def trapezoidArray(f,dx):
"""
same as trapezoidRule() but return the integral as fn of z
(mostly in-place operations for optimized memory usage)
"""
i = pl.add.accumulate(f)
pl.add(i,-0.5*f, i)
pl.add(i,-0.5*f[0], i)
pl.multiply(i,dx, i)
return i
def beep(freq_phase_amp, L):
'''Additive synthesis of sinewaves.
freq_phase_amp -- a numpy array with a row for each sinewave, and
frequency, phase and amplitude in each column.
L -- length in samples.
'''
res = pl.zeros(L)
ii = pl.arange(L)
tmp = pl.empty(L)
for f, p, a in freq_phase_amp:
pl.multiply(ii, f * tau / sr, tmp)
pl.add(tmp, p, tmp)
pl.sin(tmp, tmp)
pl.multiply(tmp, a, tmp)
pl.add(res, tmp, res)
return res
def directsum(arg): #check if all matrices are square for i in range(arg.shape[1]): assert arg[0,i].shape[0]==arg[0,i].shape[1], 'Matrix '+str(arg[i])+ ' is not square.' #calculate the shape of the result of the directsum operation temp=(0,0) for i in range(arg.shape[1]): temp=pb.add(temp,arg[0,i].shape) dsum =pb.zeros(temp) dsum[:arg[0,0].shape[0],:arg[0,0].shape[1]]=arg[0,0] rc_Indices=0 for i in range(1,arg.shape[1]): rc_Indices+=arg[0,i-1].shape[0] dsum[rc_Indices:rc_Indices+arg[0,i].shape[0],rc_Indices:rc_Indices+arg[0,i].shape[1]]=arg[0,i] return dsum
def scatter(data,lim,tilt,include):
tiltX = tilt[0]
tiltY = tilt[1]
loadData = np.loadtxt(data)
x = loadData[:,2]
y = loadData[:,1]
#Center peak vales at (0,0)
centx = np.subtract(x,float(lim))
centy = np.subtract(y,float(lim))
#Calculate distance of peaks from expected angle
dist = []
for i in xrange(len(loadData[:,1])):
rx = centx[i]
ry = centy[i]
distance = math.sqrt(((rx - tiltX)*(rx - tiltX)) + ((ry - tiltY)*(ry - tiltY))/2)
dist.append(distance)
newDist = sorted(dist)
numReadLines = round((float(include)/100)*len(loadData[:,1]))
includeRadius = []
for j in xrange(numReadLines):
includeRadius = newDist[j]
#Create function for plotting circle
theta = np.linspace(0,2*math.pi)
incRadx = includeRadius*pylab.cos(theta)
incRady = includeRadius*pylab.sin(theta)
incRadx = pylab.add(incRadx,tiltX)
incRady = pylab.add(incRady,tiltY)
#Set radii for concentric circles
rad1 = 10
rad2 = 20
rad3 = 30
rad4 = 40
rad5 = 50
rad6 = 60
#Create x,y coords for concentric cricles
cx1 = rad1*pylab.cos(theta)
cy1 = rad1*pylab.sin(theta)
cx2 = rad2*pylab.cos(theta)
cy2 = rad2*pylab.sin(theta)
cx3 = rad3*pylab.cos(theta)
cy3 = rad3*pylab.sin(theta)
cx4 = rad4*pylab.cos(theta)
cy4 = rad4*pylab.sin(theta)
cx5 = rad5*pylab.cos(theta)
cy5 = rad5*pylab.sin(theta)
cx6 = rad6*pylab.cos(theta)
cy6 = rad6*pylab.sin(theta)
#Create axes
line1 = np.linspace(-60,60,100)
#Create zeros array
line2 = []
i = 1
while i <= 100:
line2.append('0')
i = i + 1
fig = plt.figure(1)
scatter = plt.subplot(111,aspect='equal')
majorLocator = MultipleLocator(10)
majorFormatter = FormatStrFormatter('%d')
minorLocator = MultipleLocator(5)
scatter.set_xlabel('Tilt direction (degrees)',fontsize=15)
scatter.set_ylabel('Tilt direction (degrees)',fontsize=15)
scatter.set_title('%d'%(include) + '% ' + 'of particles are within %d degrees of expected angle'%(round(includeRadius)))
scatter.plot(cx1,cy1,c = 'k')
scatter.plot(cx2,cy2,c = 'k')
scatter.plot(cx3,cy3,c = 'k')
scatter.plot(cx4,cy4,c = 'k')
scatter.plot(cx5,cy5,c = 'k')
scatter.plot(cx6,cy6,c = 'k')
scatter.plot(cx5,cy5,c = 'k')
scatter.plot(incRadx,incRady,c = 'r')
scatter.plot(line2,line1,c='k')
scatter.plot(line1,line2,c='k')
scatter.scatter(centx,centy,marker='+',c='k',edgecolor='k',s=55)
majorLocator = MultipleLocator(10)
majorFormatter = FormatStrFormatter('%d')
minorLocator = MultipleLocator(5)
scatter.xaxis.set_major_locator(majorLocator)
scatter.xaxis.set_major_formatter(majorFormatter)
scatter.xaxis.set_minor_locator(minorLocator)
scatter.yaxis.set_major_locator(majorLocator)
scatter.yaxis.set_major_formatter(majorFormatter)
scatter.yaxis.set_minor_locator(minorLocator)
lim1 = -float(lim)
plt.xlim(lim1,float(lim))
plt.ylim(lim1,float(lim))
outFILE = '%s.png' %(data[:-4])
plt.savefig(outFILE,dpi=150,format='png')
def scatter(self, data, lim, tilt, include):
tiltX = tilt[0]
tiltY = tilt[1]
loadData = np.loadtxt(data)
x = loadData[:, 2]
y = loadData[:, 1]
#Center peak vales at (0,0)
centx = np.subtract(x, lim)
centy = np.subtract(y, lim)
#Calculate distance of peaks from expected angle
dist = []
for i in xrange(len(loadData[:, 1])):
rx = centx[i]
ry = centy[i]
distance = math.sqrt(((rx - tiltX) * (rx - tiltX)) +
((ry - tiltY) * (ry - tiltY)) / 2)
dist.append(distance)
newDist = sorted(dist)
numReadLines = round((float(include) / 100) * len(loadData[:, 1]))
includeRadius = []
for j in xrange(numReadLines):
includeRadius = newDist[j]
#Create function for plotting circle
theta = np.linspace(0, 2 * math.pi)
incRadx = includeRadius * pylab.cos(theta)
incRady = includeRadius * pylab.sin(theta)
incRadx = pylab.add(incRadx, tiltX)
incRady = pylab.add(incRady, tiltY)
#Set radii for concentric circles
rad1 = 10
rad2 = 20
rad3 = 30
rad4 = 40
rad5 = 50
rad6 = 60
#Create x,y coords for concentric cricles
cx1 = rad1 * pylab.cos(theta)
cy1 = rad1 * pylab.sin(theta)
cx2 = rad2 * pylab.cos(theta)
cy2 = rad2 * pylab.sin(theta)
cx3 = rad3 * pylab.cos(theta)
cy3 = rad3 * pylab.sin(theta)
cx4 = rad4 * pylab.cos(theta)
cy4 = rad4 * pylab.sin(theta)
cx5 = rad5 * pylab.cos(theta)
cy5 = rad5 * pylab.sin(theta)
cx6 = rad6 * pylab.cos(theta)
cy6 = rad6 * pylab.sin(theta)
#Create axes
line1 = np.linspace(-60, 60, 100)
#Create zeros array
line2 = []
i = 1
while i <= 100:
line2.append('0')
i = i + 1
fig = plt.figure(1)
scatter = plt.subplot(111, aspect='equal')
majorLocator = MultipleLocator(10)
majorFormatter = FormatStrFormatter('%d')
minorLocator = MultipleLocator(5)
scatter.set_xlabel('Tilt direction (degrees)', fontsize=15)
scatter.set_ylabel('Tilt direction (degrees)', fontsize=15)
scatter.set_title(
'%d' % (include) + '% ' +
'of particles are within %d degrees of expected angle' %
(round(includeRadius)))
scatter.plot(cx1, cy1, c='k')
scatter.plot(cx2, cy2, c='k')
scatter.plot(cx3, cy3, c='k')
scatter.plot(cx4, cy4, c='k')
scatter.plot(cx5, cy5, c='k')
scatter.plot(cx6, cy6, c='k')
scatter.plot(cx5, cy5, c='k')
scatter.plot(incRadx, incRady, c='r')
scatter.plot(line2, line1, c='k')
scatter.plot(line1, line2, c='k')
scatter.scatter(centx, centy, marker='+', c='k', edgecolor='k', s=55)
majorLocator = MultipleLocator(10)
majorFormatter = FormatStrFormatter('%d')
minorLocator = MultipleLocator(5)
scatter.xaxis.set_major_locator(majorLocator)
scatter.xaxis.set_major_formatter(majorFormatter)
scatter.xaxis.set_minor_locator(minorLocator)
scatter.yaxis.set_major_locator(majorLocator)
scatter.yaxis.set_major_formatter(majorFormatter)
scatter.yaxis.set_minor_locator(minorLocator)
plt.xlim(-lim, lim)
plt.ylim(-lim, lim)
outFILE = '%s.png' % (data[:-4])
plt.savefig(outFILE, dpi=150, format='png')