def draw():
X = simulate.runOne(SHOW=False,we=1.0,wl=0., wr=0., foot_print=4,s=5, l=5)
F = plt.figure( )
ax1 = F.add_subplot(2,2,1)
ax2 = F.add_subplot(2,2,2)
ax3 = F.add_subplot(2,2,3)
ax4 = F.add_subplot(2,2,4)
ax_c= F.add_axes([0.35,0.52,0.35,0.02])
ax_c.set_xticks([])
ax_c.set_yticks([])
cmap = mpl.cm.jet
norm = mpl.colors.Normalize(vmin=-1000, vmax=0)
# ColorbarBase derives from ScalarMappable and puts a colorbar
# in a specified axes, so it has everything needed for a
# standalone colorbar. There are many more kwargs, but the
# following gives a basic continuous colorbar with ticks
# and labels.
cb1 = mpl.colorbar.ColorbarBase(ax_c, cmap=cmap,
norm=norm,
orientation='horizontal')
ax_c.set_xticklabels([r"$-10^{30}$"]+ [" "," "," "," ",r"$-10^{15}$"," "," "," "," " ]+ [r'$-10^3$'] , rotation=15 )
ax_c.set_title("log-likelihood")
res = 3
mu_by_lambda(ax1, X,res)
mu_by_pi(ax2,X,res)
sigma_by_lambda(ax3,X,res)
fp_by_sigma(ax4,X,res)
plt.tight_layout()
plt.show()
def run(FILE):
FHW = open(FILE, "w")
X = load.grab_specific_region("chr1",6229860,6303055, SHOW=False, bins=1000 )
print min(X[:,0]), max(X[:,0])
FHW.write("#chr1,6229860,6303055\n")
FHW.write("~forward\n")
for i in range(X.shape[0]):
FHW.write(str(X[i,0]) + "," + str(X[i,1]) + "\n")
FHW.write("~reverse\n")
for i in range(X.shape[0]):
FHW.write(str(X[i,0]) + "," + str(X[i,2]) + "\n")
X = simulate.runOne(mu=0, s=0.1, l=3, lr=100, ll=-50, we=0.5,wl=0.25, wr=0.25, pie=0.5, pil=0.1, pir=0.9,
N=1000, SHOW=False, bins=1000, noise=True )
X[:,0]+=6303055
X[:,0]*=100.
st, sp = X[0,0], X[-1,0]
print st, sp
FHW.write("#chrN,"+str(st) + "," + str(sp) + "\n")
FHW.write("~forward\n")
for i in range(X.shape[0]):
FHW.write(str(X[i,0]) + "," + str(X[i,1]) + "\n")
FHW.write("~reverse\n")
for i in range(X.shape[0]):
FHW.write(str(X[i,0]) + "," + str(X[i,2]) + "\n")
FHW.close()
def draw_posterior(ax,ax_cbar):
X1 = sim.runOne(mu=-40, s=1, l=10, lr=40, ll=-200, we=0.5,wl=0.25, wr=0.25, pie=0.5, pil=0.1,
pir=0.9, N=3000, SHOW=False , bins=200, noise=False, foot_print = 1 )
X2 = sim.runOne(mu=40, s=1, l=10, lr=200, ll=-40, we=0.5,wl=0.25, wr=0.25, pie=0.5, pil=0.1,
pir=0.9, N=3000, SHOW=False , bins=200, noise=False, foot_print = 1 )
rvs = [model.component_bidir( -40, 1, 0.1, 0.5,0.5 , None,foot_print=1 )]
rvs +=[model.component_elongation( -40, 200, 0.25,1.0 ,None , None, None, None)]
rvs +=[model.component_elongation( -200, -40, 0.25,0 , None , None, None, None )]
rvs += [model.component_bidir( 40, 1, 0.1, 0.5,0.5 , None,foot_print=1 )]
rvs +=[model.component_elongation( 40, 200, 0.25,1.0 ,None , None, None, None)]
rvs +=[model.component_elongation( -200, 40, 0.25,0 , None , None, None, None )]
norm = mpl.colors.Normalize(vmin=0, vmax= 1)
cmap = plt.get_cmap('PuOr' )
m = cm.ScalarMappable(norm=norm, cmap=cmap)
cb1 = mpl.colorbar.ColorbarBase(ax_cbar, cmap=cmap,
norm=norm,
orientation='vertical')
cb1.set_label(r'$p(k=paused|\hat{\theta})$')
ax_cbar.yaxis.tick_right()
ax_cbar.set_yticklabels(["0", "", "", "","", "0.5", "","", "", "", "1"] )
ax2 = ax_cbar.twinx()
ax2.set_yticks([])
ax2.yaxis.set_label_position("left")
KS = (0,3)
MIN, MAX = 0,0
for i,X in enumerate((X1, X2)) :
w = (X[-1,0] - X[0,0]) / X.shape[0]
xs = np.linspace(X[0,0],X[-1,0], X.shape[0] )
MAX = max(MAX, max(X[:,1]))
MIN = min(MIN, min(-X[:,2]))
colorsf = [ m.to_rgba(posterior(x,rvs, Type=KS[i] )) for x in xs ]
ax.bar(X[:,0], X[:,1], width=w, color=colorsf, edgecolor=colorsf,alpha=0.3)
ax.bar(X[:,0], -X[:,2], width=w, color=colorsf, edgecolor=colorsf,alpha=0.3)
ax.set_ylim(MIN, MAX)
ax.set_yticklabels([""]+[str(abs(int(i ) )) for i in ax.get_yticks()[1:] ] )
ax.set_ylabel("Read Coverage")
ax.set_xlabel("Relative Genomic Position")
ax.grid()
def run(mu=0, si=1, l=0.1, pi=0.5 , we=0.5,wl=0.25, wr=0.25, N=2,NS=(100,1000), OUT=""):
FHW = open(OUT, "w")
FHW.write("~" + str(mu) + "," + str(si) + "," + str(l) + "," + str(we) + "," + str(pi) + "," + str(wl) + "," + str(wr) + "\n" )
for n in NS:
FHW.write("#" + str(int(n)) + "\n")
for b in range(N):
print n,b
FHW.write("*" + str(b) + "\n")
X = sim.runOne(mu=mu, s=si, l=1.0/l, lr=100, ll=-100, we=we,wl=wl, wr=wr, pie=pi, pil=0.1,
pir=0.9, N=int(n), SHOW=False , bins=200, noise=False, foot_print = 0 )
clf = model.EMGU(noise=True, K=1,noise_max=0.,moveUniformSupport=0,max_it=200, cores=1,
seed=False,foot_print=0)
t = clf.fit(X)
for rv in clf.rvs:
FHW.write("conv: " + str(t) + "\n")
FHW.write(rv.__str__() + "\n")
FHW.flush()
def draw_sim_one(ax, mu,si, l, w, pi):
X = sim.runOne(mu=mu, s=2, l=1.0/l, lr=100, ll=-100, we=0.5,wl=0.25, wr=0.25, pie=0.5, pil=0.1,
pir=0.9, N=300, SHOW=False , bins=200, noise=False, foot_print = 1 )
noise = np.random.uniform(-135,145, 50)
noise2 = np.random.uniform(-135,145, 50)
counts,edges = np.histogram(noise, bins=200, normed=1)
counts2,edges2 = np.histogram(noise2, bins=200, normed=1)
counts*=0.05
counts2*=0.05
rvs = [model.component_bidir( 0, 2, l, 0.5,0.5 , None,foot_print=1 )]
rvs +=[model.component_elongation( 0, 100, 0.25,1.0 ,None , None, None, None)]
rvs +=[model.component_elongation( -100, 0, 0.25,0.0 , None , None, None, None )]
X[:,1:]/=np.sum(X[:,1:])
w = (X[-1,0] - X[0,0]) / X.shape[0]
ax.bar(X[:,0], X[:,1], width=w, color="blue", edgecolor="blue",alpha=0.3)
ax.bar(X[:,0], -X[:,2], width=w, color="red", edgecolor="red",alpha=0.3)
ax.bar(edges[1:], counts,width=w, color="blue", edgecolor="blue",alpha=0.3)
ax.bar(edges2[1:], -counts2, width=w, color="red", edgecolor="red",alpha=0.3)
xs = np.linspace(X[0,0], X[-1,0], 1000)
ysf = [sum([rv.pdf(x,1) for rv in rvs ]) for x in xs]
ysr = [sum([-rv.pdf(x,-1) for rv in rvs ]) for x in xs]
ax.plot(xs,ysf,linewidth=2.5,linestyle="-", color="black")
ax.plot(xs,ysr,linewidth=2.5,linestyle="-", color="black", label="Model")
ax.set_yticks(np.linspace(min(ysr)-0.01, max(ysf)+0.01, 12))
ax.set_yticklabels([""]+ [str(abs(x))[:5] for x in np.linspace(min(ysr)+0.01, max(ysf)-0.01, 10)] + [""] )
ax.set_ylim(min(ysr)-0.01, max(ysf)+0.01)
ax.grid()
ax.set_ylabel("Density")
ax.set_xticklabels([str(int(10*x)) for x in ax.get_xticks() ])
ax.set_xlabel("Relative Genomic Coordinate")
ax.legend()
pass
ax.grid()
plt.show()
if __name__ == "__main__":
#==================================
#testing MAP-EM procedure
X = simulate.runOne(mu=0,
s=1,
l=10,
lr=100,
ll=-50,
we=0.5,
wl=0.25,
wr=0.25,
pie=0.5,
pil=0.1,
pir=0.9,
N=1000,
SHOW=False,
bins=300,
noise=False,
foot_print=10)
# chr1:20,984,647-20,991,448
#chr1:836,835-843,549
# X = load.grab_specific_region("chr1",836835, 843549,
# pos_file="/Users/joazofeifa//Lab/gro_seq_files/HCT116/bed_graph_files/DMSO2_3.pos.BedGraph",
# neg_file="/Users/joazofeifa//Lab/gro_seq_files/HCT116/bed_graph_files/DMSO2_3.neg.BedGraph",
# SHOW =False, bins=300)
# X[:,0]-=X[0,0]
# X[:,0]/=100.