def Nov18():
a =loadtxt('/home/chris/Dropbox/DataWeiss/151118/Dots with untreated alumina.csv', unpack = True, delimiter = ',', skiprows = 1,usecols = (0,1,7,9,11))
s = pf(a[0][0:150],a[4][0:150],1)
a[4]-=polyval(a[0],s)
for i in a[array([1,3,4])]:#[1:]:
i-=i[150]
r = findpeak(a[0],i,(405,420))
print r
i-=i[150]
i/=r[1]
plot(a[0], i)
legend(['as prep', 'alumina 4 mg', 'alumina 5.8 mg'])
ylabel('absorbance')
xlabel('wavelength')
return 0
def findderivative(x,y,derivorder=1):
window_len=25
# if spectrum.ndim != 1:
# raise ValueError, "smooth only accepts 1 dimension arrays."
#
# if spectrum.size < window_len:
# raise ValueError, "Input vector needs to be bigger than window size."
retval = numpy.ndarray(y.shape)
for i in range(y.size):
i_min = max(0,i-window_len/2)
i_max = min( i+window_len/2-1, y.size)
fit = pf(x[i_min:i_max+1],y[i_min:i_max+1],min(5,window_len))
retval[i] = polyval(x[i],polyder(fit,derivorder),tensor=False)
return retval
def exampleplot():
figure()
ax1=subplot(121)
ax2=subplot(122)
c = linspace(0,10,1000)
cmaxdot = 0.2
# subplot(121)
for K in [100,1000,10000]:
K=float(K)
a = K
#def b():return -ctot0*K - K*c +K*cmaxdot+1
#def d():return ctot0+c
#
#def cfree():return (-b()+sqrt(b()**2-4*a*d()))/(2*a)
a=K
b=1+K*cmaxdot-K*c
d=-c
cfree = (-b+sqrt(b**2-4*a*d))/(2*a)
cfree2= (-b-sqrt(b**2-4*a*d))/(2*a)
r = pf(c[10:15],cfree[10:15],1)
#print r[0], (K+0.5*((1+K*cmaxdot-K*xlarge)**2+4*K*xlarge)**-0.5*(-2*K*(1+K*cmaxdot-K*xlarge)+4*K))/(2*K)
M = (r[0]-0.5)**2
A = (M-0.5)#*xlarge**2
B = (2*M-1)#*xlarge
C = M-0.5
print M,A,B,C,B**2
#print K,'estimated K=',(-B+sqrt(B**2-4*A*C))/(2*A)
print 'early slope=', cfree[0]/c[1],cfree[0]/c[1]-c[1]*r[1]
# plot(c[:10],(c[:10]-0.1)*r[1]+cfree[10]/c[10])
ax1.plot(c,cfree/c)
ax2.plot(c,cfree/c)
# plot(c,findderivative(c,cfree/c,derivorder=1)/200,'--')
#plot(c,fd(c,cfree/c),'-.')
#plot(c,K*cfree/(1+K*cfree))
# plot(c,cfree2)
legend([1,10,100,1000])
ax1.set_ylabel('$\delta_{observed}$',fontsize=24)
#ax2.set_ylabel('$\delta$',fontsize=24)
ax1.set_xlabel('c$_{total}$ (mM)', fontsize=24)
ax2.set_xlabel('c$_{total}$ (mM)', fontsize=24)
ax2.set_xlim((0,0.4))
ax2.set_xticks([0,0.1,0.2,0.3,0.4,0.5])
ax1.set_yticks([0,1])
ax2.set_yticks([])
ax1.set_yticklabels(['$\delta_{bound}$','$\delta_{free}$'],fontsize=24)
figure()
ax1=subplot(211)
ax2=subplot(212)
for K in [50]:
K=float(K)
a = K
#def b():return -ctot0*K - K*c +K*cmaxdot+1
#def d():return ctot0+c
#
#def cfree():return (-b()+sqrt(b()**2-4*a*d()))/(2*a)
a=K
b=1+K*cmaxdot-K*c
d=-c
cfree = (-b+sqrt(b**2-4*a*d))/(2*a)
ax1.plot(c,cfree/c)
ax2.plot(c,c-cfree)#K*cfree*cmaxdot/(1+K*cfree))
ax2.plot(c,cfree,'--')
ax2.plot(c,c)
legend(['bound', 'free', 'total'],loc=2)
ax1.set_ylabel('$\delta_{observed}$',fontsize=24)
ax2.set_xlabel('c$_{total}$ (mM)', fontsize=24)
ax2.set_ylabel('c (mM)',fontsize=24)
#ax2.set_xticks([0,0.1,0.2,0.3,0.4,0.5])
ax1.set_yticks([0,1])
ax1.set_xlim(0,1)
ax2.set_xlim(0,1)
#ax1.set_ylim(-0.1,1.1)
ax2.set_ylim(0,1)
ax1.set_yticklabels(['$\delta_{bound}$','$\delta_{free}$'],fontsize=24)
# subplot(122)
# for cinit in [0,0.1,0.2,0.5,1]:
# a = K
# #def b():return -ctot0*K - K*c +K*cmaxdot+1
# #def d():return ctot0+c
# #
# #def cfree():return (-b()+sqrt(b()**2-4*a*d()))/(2*a)
# ctot = cinit+c
# a=K
# b=1+K*cmaxdot-K*ctot
# d=-ctot
#
# cfree = (-b+sqrt(b**2-4*a*d))/(2*a)
#
# plot(c,cfree/ctot)
# # plot(c,cfree2)
# legend([0,0.1,0.2,0.5,1])
return 0