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Diffstat (limited to 'generate_compensated_2_tone_file.ipynb')
| -rw-r--r-- | generate_compensated_2_tone_file.ipynb | 291 |
1 files changed, 0 insertions, 291 deletions
diff --git a/generate_compensated_2_tone_file.ipynb b/generate_compensated_2_tone_file.ipynb deleted file mode 100644 index 7037d3b..0000000 --- a/generate_compensated_2_tone_file.ipynb +++ /dev/null @@ -1,291 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "%matplotlib inline\n", - "import matplotlib.pyplot as plt\n", - "import numpy as np" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "a = np.fromfile(\"./out_sin\", np.complex64)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "a.shape" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "a = a[0:100]" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "mag = np.abs(a)\n", - "plt.plot(mag)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "plt.plot(a.imag[0:100])" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "plt.plot(a.real[0:100])" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def complex_exp(freq, samp_rate, periods, phase_deg=0):\n", - " t_max = 1.0 * samp_rate / freq * periods\n", - " t = np.arange(t_max)\n", - " fac = t / samp_rate * freq\n", - " phase = 1j * phase_deg/360*2*np.pi\n", - " ret = np.exp(phase + 1j * 2 * np.pi * fac - 1j * np.pi / 2, dtype=np.complex64)\n", - " return ret\n", - "ret = complex_exp(10,40,2)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "samp_rate = 4000000 #samples / second\n", - "frequency_0 = samp_rate/9. #cycles / second\n", - "frequency_1 = samp_rate/10. #cycles / second\n", - "tone_0 = complex_exp(frequency_0, samp_rate, 10, 180)\n", - "tone_1 = complex_exp(frequency_1, samp_rate, 9)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def complex_exp(freq, samp_rate, periods):\n", - " t_max = 1.0 * samp_rate / freq * periods\n", - " t = np.arange(t_max)\n", - " fac = t / samp_rate * freq\n", - " ret = np.exp(1j * 2 * np.pi * fac - 1j * np.pi / 2)\n", - " return ret\n", - "ret = complex_exp(10,40,2)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "two_tone = 1/2.0 * (tone_0 + tone_1)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "two_tone[-1]" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "two_tone.tofile(\"./np_twotone\")\n", - "two_tone.dtype" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "a_load = np.fromfile(\"./np_twotone\", dtype=np.complex64)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "plt.plot(a_load.real[0:100])" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "import pickle" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "lut_dict = pickle.load(open(\"./lut_tab.pkl\", \"rb\"))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def dpd(x):\n", - " mag = np.abs(x)\n", - " fac = np.interp(mag/2.0, lut_dict[\"ampl\"], lut_dict[\"fac\"])\n", - " ret = x*fac\n", - " return ret.astype(np.complex64)\n", - "\n", - "#def dpd(x):\n", - "# return x*0.5" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "tone_0_dpd = np.apply_along_axis(dpd, 0, tone_0)\n", - "tone_1_dpd = np.apply_along_axis(dpd, 0, tone_1)\n", - "two_tone_dpd = 1/2. * (tone_0_dpd + tone_1_dpd)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "plt.plot(two_tone_dpd.real[0:200])\n", - "plt.plot(two_tone.real[0:200])" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "two_tone_dpd.tofile(\"./np_twotone\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "two_tone.tofile(\"./np_twotone\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "a_load = np.fromfile(\"./np_twotone_dpd\", dtype=np.complex64)\n", - "plt.plot(a_load.real[0:200])" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 2", - "language": "python", - "name": "python2" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 2 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython2" - } - }, - "nbformat": 4, - "nbformat_minor": 1 -} |