{ "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": 3, "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": 4, "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": 5, "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": 6, "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 max-power 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\n", "\n", "Require atleast $f_\\mathrm{sample} \\geq 4 f$" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Required signal length is: 0.001s\n", "Required number of samples: 10.0\n", "Phase to be retrieved: -1.5707963267948966\n" ] } ], "source": [ "sample_rate = 1/1e-4 # Hz\n", "f = 100 # 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": 8, "metadata": {}, "outputs": [ { "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", "\n", "# flags\n", "unfold_phases = True\n", "N_sub_max = 2 # how many peaks to get\n", "enable_single_max = True\n", "continue_on_single_max = True\n", "keep_single_max_phase = True\n", "\n", "\n", "\n", "retrieved_phases = np.empty_like(N_deltas)\n", "fig, axes = plt.subplots(1,2, figsize=(16,4))\n", "\n", "for i, N_delta in enumerate(N_deltas):\n", " # require N_sub => 2\n", " N_sub_max = max(2, N_sub_max)\n", " idx_max = np.empty(N_sub_max, dtype=np.int)\n", "\n", " time = np.arange(required_N_samples+N_delta) / sample_rate\n", " \n", " f_delta = sample_rate/(required_N_samples+N_delta)\n", "\n", " fft, ft_freqs = ft_spectrum(signal_func(2*np.pi*f*time), sample_rate)\n", " fft_power = np.abs(fft)**2\n", " \n", "\n", " idx_single_max = None\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 # mask current fft power\n", " \n", " if f_delta < np.abs(ft_freqs[idx] - f):\n", " idx_single_max = idx\n", " continue\n", "\n", " # No use to interpolate when the max-amplitude frequency\n", " # is within the frequency resolution of f\n", " if enable_single_max and idx_single_max is not None:\n", " freqs = ft_freqs[idx_single_max]\n", " angles = np.angle(fft[idx_single_max])\n", " \n", " if keep_single_max_phase:\n", " retrieved_phases[i] = angles\n", " \n", " l = axes[0].plot(freqs, angles, '1', label=r'$\\Delta N = {}$'.format(N_delta))\n", " \n", " axes[1].plot(N_delta/required_N_samples, angles, '1', color=l[0].get_color())\n", "\n", " if continue_on_single_max:\n", " continue\n", " \n", " freqs = ft_freqs[idx_max]\n", " angles = np.angle(fft[idx_max])\n", "\n", " # fold angles down for higher submax frequencies\n", " if unfold_phases:\n", " folds = 0\n", " for j in range(len(freqs) - 1):\n", " if freqs[j] < 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(freqs[j], freqs[j+1], \"\\t|\", folds, \"\\t|\", angles[j], angles[j+1])\n", "\n", "\n", "\n", " # plot frequencies and angles\n", " axes[0].plot(freqs, angles, '--', alpha=0.5, label=r'$\\Delta N = {}$'.format(N_delta))\n", " sc = axes[0].scatter(freqs, angles, c=np.arange(len(freqs),0, -1), cmap='Spectral')\n", " \n", " # find interpolation between peaks to get the original phase\n", " dphi_df = (angles[0]-angles[1])/(freqs[0]-freqs[1])\n", " offset = angles[1] - dphi_df * freqs[1]\n", " \n", " angle_at_f = dphi_df * f + offset\n", "\n", " # modulo phase\n", " if not unfold_phases:\n", " angle_at_f = phase_modulo(angle_at_f)\n", " \n", " retrieved_phases[i] = angle_at_f\n", " axes[0].plot(f, angle_at_f, 'g^')\n", " \n", " # Try to fix the midpoints of each line\n", " if False:\n", " freq_midpoint = (freqs[0]-freqs[1])/2 + freqs[1]\n", " angle_midpoint = (angles[0]-angles[1])/2 + angles[1]\n", " interp_angle_midpoint = dphi_df*freq_midpoint + offset\n", " \n", " # modulo phase\n", " if not unfold_phases:\n", " angle_midpoint = phase_modulo(angle_midpoint)\n", " interp_angle_midpoint = phase_modulo(interp_angle_midpoint)\n", " \n", " l = axes[0].plot(freq_midpoint, angle_midpoint, '+')\n", " axes[0].plot(freq_midpoint, interp_angle_midpoint, 'x', color=l[0].get_color())\n", " \n", " \n", "# plot retrieved phases\n", "axes[1].plot(N_deltas/required_N_samples, phase_modulo(retrieved_phases), '.--')\n", "\n", "cbar = fig.colorbar(sc, ax=axes[0])\n", "cbar.ax.set_ylabel(\"Power ordering\")\n", "cbar.set_ticks([sc.colorbar.vmin, sc.colorbar.vmax])\n", "\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", "axes[0].set_xlabel(\"$f$\")\n", "axes[0].set_ylabel(r\"$\\varphi_f$\")\n", "axes[0].axvline(f, alpha=0.1)\n", "\n", "\n", "\n", "axes[1].set_xlabel(r\"$\\Delta N / N_\\mathrm{required}$\")\n", "axes[1].set_ylabel(r\"$\\varphi_f$\")\n", "axes[1].axhline(phase_to_retrieve, alpha=0.1, color='r')\n", "\n", "# zooming\n", "if True:\n", " x_res = 100\n", " y_min = -2\n", " y_max = 0.5\n", " \n", " if True:\n", " x_res = 0.3\n", " y_min = phase_to_retrieve - 0.1\n", " y_max = phase_to_retrieve + 0.1\n", "\n", " axes[0].set_xlim(f-x_res, f+x_res)\n", " axes[0].set_ylim(y_min, y_max)\n", " \n", "\n", "plt.show()" ] } ], "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 }