Merge remote-tracking branch 'origin/master'

Python/waveform.py

@@ -3,7 +3,7 @@ from typing import Dict, Tuple, Any, List
 import numpy as np
 from scipy.interpolate import interp1d
 from AWG import *
-import cupy as cp
+# import cupy as cp
 
 
 class Waveform:
@@ -214,7 +214,8 @@ def create_path_table_gpu(
     path_table = {}  # lookup table to store all moves
     static_sig = cp.zeros(sample_len)  # for fast real-time waveform generation purposes
     t = cp.arange(sample_len) / wfm.sample_rate  # time series
-
+    dt = t[1]
+    t += dt
     nt = len(wfm.omega)
 
     diagonal_mat = cp.sin(
@@ -239,7 +240,7 @@ def create_path_table_gpu(
         # I advise reading through the notes page first before going further
         dw = omega_j - omega_i  # delta omega in the equation
         adw = abs(dw)
-        t_tot = np.sqrt(abs(4 * dw / a_max))  # calculate minimum time to complete move
+        t_tot = np.sqrt(abs(4 * dw / a_max)) + dt  # calculate minimum time to complete move
 
         phi_j = wfm.phi[j] % twopi  # wrap around two pi
         phi_i = wfm.phi[i] % twopi
@@ -396,57 +397,63 @@ def create_moving_array_GPUOTF(
     return
 
 
-def create_moving_signal_single(omega_i, omega_f, sample_rate, signal_time):
-    min_len = 2 * sample_rate / (10e3)
+def create_moving_signal_single(
+        omega_i, omega_f, sample_rate, signal_time, amp=2**12, phi=0
+):
+    min_len = 2 * sample_rate / (1e3)
     sample_len = sample_rate * signal_time
     sample_len += min_len - sample_len % min_len
     sample_len = int(sample_len)
 
     t = np.arange(sample_len) / sample_rate
-    t_tot = sample_len / sample_rate
+    t += t[1]
+    t_tot = sample_len / sample_rate + t[1]
     a = 4 * (omega_i - omega_f) / (t_tot ** 2)
     end = sample_len
     half = int(end / 2) + 1
     t1 = t[:half]
     t2 = t[half:end] - t_tot / 2
 
-    amps = 2**12
     signal = np.zeros(sample_len)
 
-    signal[:half] = omega_i * t1 - a / 6 * t1 ** 3  # t<=T/2
+    signal[:half] = phi + omega_i * t1 - a / 6 * t1 ** 3  # t<=T/2
     # ph = wfm.phi[i] + omega_i * t_tot / 2 + a / 6 * (t_tot / 2) ** 3
     signal[half:end] = signal[half - 1] + \
                      (omega_i - a / 2 * (t_tot / 2) ** 2) * t2 - \
                      a / 2 * t_tot / 2 * t2 ** 2 + \
                      a / 6 * t2 ** 3  # t>=T/2
     signal[end:] = signal[end - 1] + omega_f * (t[end:] - t[end - 1])
-    signal = (amps * np.sin(signal)).astype(np.int16)
-    return signal
+    phi_end = signal[-1]
+    signal = amp * np.sin(signal)
+    return signal.astype(np.int16), phi_end
 
 
-def create_move_then_back(omega_i, omega_f, sample_rate, move_time, stay_time):
-    min_len = 2 * sample_rate / 0.1e3
-    sample_len = sample_rate * (move_time * 2 + stay_time)
+def create_static_signal_single(
+        omega, sample_rate, signal_time, amp=2 ** 12, phi=0
+):
+    min_len = 2 * sample_rate / (1e3)
+    sample_len = sample_rate * signal_time
     sample_len += min_len - sample_len % min_len
     sample_len = int(sample_len)
 
     t = np.arange(sample_len) / sample_rate
-    t_tot = sample_len / sample_rate
-    a = 4 * (omega_i - omega_f) / (t_tot ** 2)
-    end = sample_len
-    half = int(end / 2) + 1
-    t1 = t[:half]
-    t2 = t[half:end] - t_tot / 2
+    t += t[1]
+    signal = phi + omega * t
+    phi_end = signal[-1]
+    signal = amp * np.sin(signal)
+    return signal.astype(np.int16), phi_end
 
-    amps = 2**12
-    signal = np.zeros(sample_len)
 
-    signal[:half] = omega_i * t1 - a / 6 * t1 ** 3  # t<=T/2
-    # ph = wfm.phi[i] + omega_i * t_tot / 2 + a / 6 * (t_tot / 2) ** 3
-    signal[half:end] = signal[half - 1] + \
-                     (omega_i - a / 2 * (t_tot / 2) ** 2) * t2 - \
-                     a / 2 * t_tot / 2 * t2 ** 2 + \
-                     a / 6 * t2 ** 3  # t>=T/2
-    signal[end:] = signal[end - 1] + omega_f * (t[end:] - t[end - 1])
-    signal = (amps * np.sin(signal)).astype(np.int16)
+def create_move_then_back(omega_i, omega_f, sample_rate, move_time, stay_time):
+    move0, phi0 = create_moving_signal_single(
+        omega_i, omega_f, sample_rate, move_time
+    )
+    stay, phi1 = create_static_signal_single(
+        omega_f, sample_rate, stay_time, phi=phi0
+    )
+    move1, phi2 = create_moving_signal_single(
+        omega_f, omega_i, sample_rate, move_time, phi=phi1
+    )
+    signal = np.concatenate((move0, stay, move1))
     return signal
+