disable depth transparency effect
self.plotStoitNames(ax1)
cbar = plt.colorbar(sc, shrink=0.5)
cbar.ax.tick_params()
cbar.ax.set_title("% GC", size=10)
cbar.set_ticks([0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8])
#import IPython; IPython.embed()
cbar.ax.set_ylim([0.15, 0.85])
mungeCbar(cbar)
try:
plt.show()
plt.close(fig)
except:
print("Error showing image", exc_info()[0])
raise
del fig
def plotAll(self, timer, coreCut, transform=True, ignoreContigLengths=False):
"""Plot all contigs over a certain length which are unbinned"""
self.loadData(timer, "((length >= "+str(coreCut)+"))")
if transform:
self.transformCP(timer)
else:
if self.numStoits == 3:
self.transformedCP = self.covProfiles
else:
print "Number of stoits != 3. You need to transform"
self.transformCP(timer)
fig = plt.figure()
ax1 = fig.add_subplot(111, projection='3d')
if ignoreContigLengths:
sc = ax1.scatter(self.transformedCP[:,0],
self.transformedCP[:,1],
self.transformedCP[:,2],
edgecolors='none',
c=self.contigGCs,
cmap=self.colorMapGC,
vmin=0.0,
vmax=1.0,
marker='.',
s=10.
)
else:
sc = ax1.scatter(self.transformedCP[:,0],
self.transformedCP[:,1],
self.transformedCP[:,2],
edgecolors='k',
c=self.contigGCs,
cmap=self.colorMapGC,
vmin=0.0,
vmax=1.0,
marker='.',
s=np_sqrt(self.contigLengths)
)
sc.set_edgecolors = sc.set_facecolors = lambda *args:None # disable depth transparency effect
self.plotStoitNames(ax1)
cbar = plt.colorbar(sc, shrink=0.5)
cbar.ax.tick_params()
cbar.ax.set_title("% GC", size=10)
cbar.set_ticks([0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8])
#import IPython; IPython.embed()
cbar.ax.set_ylim([0.15, 0.85])
mungeCbar(cbar)
try:
plt.show()
plt.close(fig)
except:
print "Error showing image", exc_info()[0]
raise
del fig
def renderTransCPData(self,
fileName="",
show=True,
elev=45,
azim=45,
all=False,
showAxis=False,
primaryWidth=12,
primarySpace=3,
dpi=300,
format='png',
fig=None,
highlight=None,
restrictedBids=[],
alpha=1,
ignoreContigLengths=False):
"""Plot transformed data in 3D"""
del_fig = False
if (fig is None):
fig = plt.figure()
del_fig = True
else:
plt.clf()
if (all):
myAXINFO = {
'x': {
'i': 0,
'tickdir': 1,
'juggled': (1, 0, 2),
'color': (0, 0, 0, 0, 0)
},
'y': {
'i': 1,
'tickdir': 0,
'juggled': (0, 1, 2),
'color': (0, 0, 0, 0, 0)
},
'z': {
'i': 2,
'tickdir': 0,
'juggled': (0, 2, 1),
'color': (0, 0, 0, 0, 0)
},
}
ax = fig.add_subplot(131, projection='3d')
sc = ax.scatter(self.transformedCP[:, 0],
self.transformedCP[:, 1],
self.transformedCP[:, 2],
edgecolors='k',
c=self.contigGCs,
cmap=self.colorMapGC,
vmin=0.0,
vmax=1.0,
marker='.')
sc.set_edgecolors = sc.set_facecolors = lambda *args: None # disable depth transparency effect
ax.azim = 0
ax.elev = 0
ax.set_xlim3d(0, self.scaleFactor)
ax.set_ylim3d(0, self.scaleFactor)
ax.set_zlim3d(0, self.scaleFactor)
ax.set_xticklabels([])
ax.set_yticklabels([])
ax.set_zticklabels([])
ax.set_xticks([])
ax.set_yticks([])
ax.set_zticks([])
for axis in ax.w_xaxis, ax.w_yaxis, ax.w_zaxis:
for elt in axis.get_ticklines() + axis.get_ticklabels():
elt.set_visible(False)
ax.w_xaxis._AXINFO = myAXINFO
ax.w_yaxis._AXINFO = myAXINFO
ax.w_zaxis._AXINFO = myAXINFO
ax = fig.add_subplot(132, projection='3d')
sc = ax.scatter(self.transformedCP[:, 0],
self.transformedCP[:, 1],
self.transformedCP[:, 2],
edgecolors='k',
c=self.contigGCs,
cmap=self.colorMapGC,
vmin=0.0,
vmax=1.0,
marker='.')
sc.set_edgecolors = sc.set_facecolors = lambda *args: None # disable depth transparency effect
ax.azim = 90
ax.elev = 0
ax.set_xlim3d(0, self.scaleFactor)
ax.set_ylim3d(0, self.scaleFactor)
ax.set_zlim3d(0, self.scaleFactor)
ax.set_xticklabels([])
ax.set_yticklabels([])
ax.set_zticklabels([])
ax.set_xticks([])
ax.set_yticks([])
ax.set_zticks([])
for axis in ax.w_xaxis, ax.w_yaxis, ax.w_zaxis:
for elt in axis.get_ticklines() + axis.get_ticklabels():
elt.set_visible(False)
ax.w_xaxis._AXINFO = myAXINFO
ax.w_yaxis._AXINFO = myAXINFO
ax.w_zaxis._AXINFO = myAXINFO
ax = fig.add_subplot(133, projection='3d')
sc = ax.scatter(self.transformedCP[:, 0],
self.transformedCP[:, 1],
self.transformedCP[:, 2],
edgecolors='k',
c=self.contigGCs,
cmap=self.colorMapGC,
vmin=0.0,
vmax=1.0,
marker='.')
sc.set_edgecolors = sc.set_facecolors = lambda *args: None # disable depth transparency effect
ax.azim = 0
ax.elev = 90
ax.set_xlim3d(0, self.scaleFactor)
ax.set_ylim3d(0, self.scaleFactor)
ax.set_zlim3d(0, self.scaleFactor)
ax.set_xticklabels([])
ax.set_yticklabels([])
ax.set_zticklabels([])
ax.set_xticks([])
ax.set_yticks([])
ax.set_zticks([])
for axis in ax.w_xaxis, ax.w_yaxis, ax.w_zaxis:
for elt in axis.get_ticklines() + axis.get_ticklabels():
elt.set_visible(False)
ax.w_xaxis._AXINFO = myAXINFO
ax.w_yaxis._AXINFO = myAXINFO
ax.w_zaxis._AXINFO = myAXINFO
else:
ax = fig.add_subplot(111, projection='3d')
if len(restrictedBids) == 0:
if highlight is None:
print("BF:", np_shape(self.transformedCP))
if ignoreContigLengths:
sc = ax.scatter(self.transformedCP[:, 0],
self.transformedCP[:, 1],
self.transformedCP[:, 2],
edgecolors='none',
c=self.contigGCs,
cmap=self.colorMapGC,
s=10.,
vmin=0.0,
vmax=1.0,
marker='.')
else:
sc = ax.scatter(self.transformedCP[:, 0],
self.transformedCP[:, 1],
self.transformedCP[:, 2],
edgecolors='none',
c=self.contigGCs,
cmap=self.colorMapGC,
vmin=0.0,
vmax=1.0,
s=np_sqrt(self.contigLengths),
marker='.')
sc.set_edgecolors = sc.set_facecolors = lambda *args: None # disable depth transparency effect
else:
#draw the opaque guys first
"""
sc = ax.scatter(self.transformedCP[:,0],
self.transformedCP[:,1],
self.transformedCP[:,2],
edgecolors='none',
c=self.contigGCs,
cmap=self.colorMapGC,
vmin=0.0,
vmax=1.0,
s=100.,
marker='s',
alpha=alpha)
sc.set_edgecolors = sc.set_facecolors = lambda *args:None # disable depth transparency effect
"""
# now replot the highlighted guys
disp_vals = np_array([])
disp_GCs = np_array([])
thrower = {}
hide_vals = np_array([])
hide_GCs = np_array([])
num_points = 0
for bin in highlight:
for row_index in bin.rowIndices:
num_points += 1
disp_vals = np_append(
disp_vals, self.transformedCP[row_index])
disp_GCs = np_append(disp_GCs,
self.contigGCs[row_index])
thrower[row_index] = False
# reshape
disp_vals = np_reshape(disp_vals, (num_points, 3))
num_points = 0
for i in range(len(self.indices)):
try:
thrower[i]
except KeyError:
num_points += 1
hide_vals = np_append(hide_vals,
self.transformedCP[i])
hide_GCs = np_append(hide_GCs, self.contigGCs[i])
# reshape
hide_vals = np_reshape(hide_vals, (num_points, 3))
sc = ax.scatter(hide_vals[:, 0],
hide_vals[:, 1],
hide_vals[:, 2],
edgecolors='none',
c=hide_GCs,
cmap=self.colorMapGC,
vmin=0.0,
vmax=1.0,
s=100.,
marker='s',
alpha=alpha)
sc.set_edgecolors = sc.set_facecolors = lambda *args: None # disable depth transparency effect
sc = ax.scatter(disp_vals[:, 0],
disp_vals[:, 1],
disp_vals[:, 2],
edgecolors='none',
c=disp_GCs,
cmap=self.colorMapGC,
vmin=0.0,
vmax=1.0,
s=10.,
marker='.')
sc.set_edgecolors = sc.set_facecolors = lambda *args: None # disable depth transparency effect
print(np_shape(disp_vals), np_shape(hide_vals),
np_shape(self.transformedCP))
# render color bar
cbar = plt.colorbar(sc, shrink=0.5)
cbar.ax.tick_params()
cbar.ax.set_title("% GC", size=10)
cbar.set_ticks([0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8])
cbar.ax.set_ylim([0.15, 0.85])
mungeCbar(cbar)
else:
r_trans = np_array([])
r_cols = np_array([])
num_added = 0
for i in range(len(self.indices)):
if self.binIds[i] not in restrictedBids:
r_trans = np_append(r_trans, self.transformedCP[i])
r_cols = np_append(r_cols, self.contigGCs[i])
num_added += 1
r_trans = np_reshape(r_trans, (num_added, 3))
print(np_shape(r_trans))
#r_cols = np_reshape(r_cols, (num_added,3))
sc = ax.scatter(r_trans[:, 0],
r_trans[:, 1],
r_trans[:, 2],
edgecolors='none',
c=r_cols,
cmap=self.colorMapGC,
s=10.,
vmin=0.0,
vmax=1.0,
marker='.')
sc.set_edgecolors = sc.set_facecolors = lambda *args: None # disable depth transparency effect
# render color bar
cbar = plt.colorbar(sc, shrink=0.5)
cbar.ax.tick_params()
cbar.ax.set_title("% GC", size=10)
cbar.set_ticks([0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8])
cbar.ax.set_ylim([0.15, 0.85])
mungeCbar(cbar)
ax.azim = azim
ax.elev = elev
ax.set_xlim3d(0, self.scaleFactor)
ax.set_ylim3d(0, self.scaleFactor)
ax.set_zlim3d(0, self.scaleFactor)
ax.set_xticklabels([])
ax.set_yticklabels([])
ax.set_zticklabels([])
ax.set_xticks([])
ax.set_yticks([])
ax.set_zticks([])
if (not showAxis):
ax.set_axis_off()
if (fileName != ""):
try:
if (all):
fig.set_size_inches(3 * primaryWidth + 2 * primarySpace,
primaryWidth)
else:
fig.set_size_inches(primaryWidth, primaryWidth)
plt.savefig(fileName, dpi=dpi, format=format)
except:
print("Error saving image", fileName, exc_info()[0])
raise
elif (show):
try:
plt.show()
except:
print("Error showing image", exc_info()[0])
raise
if del_fig:
plt.close(fig)
del fig
def r2nderTransCPData(
self,
fig,
alphaIndices=[],
visibleIndices=[],
alpha=1,
ignoreContigLengths=False,
elev=45,
azim=45,
fileName="",
dpi=300,
format='png',
primaryWidth=6,
title="",
showAxis=False,
showColorbar=True,
):
"""Plot transformed data in 3D"""
# clear any existing plot
plt.clf()
ax = fig.add_subplot(111, projection='3d')
# work out the coords an colours based on indices
alpha_coords = self.transformedCP[alphaIndices]
alpha_GCs = self.contigGCs[alphaIndices]
visible_coords = self.transformedCP[visibleIndices]
visible_GCs = self.contigGCs[visibleIndices]
# lengths if needed
if not ignoreContigLengths:
alpha_lengths = self.contigLengths[alphaIndices]
visible_lengths = self.contigLengths[visibleIndices]
else:
alpha_lengths = 10.
visible_lengths = 10.
# first plot alpha points
if len(alpha_GCs) > 0:
sc = ax.scatter(alpha_coords[:, 0],
alpha_coords[:, 1],
alpha_coords[:, 2],
edgecolors='none',
c=alpha_GCs,
cmap=self.colorMapGC,
vmin=0.0,
vmax=1.0,
s=alpha_lengths,
marker='.',
alpha=alpha)
sc.set_edgecolors = sc.set_facecolors = lambda *args: None # disable depth transparency effect
# then plot full visible points
if len(visible_GCs) > 0:
sc = ax.scatter(visible_coords[:, 0],
visible_coords[:, 1],
visible_coords[:, 2],
edgecolors='none',
c=visible_GCs,
cmap=self.colorMapGC,
s=visible_lengths,
vmin=0.0,
vmax=1.0,
marker='.')
sc.set_edgecolors = sc.set_facecolors = lambda *args: None # disable depth transparency effect
# render color bar
if showColorbar:
cbar = plt.colorbar(sc, shrink=0.5)
cbar.ax.tick_params()
cbar.ax.set_title("% GC", size=10)
cbar.set_ticks([0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8])
cbar.ax.set_ylim([0.15, 0.85])
mungeCbar(cbar)
# set aspect
ax.azim = azim
ax.elev = elev
# make it purdy
ax.set_xlim3d(0, self.scaleFactor)
ax.set_ylim3d(0, self.scaleFactor)
ax.set_zlim3d(0, self.scaleFactor)
ax.set_xticklabels([])
ax.set_yticklabels([])
ax.set_zticklabels([])
ax.set_xticks([])
ax.set_yticks([])
ax.set_zticks([])
plt.tight_layout()
if title != "":
plt.title(title)
if (not showAxis):
ax.set_axis_off()
if (fileName != ""):
try:
fig.set_size_inches(primaryWidth, primaryWidth)
plt.savefig(fileName, dpi=dpi, format=format)
except:
print("Error saving image", fileName, exc_info()[0])
raise
else:
try:
plt.show()
except:
print("Error showing image", exc_info()[0])
raise
def r2nderTransCPData(self,
fig,
alphaIndices=[],
visibleIndices=[],
alpha=1,
ignoreContigLengths=False,
elev=45,
azim=45,
fileName="",
dpi=300,
format='png',
primaryWidth=6,
title="",
showAxis=False,
showColorbar=True,):
"""Plot transformed data in 3D"""
# clear any existing plot
plt.clf()
ax = fig.add_subplot(111, projection='3d')
# work out the coords an colours based on indices
alpha_coords = self.transformedCP[alphaIndices]
alpha_GCs = self.contigGCs[alphaIndices]
visible_coords = self.transformedCP[visibleIndices]
visible_GCs = self.contigGCs[visibleIndices]
# lengths if needed
if not ignoreContigLengths:
alpha_lengths = self.contigLengths[alphaIndices]
visible_lengths = self.contigLengths[visibleIndices]
else:
alpha_lengths = 10.
visible_lengths = 10.
# first plot alpha points
if len(alpha_GCs) > 0:
sc = ax.scatter(alpha_coords[:,0],
alpha_coords[:,1],
alpha_coords[:,2],
edgecolors='none',
c=alpha_GCs,
cmap=self.colorMapGC,
vmin=0.0,
vmax=1.0,
s=alpha_lengths,
marker='.',
alpha=alpha)
sc.set_edgecolors = sc.set_facecolors = lambda *args:None # disable depth transparency effect
# then plot full visible points
if len(visible_GCs) > 0:
sc = ax.scatter(visible_coords[:,0],
visible_coords[:,1],
visible_coords[:,2],
edgecolors='none',
c=visible_GCs,
cmap=self.colorMapGC,
s=visible_lengths,
vmin=0.0,
vmax=1.0,
marker='.')
sc.set_edgecolors = sc.set_facecolors = lambda *args:None # disable depth transparency effect
# render color bar
if showColorbar:
cbar = plt.colorbar(sc, shrink=0.5)
cbar.ax.tick_params()
cbar.ax.set_title("% GC", size=10)
cbar.set_ticks([0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8])
cbar.ax.set_ylim([0.15, 0.85])
mungeCbar(cbar)
# set aspect
ax.azim = azim
ax.elev = elev
# make it purdy
ax.set_xlim3d(0,self.scaleFactor)
ax.set_ylim3d(0,self.scaleFactor)
ax.set_zlim3d(0,self.scaleFactor)
ax.set_xticklabels([])
ax.set_yticklabels([])
ax.set_zticklabels([])
ax.set_xticks([])
ax.set_yticks([])
ax.set_zticks([])
plt.tight_layout()
if title != "":
plt.title(title)
if(not showAxis):
ax.set_axis_off()
if(fileName != ""):
try:
fig.set_size_inches(primaryWidth,primaryWidth)
plt.savefig(fileName,dpi=dpi,format=format)
except:
print "Error saving image",fileName, exc_info()[0]
raise
else:
try:
plt.show()
except:
print "Error showing image", exc_info()[0]
raise
def renderTransCPData(self,
fileName="",
show=True,
elev=45,
azim=45,
all=False,
showAxis=False,
primaryWidth=12,
primarySpace=3,
dpi=300,
format='png',
fig=None,
highlight=None,
restrictedBids=[],
alpha=1,
ignoreContigLengths=False):
"""Plot transformed data in 3D"""
del_fig = False
if(fig is None):
fig = plt.figure()
del_fig = True
else:
plt.clf()
if(all):
myAXINFO = {
'x': {'i': 0, 'tickdir': 1, 'juggled': (1, 0, 2),
'color': (0, 0, 0, 0, 0)},
'y': {'i': 1, 'tickdir': 0, 'juggled': (0, 1, 2),
'color': (0, 0, 0, 0, 0)},
'z': {'i': 2, 'tickdir': 0, 'juggled': (0, 2, 1),
'color': (0, 0, 0, 0, 0)},
}
ax = fig.add_subplot(131, projection='3d')
sc = ax.scatter(self.transformedCP[:,0], self.transformedCP[:,1], self.transformedCP[:,2], edgecolors='k', c=self.contigGCs, cmap=self.colorMapGC, vmin=0.0, vmax=1.0, marker='.')
sc.set_edgecolors = sc.set_facecolors = lambda *args:None # disable depth transparency effect
ax.azim = 0
ax.elev = 0
ax.set_xlim3d(0,self.scaleFactor)
ax.set_ylim3d(0,self.scaleFactor)
ax.set_zlim3d(0,self.scaleFactor)
ax.set_xticklabels([])
ax.set_yticklabels([])
ax.set_zticklabels([])
ax.set_xticks([])
ax.set_yticks([])
ax.set_zticks([])
for axis in ax.w_xaxis, ax.w_yaxis, ax.w_zaxis:
for elt in axis.get_ticklines() + axis.get_ticklabels():
elt.set_visible(False)
ax.w_xaxis._AXINFO = myAXINFO
ax.w_yaxis._AXINFO = myAXINFO
ax.w_zaxis._AXINFO = myAXINFO
ax = fig.add_subplot(132, projection='3d')
sc = ax.scatter(self.transformedCP[:,0], self.transformedCP[:,1], self.transformedCP[:,2], edgecolors='k', c=self.contigGCs, cmap=self.colorMapGC, vmin=0.0, vmax=1.0, marker='.')
sc.set_edgecolors = sc.set_facecolors = lambda *args:None # disable depth transparency effect
ax.azim = 90
ax.elev = 0
ax.set_xlim3d(0,self.scaleFactor)
ax.set_ylim3d(0,self.scaleFactor)
ax.set_zlim3d(0,self.scaleFactor)
ax.set_xticklabels([])
ax.set_yticklabels([])
ax.set_zticklabels([])
ax.set_xticks([])
ax.set_yticks([])
ax.set_zticks([])
for axis in ax.w_xaxis, ax.w_yaxis, ax.w_zaxis:
for elt in axis.get_ticklines() + axis.get_ticklabels():
elt.set_visible(False)
ax.w_xaxis._AXINFO = myAXINFO
ax.w_yaxis._AXINFO = myAXINFO
ax.w_zaxis._AXINFO = myAXINFO
ax = fig.add_subplot(133, projection='3d')
sc = ax.scatter(self.transformedCP[:,0], self.transformedCP[:,1], self.transformedCP[:,2], edgecolors='k', c=self.contigGCs, cmap=self.colorMapGC, vmin=0.0, vmax=1.0, marker='.')
sc.set_edgecolors = sc.set_facecolors = lambda *args:None # disable depth transparency effect
ax.azim = 0
ax.elev = 90
ax.set_xlim3d(0,self.scaleFactor)
ax.set_ylim3d(0,self.scaleFactor)
ax.set_zlim3d(0,self.scaleFactor)
ax.set_xticklabels([])
ax.set_yticklabels([])
ax.set_zticklabels([])
ax.set_xticks([])
ax.set_yticks([])
ax.set_zticks([])
for axis in ax.w_xaxis, ax.w_yaxis, ax.w_zaxis:
for elt in axis.get_ticklines() + axis.get_ticklabels():
elt.set_visible(False)
ax.w_xaxis._AXINFO = myAXINFO
ax.w_yaxis._AXINFO = myAXINFO
ax.w_zaxis._AXINFO = myAXINFO
else:
ax = fig.add_subplot(111, projection='3d')
if len(restrictedBids) == 0:
if highlight is None:
print "BF:", np_shape(self.transformedCP)
if ignoreContigLengths:
sc = ax.scatter(self.transformedCP[:,0],
self.transformedCP[:,1],
self.transformedCP[:,2],
edgecolors='none',
c=self.contigGCs,
cmap=self.colorMapGC,
s=10.,
vmin=0.0,
vmax=1.0,
marker='.')
else:
sc = ax.scatter(self.transformedCP[:,0],
self.transformedCP[:,1],
self.transformedCP[:,2],
edgecolors='none',
c=self.contigGCs,
cmap=self.colorMapGC,
vmin=0.0,
vmax=1.0,
s=np_sqrt(self.contigLengths),
marker='.')
sc.set_edgecolors = sc.set_facecolors = lambda *args:None # disable depth transparency effect
else:
#draw the opaque guys first
"""
sc = ax.scatter(self.transformedCP[:,0],
self.transformedCP[:,1],
self.transformedCP[:,2],
edgecolors='none',
c=self.contigGCs,
cmap=self.colorMapGC,
vmin=0.0,
vmax=1.0,
s=100.,
marker='s',
alpha=alpha)
sc.set_edgecolors = sc.set_facecolors = lambda *args:None # disable depth transparency effect
"""
# now replot the highlighted guys
disp_vals = np_array([])
disp_GCs = np_array([])
thrower = {}
hide_vals = np_array([])
hide_GCs = np_array([])
num_points = 0
for bin in highlight:
for row_index in bin.rowIndices:
num_points += 1
disp_vals = np_append(disp_vals, self.transformedCP[row_index])
disp_GCs = np_append(disp_GCs, self.contigGCs[row_index])
thrower[row_index] = False
# reshape
disp_vals = np_reshape(disp_vals, (num_points, 3))
num_points = 0
for i in range(len(self.indices)):
try:
thrower[i]
except KeyError:
num_points += 1
hide_vals = np_append(hide_vals, self.transformedCP[i])
hide_GCs = np_append(hide_GCs, self.contigGCs[i])
# reshape
hide_vals = np_reshape(hide_vals, (num_points, 3))
sc = ax.scatter(hide_vals[:,0],
hide_vals[:,1],
hide_vals[:,2],
edgecolors='none',
c=hide_GCs,
cmap=self.colorMapGC,
vmin=0.0,
vmax=1.0,
s=100.,
marker='s',
alpha=alpha)
sc.set_edgecolors = sc.set_facecolors = lambda *args:None # disable depth transparency effect
sc = ax.scatter(disp_vals[:,0],
disp_vals[:,1],
disp_vals[:,2],
edgecolors='none',
c=disp_GCs,
cmap=self.colorMapGC,
vmin=0.0,
vmax=1.0,
s=10.,
marker='.')
sc.set_edgecolors = sc.set_facecolors = lambda *args:None # disable depth transparency effect
print np_shape(disp_vals), np_shape(hide_vals), np_shape(self.transformedCP)
# render color bar
cbar = plt.colorbar(sc, shrink=0.5)
cbar.ax.tick_params()
cbar.ax.set_title("% GC", size=10)
cbar.set_ticks([0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8])
cbar.ax.set_ylim([0.15, 0.85])
mungeCbar(cbar)
else:
r_trans = np_array([])
r_cols=np_array([])
num_added = 0
for i in range(len(self.indices)):
if self.binIds[i] not in restrictedBids:
r_trans = np_append(r_trans, self.transformedCP[i])
r_cols = np_append(r_cols, self.contigGCs[i])
num_added += 1
r_trans = np_reshape(r_trans, (num_added,3))
print np_shape(r_trans)
#r_cols = np_reshape(r_cols, (num_added,3))
sc = ax.scatter(r_trans[:,0],
r_trans[:,1],
r_trans[:,2],
edgecolors='none',
c=r_cols,
cmap=self.colorMapGC,
s=10.,
vmin=0.0,
vmax=1.0,
marker='.')
sc.set_edgecolors = sc.set_facecolors = lambda *args:None # disable depth transparency effect
# render color bar
cbar = plt.colorbar(sc, shrink=0.5)
cbar.ax.tick_params()
cbar.ax.set_title("% GC", size=10)
cbar.set_ticks([0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8])
cbar.ax.set_ylim([0.15, 0.85])
mungeCbar(cbar)
ax.azim = azim
ax.elev = elev
ax.set_xlim3d(0,self.scaleFactor)
ax.set_ylim3d(0,self.scaleFactor)
ax.set_zlim3d(0,self.scaleFactor)
ax.set_xticklabels([])
ax.set_yticklabels([])
ax.set_zticklabels([])
ax.set_xticks([])
ax.set_yticks([])
ax.set_zticks([])
if(not showAxis):
ax.set_axis_off()
if(fileName != ""):
try:
if(all):
fig.set_size_inches(3*primaryWidth+2*primarySpace,primaryWidth)
else:
fig.set_size_inches(primaryWidth,primaryWidth)
plt.savefig(fileName,dpi=dpi,format=format)
except:
print "Error saving image",fileName, exc_info()[0]
raise
elif(show):
try:
plt.show()
except:
print "Error showing image", exc_info()[0]
raise
if del_fig:
plt.close(fig)
del fig
