m-thesis-introduction/simulations/08_beacon_sync.ipynb

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Text

{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Beacon Sync\n",
"\n",
"Synchronise two delta peaks, by using an intermediate beacon that was sent out together with it."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"import scipy.signal as signal\n",
"\n",
"import os\n",
"import sys\n",
"# Append parent directory to import path so lib can be found\n",
"sys.path.append(os.path.dirname(os.path.abspath(os.getcwd())))\n",
"from lib.util import *\n",
"from lib.plotting import *\n",
"from lib.beacon import *\n"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Beacon period [ns]: 14.285714285714285\n",
"Beacon initial [ns]: 4.4\n",
"Beacon initial [phase]: 1.9352210746113125\n",
"Beacon initial [idx]: 2.2\n",
"Beacon difference [ns]: 8.571428571428571\n",
"Beacon difference [phase]: 3.7699111843077517\n",
"Impulse offsets [ns]: [ 76. 164.]\n",
"Time difference Impulses [ns]: 88.0\n",
"Time difference Impulses [T]: 6.160000000000001\n"
]
}
],
"source": [
"us = 1e3 # ns\n",
"ns = 1/us # us\n",
"\n",
"\n",
"band = (30, 80) # MHz\n",
"samplerate = 500 # MHz\n",
"timelength = 0.2 # us\n",
"\n",
"time = np.arange(0, timelength, 1/samplerate)\n",
"\n",
"# generate beacons\n",
"if True: # in-band\n",
" f_beacon = 70 # MHz\n",
"else: # under band\n",
" f_beacon = 20 # MHz\n",
"\n",
"beacon_amplitude = 0.1\n",
"beacon_init_phase = time2phase(4.4*ns, f_beacon)\n",
"beacon_phase_offset = 1.2*np.pi\n",
"\n",
"beacons = np.array([\n",
" beacon_amplitude * sin_delay(f_beacon, time, t_delay=0, phase=-beacon_init_phase),\n",
" beacon_amplitude * sin_delay(f_beacon, time, t_delay=0, phase=-beacon_init_phase-beacon_phase_offset)\n",
"])\n",
"\n",
"\n",
"# generate impulses\n",
"impulses = []\n",
"impulses_offsets = []\n",
"impulses_def_offsets = [\n",
" (0.3*len(time),0.4*len(time)),\n",
" (0.5*len(time),0.9*len(time)),\n",
" ]# random offsets in interval\n",
"if not True:\n",
" # freeze impulses\n",
" impulses_def_offsets = [\n",
" 0.072*samplerate,\n",
" 0.168*samplerate \n",
" ]\n",
" \n",
"for i in range(2):\n",
" offset = None\n",
" if impulses_def_offsets:\n",
" if len(impulses_def_offsets) == 1:\n",
" offset = impulses_def_offsets[0]\n",
" else:\n",
" offset = impulses_def_offsets[i]\n",
" orig_imp, imp_offset = deltapeak(timelength, samplerate, offset=offset, peaklength=1)\n",
"\n",
" ## Bandpass it\n",
" imp, _ = fft_bandpass(orig_imp, band, samplerate)\n",
" imp /= np.max(imp)\n",
" \n",
" impulses.append(imp)\n",
" impulses_offsets.append(imp_offset/samplerate)\n",
"\n",
"impulses = np.array(impulses)\n",
"impulses_offsets = np.array(impulses_offsets)\n",
"print(\"Beacon period [ns]:\", 1/f_beacon/ns)\n",
"print(\"Beacon initial [ns]:\", phase2time(beacon_init_phase, f_beacon) /ns)\n",
"print(\"Beacon initial [phase]:\", beacon_init_phase)\n",
"print(\"Beacon initial [idx]:\", phase2time(beacon_init_phase, f_beacon)*samplerate)\n",
"print(\"Beacon difference [ns]:\", phase2time(beacon_phase_offset, f_beacon)/ns)\n",
"print(\"Beacon difference [phase]:\", beacon_phase_offset)\n",
"print(\"Impulse offsets [ns]:\", impulses_offsets[:,0]/ns)\n",
"print(\"Time difference Impulses [ns]: {}\".format( (impulses_offsets[1,0]-impulses_offsets[0,0])/ns ))\n",
"print(\"Time difference Impulses [T]: {}\".format( (impulses_offsets[1,0]-impulses_offsets[0,0])*f_beacon ))"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"full_signals = impulses + beacons"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 864x288 with 3 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# Make a figure showing two signals with a beacon per signal\n",
"colors = ['y','g']\n",
"multiplier_name = ['m','n']\n",
"\n",
"\n",
"fig, axes = plt.subplots(3,1, sharex=True, figsize=(12,4))\n",
"axes[-1].set_xlabel(\"Time [ns]\")\n",
"axes[-1].set_yticks([],[])\n",
"for i in range(0, 2):\n",
" axes[i].set_yticks([],[])\n",
" axes[i].set_ylabel(\"Antenna {:d}\".format(i+1))\n",
" axes[i].plot(time/ns, impulses[i])\n",
" axes[i].plot(time/ns, beacons[i], marker='.')\n",
" if not True:\n",
" axes[i].plot(time/ns, full_signals[i])\n",
"\n",
"\n",
"# indicate timing of pulses\n",
"for i, impulse_offset in enumerate(impulses_offsets):\n",
" kwargs = dict(color=colors[i])\n",
" [ax.axvline(impulse_offset/ns, **kwargs) for ax in (axes[i], axes[-1])]\n",
"\n",
"\n",
"# indicate timing of the beacons\n",
"# and annotate ticks and impulse widths\n",
"tmp_beacon_phases = beacon_init_phase + np.arange(0,2)*beacon_phase_offset\n",
"if True: # mod phases\n",
" tmp_beacon_phases %= 2*np.pi\n",
"tmp_beacon_offsets = phase2time(tmp_beacon_phases, f_beacon)\n",
"\n",
"\n",
"A = np.empty(2)\n",
"B = np.empty(2)\n",
"for i in range(0,2):\n",
" kwargs = dict(color=colors[i], ls=(0, (3,2)))\n",
" tick_kwargs = dict(color='k', alpha=0.2)\n",
"\n",
" # indicate every period of the beacon\n",
" beacon_ticks = tmp_beacon_offsets[i] + [(n)*1/f_beacon for n in range(1+int((time[-1] - time[0]) * f_beacon))]\n",
"\n",
" [axes[i].axvline(tick/ns, **{**kwargs, **tick_kwargs}) for tick in beacon_ticks]\n",
"\n",
" # reference period in beacon\n",
" [ax.axvline(tmp_beacon_offsets[i]/ns, **kwargs) for ax in (axes[i], axes[-1])]\n",
"\n",
" # annotate width between impulse and closest beacon tick\n",
" # and closest beacon tick and reference tick\n",
" closest_beacon_tick_id = np.argmin(np.abs(beacon_ticks-impulses_offsets[i]))\n",
" if closest_beacon_tick_id != 0 and beacon_ticks[closest_beacon_tick_id] > impulses_offsets[i]:\n",
" closest_beacon_tick_id -= 1\n",
" closest_beacon_tick = beacon_ticks[closest_beacon_tick_id]\n",
"\n",
" annotate_width(axes[i], f\"$A_{i+1}$\", closest_beacon_tick/ns, impulses_offsets[i]/ns, 0.7)\n",
" annotate_width(axes[i], f\"$B_{i+1}={multiplier_name[i]}T$\", closest_beacon_tick/ns, tmp_beacon_offsets[i]/ns, 0.4)\n",
"\n",
" A[i] = closest_beacon_tick - impulses_offsets[i]\n",
" B[i] = closest_beacon_tick - tmp_beacon_offsets[i]\n",
"\n",
"# annotate width between beacon reference periods\n",
"annotate_width(axes[-1], \"$t_\\phi$\", tmp_beacon_offsets[0]/ns, tmp_beacon_offsets[-1]/ns, 0.4)\n",
"\n",
"# annotate width between pulses\n",
"annotate_width(axes[-1], \"$\\Delta t$\", impulses_offsets[0]/ns, impulses_offsets[-1]/ns, 0.4)\n",
"\n",
"\n",
"fig.show()\n",
"if False:\n",
" fname = 'figures/08_beacon_sync_timing_outline'\n",
"\n",
" # Dump figure\n",
" fig.savefig(fname +'.pdf')\n",
" \n",
" # Dump information into accompanying file\n",
" with open(fname + '.dat', 'w+') as fp:\n",
" fp.write(\"f_beacon = {}MHz\\n\".format(f_beacon))\n",
" fp.write(\"samplerate = {}\\n\".format(samplerate))\n",
" fp.write(\"band = {}MHz\\n\".format(band))\n",
" fp.write(\"timelength = {}us\\n\".format(timelength))\n",
" \n",
" fp.write(\"-\"*8 + \"\\n\")\n",
" fp.write(\"\\Delta t = {}ns\\n\".format( (impulses_offsets[1][0] - impulses_offsets[0][0])/ns ))\n",
" fp.write(\"t_phi = {}ns\\n\".format( (tmp_beacon_offsets[1]-tmp_beacon_offsets[0])/ns ))\n",
" fp.write(\"\\Delta A = {}ns\\n\".format( (A[1] - A[0])/ns ))\n",
" fp.write(\"kT = {}ns = {}T\\n\".format( (B[1]-B[0])/ns, (B[1]-B[0])*f_beacon ))\n",
" \n",
" fp.write(\"-\"*8 + \"\\n\")\n",
" fp.write(\"A_1 = {}ns\\n\".format( (A[0])/ns ))\n",
" fp.write(\"A_2 = {}ns\\n\".format( (A[1])/ns ))\n",
" fp.write(\"B_1 = {}ns = {}T\\n\".format( (B[0])/ns, (B[0]*f_beacon) ))\n",
" fp.write(\"B_2 = {}ns = {}T\\n\".format( (B[1])/ns, (B[1]*f_beacon) ))"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\\Delta t = 88.0ns\n",
"\\Delta A = -8.000000000000007ns\n",
"t_phi = 8.571428571428573ns\n",
"B_1 = 71.42857142857142ns = 5.0T\n",
"B_2 = 142.85714285714283ns = 10.0T\n",
"kT = 71.42857142857142ns = 5.0T\n"
]
}
],
"source": [
"t_phi = (tmp_beacon_offsets[1]-tmp_beacon_offsets[0])\n",
"Delta_A = (A[1] - A[0])\n",
"\n",
"print(\"\\Delta t = {}ns\".format( (impulses_offsets[1][0] - impulses_offsets[0][0])/ns ))\n",
"print(\"\\Delta A = {}ns\".format( Delta_A/ns ))\n",
"print(\"t_phi = {}ns\".format( t_phi/ns ))\n",
"print(\"B_1 = {}ns = {}T\".format( (B[0])/ns, (B[0]*f_beacon) ))\n",
"print(\"B_2 = {}ns = {}T\".format( (B[1])/ns, (B[1]*f_beacon) ))\n",
"print(\"kT = {}ns = {}T\".format( (B[1]-B[0])/ns, (B[1]-B[0])*f_beacon ))\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"$\n",
"\\Delta t = (A_2 + B_2) - (A_1 + B_1) + t_\\phi\\\\\n",
"\\quad = (A_2 - A_1) + (B_2 - B_1) + t_\\phi\\\\\n",
"\\quad = (A_2 - A_1) + (nT - mT) + t_\\phi\\\\\n",
"\\quad = \\Delta A + (kT) + t_\\phi\n",
"$\n",
"\n",
", where $\\Delta A < T$ and $k \\in \\mathbb{Z}$ and $t_\\phi$ is minimisable by synchronising the beacons.\n",
"\n",
"Then $\\Delta t$ can be determined by iteratively summing the signals, changing $k$, and finding the $k$ belonging to the maximum of the sums."
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"def find_beacon_integer_period_sum(samplerate, f_beacon, ref_impulse, impulse, k_step=1):\n",
" max_k = int( len(ref_impulse)*f_beacon/samplerate )\n",
" ks = np.arange(-max_k/2, max_k/2, step=k_step)\n",
" \n",
" maxima = np.empty(len(ks))\n",
" \n",
" best_i = 0\n",
" \n",
" for i,k in enumerate(ks, 0):\n",
" augmented_impulse = time_roll(impulse, samplerate, k/f_beacon)\n",
" \n",
" maxima[i] = max(ref_impulse + augmented_impulse)\n",
" \n",
" if maxima[i] > maxima[best_i]:\n",
" best_i = i\n",
" \n",
" return ks[best_i], (ks, maxima)\n",
"\n",
"def find_beacon_integer_period(samplerate, f_beacon, ref_impulse, impulse, k_step=1):\n",
" return find_beacon_integer_period_sum(samplerate, f_beacon, ref_impulse, impulse, k_step=k_step)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Best k: -5\n",
"Maximum: 2.0\n"
]
},
{
"data": {
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\n",
"text/plain": [
"<Figure size 864x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# Make figure showing the sums depending on k\n",
"ref_impulse = impulses[0]\n",
"my_impulse = impulses[1]\n",
"\n",
"# remove 'already determined' offsets\n",
"if True:\n",
" # $t_\\phi$ offset\n",
" my_impulse = time_roll(my_impulse, samplerate, -t_phi)\n",
"\n",
" # $\\Delta A$ offset\n",
" my_impulse = time_roll(my_impulse, samplerate, +Delta_A)\n",
"\n",
"best_k, (ks, maxima) = find_beacon_integer_period(samplerate, f_beacon, ref_impulse, my_impulse)\n",
"print(\"Best k: {:0g}\".format(best_k))\n",
"print(\"Maximum: {}\".format(maxima[np.where(ks == best_k)][0]))\n",
"\n",
"\n",
"# Make figure\n",
"fig, axes = plt.subplots(1, 1, sharex=True,figsize=(12,4))\n",
"if not hasattr(axes, 'ndim'):\n",
" axes = [axes]\n",
"\n",
"axes[0].set_title(\"Sum of impulses with $kT$ offsets. Best offset: ${:.0f}*T$\".format(best_k))\n",
"axes[-1].set_xlabel(\"Time [ns]\")\n",
"\n",
"if not True:\n",
" i=0\n",
" axes[i].set_ylabel(\"Reference\")\n",
" axes[i].plot(time/ns, ref_impulse, label=\"reference\")\n",
" axes[i].plot(time/ns, my_impulse, label='impulse')\n",
" axes[i].legend()\n",
"\n",
"axes[-1].set_ylabel(\"Coherence Sum\")\n",
"\n",
"best_maximum = np.max(maxima)\n",
"axes[-1].axhline(best_maximum, alpha=0.7)\n",
"\n",
"for i, k in enumerate(ks, 0):\n",
" sample_offset = int(k*1/f_beacon*samplerate)\n",
" augmented_impulses = np.roll(my_impulse, sample_offset)\n",
" \n",
" summed_impulse = ref_impulse + augmented_impulses\n",
" if True or k%2 == 1:\n",
" axes[-1].plot(time/ns, summed_impulse, label='k={:.0f}'.format(k),\n",
" alpha=0.1 + 0.9*1/(1+2*abs(best_maximum-maxima[i]))\n",
" )\n",
" \n",
"axes[-1].legend()\n",
"fig.show()\n",
"\n",
"del ref_impulse\n",
"del my_impulse"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 1. Solve it\n",
"\n",
" 1. Find $t_\\phi$\n",
" 2. Find $\\Delta A$, and $kT$"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"##### 1.1 Beacon Phase Delay ($t_\\phi$)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Beacon delays [ns] \\pm k*14.285714285714285ns: [0. 8.57142857]\n"
]
}
],
"source": [
"abs_beacon_time_delays_tmp = np.array([\n",
" beacon_time_delay(samplerate, beacons[0], beacon)\n",
" for beacon in beacons\n",
"])\n",
"\n",
"\n",
"abs_beacon_time_delays = abs_beacon_time_delays_tmp[:,0]\n",
"t_phi = np.array(abs_beacon_time_delays % (1/f_beacon), dtype=np.float64)\n",
"beacon_time_delays_err = abs_beacon_time_delays_tmp[:,1]\n",
"\n",
"print(\"Beacon delays [ns] \\pm k*{}ns: {}\".format(1/f_beacon/ns, t_phi/ns))"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# Make a figure showing the corrected beacons\n",
"fig, ax = plt.subplots(1,1, sharex=True)\n",
"ax.set_xlabel(\"Time [ns]\")\n",
"ax.set_ylabel(\"Amplitude [au]\")\n",
"ax.set_title(\n",
" \"Beacon delays [ns] $\\pm$ $k*{}$\\n$t_{{\\phi}}$ = {}\"\n",
" .format(1/f_beacon/ns, t_phi/ns)\n",
")\n",
"\n",
"for i, _ in enumerate(beacons):\n",
" l = ax.plot(\n",
" time/ns, beacons[i],\n",
" label=\"ch {}\".format(i), \n",
" ls ='--', \n",
" alpha=0.5\n",
" )\n",
" \n",
" # indicate start of uncorrected beacons\n",
" ax.axvline(\n",
" t_phi[i]/ns,\n",
" color=l[0].get_color(),\n",
" ls = '--'\n",
" )\n",
" \n",
" ax.plot(\n",
" (time-t_phi[i])/ns,\n",
" beacons[i],\n",
" label='ch {} corrected'.format(i),\n",
" color=l[0].get_color(),\n",
" ls=(5*i+2, (20, 20))\n",
" )\n",
" \n",
"ax.legend(ncol=2)\n",
"ax.margins(y=0.3)\n",
"if True:\n",
" ax.set_xlim(time[0]/ns - 10, time[2*samplerate//f_beacon]/ns)\n",
"\n",
"fig.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"##### 1.2 Impulse delays ($\\Delta A, kT$)\n",
"\n",
"Find the delay within a single beacon period"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"impulse_max_time = np.argmax(impulses, axis=1) /samplerate\n",
"impulse_time_in_periods = np.array((impulse_max_time - t_phi)*f_beacon)\n",
"B, A = np.divmod(impulse_time_in_periods, 1)\n",
"\n",
"# subtract the reference beacon's value to obtain time differences\n",
"A -= A[0]\n",
"B -= B[0]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### 1.3 Total Time delay"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Δ𝐴 = [0. 8.]\n",
"B = kT = [0. 5.]T\n",
"𝑡𝜙 = [0. 8.57142857]\n",
"Δt = 0.08800000000000001\n",
"Preset Δt = 0.08800000000000001\n"
]
}
],
"source": [
"print(\"Δ𝐴 = {}\".format(A /f_beacon/ns))\n",
"print(\"B = kT = {}T\".format(B))\n",
"print(\"𝑡𝜙 = {}\".format(t_phi/ns))\n",
"\n",
"\n",
"delta_t = A/f_beacon + B/f_beacon + t_phi\n",
"\n",
"print(\"Δt = {}\".format(delta_t[1]))\n",
"\n",
"print(\"Preset Δt = {}\".format(impulses_offsets[1,0]-impulses_offsets[0,0]))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
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