First push, taken from the previous Spintrum software model

examples/TimeDependent/MagneticResonance.py

@@ -0,0 +1,52 @@
+#!/usr/bin/python3
+
+import spintrum
+import math
+import matplotlib.pyplot as plt
+import numpy as np
+import matplotlib as mpl
+from mpl_toolkits.mplot3d import Axes3D
+
+
+def run(dirs):
+    gammas = [10] #Hz/T
+    jCouplings = [[0]]
+
+    BThermal = 10e0
+    T2 = 10
+    sampleRate = 1e4
+    T= 1/sampleRate
+    B0=10.
+    B1=0.3e0
+    points = 1650
+    f = B0*gammas[0]
+    bx = np.array([np.sin(2*math.pi*f*t/sampleRate)*B1 for t in range(points)])
+    by = np.array([np.cos(2*math.pi*f*t/sampleRate)*B1 for t in range(points)])
+
+    spinOp = spintrum.SpinOperations()
+    spinOp.add_operation(spintrum.SpinOperations.OPERATION__THERMAL_POPULATE,
+                         {'Bx': 0, 'By': 0, 'Bz': BThermal, 'T': 293.778})
+    spinOp.add_operation(spintrum.SpinOperations.OPERATION__SET_HAMILTONIAN,
+                         {'Bx': 0, 'By': 0, 'Bz': B0})
+    spinOp.add_operation(spintrum.SpinOperations.OPERATION__EVOLVE_TIME_DEPENDENT,
+                         {'threads': 4, 'samplingRate': sampleRate, 'store': dirs,
+                          'input': {'Bx': bx, 'By': by}})
+
+    signal = spintrum.simulate(gyromagneticRatios=gammas,
+                               jCouplings=jCouplings,
+                               spinOperations=spinOp)
+    return signal
+
+#this will result in points in the form xyzxyzxyz (order doesn't make a difference)
+data = run('xyz')
+
+mpl.rcParams['legend.fontsize'] = 10
+
+fig = plt.figure()
+ax = fig.gca(projection='3d')
+datanp = np.transpose(np.split(np.array(data),len(data)/3))
+
+ax.plot(datanp[0], datanp[1], datanp[2], label='parametric curve')
+ax.legend()
+
+plt.show()