{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", "\n", "import numpy as np\n", "import scipy.fft as ft\n", "import matplotlib.pyplot as plt\n", "import matplotlib.gridspec as gridspec\n", "import matplotlib.ticker as tck\n", "rng = np.random.default_rng()" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "# copied from 01_fourier 4988cf4f6e81b6b9510bf55a264011c37dc71872\n", "def ft_spectrum( signal, sample_rate, fft=None, freq=None, mask_bias=False):\n", " \"\"\"Return a FT of $signal$, with corresponding frequencies\"\"\"\n", " n_samples = len(signal)\n", " real_signal = np.isrealobj(signal)\n", " \n", " if fft is None:\n", " if real_signal:\n", " fft = ft.rfft\n", " freq = ft.rfftfreq\n", " else:\n", " fft = ft.fft\n", " freq = ft.fftfreq\n", "\n", " if freq is None:\n", " freq = ft.fftfreq\n", " \n", " spectrum = fft(signal) / sample_rate\n", " freqs = freq(n_samples, 1/sample_rate)\n", " \n", " if not mask_bias:\n", " return spectrum, freqs\n", " else:\n", " return spectrum[1:], freqs[1:]\n", "\n", " \n", "def plot_spectrum( ax, spectrum, freqs, plot_complex=False, plot_power=False, plot_amplitude=None):\n", " \"\"\" Plot a signal's spectrum on an Axis object\"\"\"\n", " plot_amplitude = plot_amplitude or (not plot_power and not plot_complex)\n", " alpha = 1\n", " \n", " ax.set_title(\"Spectrum\")\n", " ax.set_xlabel(\"f (Hz)\")\n", " ylabel = \"\"\n", " if plot_amplitude or plot_complex:\n", " ylabel = \"Amplitude\"\n", " if plot_power:\n", " if ylabel:\n", " ylabel += \"|\"\n", " ylabel += \"Power\"\n", " ax.set_ylabel(ylabel)\n", "\n", " if plot_complex:\n", " alpha = 0.5\n", " ax.plot(freqs, np.real(spectrum), '.-', label='Real', alpha=alpha)\n", " ax.plot(freqs, np.imag(spectrum), '.-', label='Imag', alpha=alpha)\n", "\n", " if plot_power:\n", " ax.plot(freqs, np.abs(spectrum)**2, '.-', label='Power', alpha=alpha)\n", " \n", " if plot_amplitude:\n", " ax.plot(freqs, np.abs(spectrum), '.-', label='Abs', alpha=alpha)\n", "\n", " ax.legend()\n", "\n", " return ax\n", "\n", "\n", "def plot_phase( ax, spectrum, freqs, ylim_epsilon=0.5):\n", " ax.set_ylabel(\"Phase\")\n", " ax.set_xlabel(\"f (Hz)\")\n", "\n", " ax.plot(freqs, np.angle(spectrum), '.-')\n", " ax.set_ylim(-1*np.pi - ylim_epsilon, np.pi + ylim_epsilon)\n", " \n", " return ax\n", "\n", "\n", "def plot_combined_spectrum(spectrum, freqs, \n", " spectrum_kwargs={}, fig=None, gs=None):\n", " \"\"\"Plot both the frequencies and phase in one figure.\"\"\"\n", " \n", " # configure plotting layout\n", " if fig is None:\n", " fig = plt.figure(figsize=(8, 16))\n", "\n", " if gs is None:\n", " gs = gridspec.GridSpec(2, 1, figure=fig, height_ratios=[3,1], hspace=0)\n", "\n", " ax1 = fig.add_subplot(gs[:-1, -1])\n", " ax2 = fig.add_subplot(gs[-1, -1], sharex=ax1)\n", "\n", " axes = np.array([ax1, ax2])\n", " \n", " # plot the spectrum \n", " plot_spectrum(ax1, spectrum, freqs, **spectrum_kwargs)\n", "\n", " # plot the phase\n", " plot_phase(ax2, spectrum, freqs)\n", "\n", " ax1.xaxis.tick_top()\n", " [label.set_visible(False) for label in ax1.get_xticklabels()]\n", " \n", " return fig, axes" ] }, { "cell_type": "code", "execution_count": 218, "metadata": {}, "outputs": [], "source": [ "def phase_modulo(phase):\n", " \"\"\"\n", " Modulo phase such that it falls within the interval [\\pi, \\pi)\n", " \"\"\"\n", "\n", " return (phase + np.pi) % (2*np.pi) - np.pi" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Phase information in the Fourier Transform\n", "\n", "$$\n", "u(t) = sin(2\\pi f t + \\varphi_t)\n", "$$\n", "\n", "Define $f_\\mathrm{max}$ as the frequency with the highest power in the FT (it should be close to $f$).\n", "Then $\\varphi_f$ is its associated phase." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Required signal length is: 0.005s\n", "Required number of samples: 50.0\n" ] } ], "source": [ "sample_rate = 1/1e-4 # Hz\n", "f = 200 # Hz\n", "required_N_samples = sample_rate/f\n", "\n", "signal_func = lambda phase: np.sin(phase)\n", "\n", "# set signal_func to exp(i*phi)\n", "if False:\n", " signal_func = lambda phase: np.exp(1j*phase)\n", "\n", "print(\"Required signal length is: {}s\".format(1/f))\n", "print(\"Required number of samples: {}\".format(required_N_samples))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### $\\varphi_f$ vs $f_\\mathrm{max}$ for differing $\\Delta f$" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# \\phi_f vs f_max for differing \\Delta f\n", "N_delta_f = 200\n", "\n", "plot_submax = True\n", "\n", "\n", "Ns_samples = required_N_samples//1 + np.arange(0, N_delta_f)\n", "phi_f = np.empty(N_delta_f)\n", "f_max = np.empty(N_delta_f)\n", "\n", "if plot_submax:\n", " phi_f_sub = np.empty(N_delta_f)\n", " f_submax = np.empty(N_delta_f)\n", "\n", "for i, N_sample in enumerate(Ns_samples):\n", " time = np.arange(N_sample) / sample_rate\n", " \n", " fft, freqs = ft_spectrum(signal_func(2*np.pi*f*time), sample_rate)\n", " \n", " fft_power = np.abs(fft)**2\n", " id_max = np.argmax(fft_power)\n", " \n", " phi_f[i] = np.angle(fft[id_max])\n", " f_max[i] = freqs[id_max]\n", " \n", " if plot_submax:\n", " fft_power[id_max] = 0\n", " id_submax = np.argmax( fft_power )\n", " \n", " phi_f_sub[i] = np.angle(fft[id_submax])\n", " f_submax[i] = freqs[id_submax]\n", "\n", "if plot_submax:\n", " fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2,2, figsize=(16,8), sharex=\"col\")\n", " fig.suptitle(\"Maximum (and sub maximum) Power frequencies and their phase\")\n", "else:\n", " fig, (ax1, ax2) = plt.subplots(1,2, figsize=(16,4))\n", " fig.suptitle(\"Maximum Power frequencies and their phase\")\n", " \n", " \n", "# Maximum values\n", "ax1.set_xlabel('$f_\\\\mathrm{max}$')\n", "ax1.set_ylabel('$\\\\varphi_f$')\n", "ax1.plot(f_max, phi_f, '--', alpha=0.1)\n", "sc = ax1.scatter(f_max, phi_f, c=Ns_samples, cmap='Spectral')\n", "ax1.axvline(f, color='r', alpha=0.5, label=\"Signal frequency\")\n", "for hline in [0, -np.pi/2]:\n", " ax1.axhline(hline, color='k', alpha=0.5)\n", "\n", "ax2.set_xlabel('$N_\\\\mathrm{samples}$')\n", "ax2.set_ylabel('$f_\\\\mathrm{max}$')\n", "ax2.scatter(Ns_samples, f_max, c=Ns_samples, cmap='Spectral')\n", "ax2.axhline(f, color='r', alpha=0.5, label=\"Signal frequency\")\n", "\n", "# SubMaximum values\n", "if plot_submax:\n", " \n", " # filter submax frequencies above twice the frequency\n", " if True:\n", " idx_submax = np.argwhere(np.abs(f_submax) < 2*f)\n", " \n", " f_submax = f_submax[idx_submax]\n", " phi_f_sub = phi_f_sub[idx_submax]\n", " \n", " Ns_samples_submax = Ns_samples[idx_submax]\n", " else:\n", " Ns_samples_submax = Ns_samples\n", " \n", " \n", " ax3.set_xlabel('$f_\\\\mathrm{submax}$')\n", " ax3.set_ylabel('$\\\\varphi_{f\\_sub}$')\n", " ax3.plot(f_submax, phi_f_sub, '--', alpha=0.1)\n", " sc = ax3.scatter(f_submax, phi_f_sub, c=Ns_samples_submax, cmap='Spectral')\n", " ax3.axvline(f, color='r', alpha=0.5, label=\"Signal frequency\")\n", " for hline in [0, -np.pi/2]:\n", " ax3.axhline(hline, color='k', alpha=0.5)\n", "\n", " ax4.set_xlabel('$N_\\\\mathrm{samples}$')\n", " ax4.set_ylabel('$f_\\\\mathrm{submax}$')\n", " ax4.scatter(Ns_samples_submax, f_submax, c=Ns_samples_submax, cmap='Spectral')\n", " ax4.axhline(f, color='r', alpha=0.5, label=\"Signal frequency\")\n", "\n", "\n", "\n", "if False:\n", " res = 50\n", " ax1.set_xlim(f-res, f+res)\n", " ax2.set_ylim(f-res, f+res)\n", " if plot_submax:\n", " ax4.set_ylim(f-res, f+res)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## $\\varphi_f$ vs $\\varphi_t$ and the effect of $f/f_\\mathrm{sample}$" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sample_rate = 1/1e-4 # Hz\n", "\n", "phase_offsets = np.linspace(-np.pi, np.pi, 500, endpoint=True)# rad\n", "\n", "frequencies = sample_rate * np.array([0.5, 0.49, 0.45, 0.3, 0.28, 0.25, 0.05, 0.001])\n", "\n", "signal_func = lambda phase: np.sin(phase)\n", "\n", "\n", "# Precreate figure and axis\n", "fig, (ax1) = plt.subplots(1,1, figsize=(16,4))\n", "\n", "for f in frequencies[::-1]:\n", " \n", " required_N_samples = sample_rate/f\n", "\n", " phi_f = np.empty_like(phase_offsets)\n", "\n", " time = np.arange(required_N_samples) / sample_rate\n", "\n", " for i, offset in enumerate(phase_offsets):\n", "\n", " fft, freqs = ft_spectrum(signal_func(2*np.pi*f*time + offset), sample_rate) \n", " id_max = np.argmax(np.abs(fft)**2)\n", "\n", " phi_f[i] = np.angle(fft[id_max])\n", " \n", " \n", " ax1.plot(phase_offsets, phi_f, '.--', label=\"$f/f_\\\\mathrm{{sample}} = {}$\".format(f/sample_rate))\n", "\n", " if True:\n", " id_phi_f_min = np.argmin(phi_f)\n", " ylocation = (np.max(phi_f) + np.min(phi_f)) /2\n", " ax1.text(phase_offsets[id_phi_f_min], ylocation, \"${:.2g}\\\\pi$\".format(phase_offsets[id_phi_f_min]/np.pi), horizontalalignment='center')\n", "\n", " \n", "ax1.set_title(\"Frequencydomain phase of maximum amplitude frequency $\\\\varphi_f$ \\n vs Timedomain phase $\\\\varphi_t$ with varying $f / f_\\\\mathrm{{sample}}$\")\n", "ax1.set_xlabel('$\\\\varphi_t$')\n", "ax1.set_ylabel('$\\\\varphi_f$')\n", "ax1.legend(loc='lower right')\n", "\n", "# grid lines\n", "## vertical lines\n", "vlines = [\n", " (-np.pi, r'$-\\pi$'),\n", " (-np.pi/np.sqrt(2), r'$\\frac{-\\pi}{\\sqrt{2}}$'),\n", " (-np.pi/np.sqrt(3), r'$\\frac{-\\pi}{\\sqrt{3}}$'),\n", " (-np.pi/2, r'$\\frac{-\\pi}{2}$'),\n", " (np.pi, r'$\\pi$'),\n", "]\n", "\n", "xtrans = ax1.get_xaxis_transform()\n", "ax1.axhline(0, alpha=0.1, color='k')\n", "for location, label in vlines:\n", " ax1.axvline(location, alpha=0.1, color='k')\n", " ax1.text(location, -0.06, label, transform=xtrans, horizontalalignment='center')\n", "\n", "## horizontal lines\n", "hlines = [\n", " (1, ''),\n", " (-2, ''),\n", " (-np.pi/2, r'$\\frac{-\\pi}{2}$'),\n", " (np.pi/2, r'$\\frac{\\pi}{2}$'),\n", "]\n", "\n", "ytrans = ax1.get_yaxis_transform()\n", "ax1.axvline(0, alpha=0.1, color='k')\n", "for location, label in hlines:\n", " ax1.axhline(location, alpha=0.1, color='k')\n", " ax1.text(-0.03, location, label, transform=ytrans, verticalalignment='center')\n", " \n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "For $f_\\mathrm{sample} \\geq 3f$ the relationship between $\\varphi_t$ and $\\varphi_f$ is (almost) linear.\n", "\n", "From $f_\\mathrm{sample} \\geq 4f$ onwards, this relationship is stable with\n", "\n", "$$\n", "\\varphi_f = \\varphi_t - \\frac{\\pi}{2} \\delta_\\mathrm{sin}\n", ",\n", "$$\n", "where $\\delta_\\mathrm{sin}$ is 1 if the signal was a sine, and 0 for a cosine." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# reconstruct phase from off-frequency ft" ] }, { "cell_type": "code", "execution_count": 273, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Required signal length is: 0.0004s\n", "Required number of samples: 4.0\n", "Phase to be retrieved: -1.5707963267948966\n" ] } ], "source": [ "sample_rate = 1/1e-4 # Hz\n", "f = 2500 # Hz\n", "required_N_samples = sample_rate/f\n", "\n", "phase_to_retrieve = phase_modulo(-np.pi/2)\n", "signal_func = lambda phase: np.cos(phase + phase_to_retrieve)\n", "\n", "print(\"Required signal length is: {}s\".format(1/f))\n", "print(\"Required number of samples: {}\".format(required_N_samples))\n", "print(\"Phase to be retrieved: {}\".format(phase_to_retrieve))" ] }, { "cell_type": "code", "execution_count": 282, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "3000.0 -2.199114857512855\n", "3000.0 -0.9424777960769379\n", "3000.0 -3.141592653589793\n", "2500.0 -1.5707963267948961\n", "2500.0 -1.5707963267948966\n", "2500.0 -3.141592653589793\n", "2142.857142857143 -0.8975979010256547\n", "2142.857142857143 0.8975979010256534\n", "2142.857142857143 0.0\n", "1875.0 0.3755285390725924\n", "1875.0 -2.628699773508142\n", "1875.0 -2.25317123443555\n", "-1.5707963267948966\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "N_deltas = np.arange(1, required_N_samples+1, 1) # set !={0, required_N_sample} for imperfect FT\n", "\n", "fig, axes = plt.subplots(1,2, figsize=(16,4))\n", "\n", "\n", "N_sub = 2 # how many peaks to get\n", "retrieved_phases = np.empty_like(N_deltas)\n", "\n", "for i, N_delta in enumerate(N_deltas):\n", " time = np.arange(required_N_samples+N_delta) / sample_rate\n", "\n", " fft, freqs = ft_spectrum(signal_func(2*np.pi*f*time), sample_rate)\n", "\n", " fft_power = np.abs(fft)**2\n", "\n", " idx_max = np.empty(N_sub, dtype=np.int)\n", " for sub in range(len(idx_max)):\n", " idx = np.argmax(fft_power)\n", " idx_max[sub] = idx\n", " tmp = fft_power[idx]\n", " fft_power[idx] = 0\n", "\n", " # select only the top two frequencies\n", " idx_top = idx_max[:2]\n", "\n", " plot_freqs = freqs[idx_top]\n", " angles = np.angle(fft[idx_top])\n", "\n", " # fold angles down for higher submax frequencies\n", " if True:\n", " folds = 0\n", " for j in range(len(plot_freqs)-1):\n", " if plot_freqs[j] < plot_freqs[j+1] and angles[j] < angles[j+1]:\n", " folds += 1\n", " angles[j+1] -= 2*np.pi*folds\n", "\n", " if False:\n", " print(plot_freqs[j], \"\\t\", plot_freqs[j+1], \"\\t|\", folds, \"\\t|\", angles[j], angles[j+1])\n", "\n", " # plot frequencies and angles\n", " axes[0].plot(plot_freqs, angles, '--', alpha=0.5, label=r'$\\Delta N = {}$'.format(N_delta))\n", " sc = axes[0].scatter(plot_freqs, angles, c=np.arange(len(plot_freqs),0, -1), cmap='Spectral')\n", " \n", " # find interpolation between peaks to get the original phase\n", " dphi_df = (angles[0]-angles[1])/(plot_freqs[0]-plot_freqs[1])\n", " offset = angles[0] + dphi_df * plot_freqs[0]\n", " \n", " phase_at_f = dphi_df * f + offset\n", "\n", " # modulo phase\n", " phase_at_f = phase_modulo(phase_at_f)\n", " \n", " retrieved_phases[i] = phase_at_f\n", " \n", " axes[0].plot(f, phase_at_f, 'g^')\n", " \n", " # Try to fix the midpoints of each line\n", " freq_midpoint = (plot_freqs[0]-plot_freqs[1])/2 + plot_freqs[1]\n", " angle_midpoint = phase_modulo((angles[0]-angles[1])/2 + angles[1])\n", " axes[0].plot(freq_midpoint, angle_midpoint, '+')\n", " \n", " print(freq_midpoint, angle_midpoint)\n", " print(freq_midpoint, phase_modulo(dphi_df*freq_midpoint + offset))\n", " print(freq_midpoint, phase_modulo(angle_midpoint - dphi_df*freq_midpoint + offset))\n", " \n", "# plot retrieved phases\n", "axes[1].plot(N_deltas, retrieved_phases, '.--')\n", "\n", "cbar = fig.colorbar(sc, ax=axes[0])\n", "cbar.ax.set_ylabel(\"Power ordering\")\n", "\n", "## horizontal lines\n", "hlines = [\n", " (0, None),\n", " (-np.pi/2, r'$\\frac{-\\pi}{2}$'),\n", "]\n", "\n", "ytrans = axes[0].get_yaxis_transform()\n", "for location, label in hlines:\n", " axes[0].axhline(location, alpha=0.1, color='k')\n", " axes[0].text(-0.06, location, label, transform=ytrans, verticalalignment='center')\n", " \n", "axes[0].plot(f, phase_to_retrieve, 'r*')\n", "print(phase_to_retrieve)\n", "axes[0].set_xlabel(\"$f$\")\n", "axes[0].set_ylabel(r\"$\\varphi_f$\")\n", "axes[0].axvline(f, alpha=0.1)\n", "#fig.legend(loc='center left')\n", "\n", "\n", "\n", "axes[1].set_xlabel(r\"$\\Delta N$\")\n", "axes[1].set_ylabel(r\"$\\varphi_f$\")\n", "axes[1].axhline(phase_to_retrieve, alpha=0.1)\n", "\n", "\n", "if False:\n", " res=200\n", " axes[0].set_xlim(f-res, f+res)\n", " axes[0].set_ylim(-2,+0.5)\n", "\n", "plt.show()\n" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.6" } }, "nbformat": 4, "nbformat_minor": 4 }