def _spectrum(a, b):
def func(x, y, a, b):
Delta = b
#omega = 2.0*3.14159/20.0
data = numpy.zeros((len(x), len(y)))
for i_x in range(len(x)):
data[i_x, :] = a*numpy.exp(-(x[i_x]/Delta)**2)* \
numpy.exp(-(y/Delta)**2)
data[i_x, :] -= (a/2.0)*numpy.exp(-(x[i_x]/Delta)**2)* \
numpy.exp(-((y-Delta)/Delta)**2)
return data
xrange = qr.FrequencyAxis(-50.0, 100, 1.0)
yrange = qr.FrequencyAxis(-50.0, 100, 1.0)
data = func(xrange.data, yrange.data, a, b)
return (xrange, yrange, data)
def step_given_16(context, N, step):
"""
And I have a FrequencyAxis of lenght {N} starting from zero with certain {step}
"""
length = int(N)
step = float(step)
vaxis = qr.FrequencyAxis(0.0, length, step)
context.vaxis = vaxis
context.length = length
context.step = step
def get_spectrum_from_data(xax, yax, data, timestamp):
x_ax_n = len(xax)
x_ax_start = xax[0]
x_ax_fin = xax[-1]
x_ax_len = x_ax_fin - x_ax_start
x_ax_step = x_ax_len / x_ax_n
x_ax = qr.FrequencyAxis(x_ax_start, x_ax_n, x_ax_step)
y_ax_n = len(yax)
y_ax_start = yax[0]
y_ax_fin = yax[-1]
y_ax_len = y_ax_fin - y_ax_start
y_ax_step = y_ax_len / y_ax_n
y_ax = qr.FrequencyAxis(y_ax_start, y_ax_n, y_ax_step)
onetwod = qr.TwoDResponse()
onetwod.set_axis_1(x_ax)
onetwod.set_axis_3(y_ax)
onetwod._add_data(data, resolution="off")
onetwod.set_t2(timestamp)
return onetwod
Ns = [100, 101]
print("\nStarting with TimeAxis:")
for N in Ns:
print("\nN =", N)
tmaxs1 = qr.TimeAxis(0.0, N, 10.0)
print("TimeAxis type :", tmaxs1.atype)
print("start, length, step :", tmaxs1.start, tmaxs1.length, tmaxs1.step)
fraxs1 = tmaxs1.get_FrequencyAxis()
print("FrequencyAxis type :", fraxs1.atype)
print("start, length, step :", fraxs1.start, fraxs1.length, fraxs1.step)
print("Starting with FrequencyAxis:")
for N in Ns:
print("\nN =", N)
fraxs2 = qr.FrequencyAxis(0.0, N, 0.01)
print("FrequencyAxis type :", fraxs2.atype)
print("start, length, step :", fraxs2.start, fraxs2.length, fraxs2.step)
tmaxs2 = fraxs2.get_TimeAxis()
print("TimeAxis type :", tmaxs2.atype)
print("start, length, step :", tmaxs2.start, tmaxs2.length, tmaxs2.step)
print("\n")
print("Non-default behaviour")
print("---------------------")
print("\nStarting with TimeAxis of `complete` type:")
for N in Ns:
print("\nN =", N)
tmaxs1 = qr.TimeAxis(0.0, N, 10.0, atype="complete")
print("TimeAxis type :", tmaxs1.atype)
""" Usage of finite transform limited pulses """ import quantarhei as qr import matplotlib.pyplot as plt lab = qr.LabSetup() freq = qr.FrequencyAxis(-2500, 1000, 5.0) pulse2 = dict(ptype="Gaussian", FWHM=800.0, amplitude=1.0) params = (pulse2, pulse2, pulse2) lab.set_pulse_shapes(freq, params) freq2 = qr.FrequencyAxis(-1000, 100, 20.0) dfc1 = lab.get_pulse_spectrum(1, freq.data) dfc2 = lab.get_pulse_spectrum(1, freq2.data) pl1 = plt.plot(freq.data, dfc1) pl2 = plt.plot(freq2.data, dfc2) plt.show()