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add interface to load pre-binned bias series into the processor and a…
…dd example notebook to use the energy calibrator workflow with FLASH data
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,206 @@ | ||
| { | ||
| "cells": [ | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "39b2e62a", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "%load_ext autoreload\n", | ||
| "%autoreload 2\n", | ||
| "\n", | ||
| "from sed import SedProcessor\n", | ||
| "import sed\n", | ||
| "import numpy as np\n", | ||
| "\n", | ||
| "# %matplotlib inline\n", | ||
| "%matplotlib widget\n", | ||
| "import matplotlib.pyplot as plt" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "4d78d236", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "# Try to calibrate energy" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "a62f084f", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "## Spin-integrated branch, E_TOF=10eV\n", | ||
| "single scan, move sample bias manually every 2000 pulses." | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "7dabbe92", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "sp = SedProcessor(runs=[44638], config=\"config_flash_energy_calib.yaml\", system_config={})" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "248a41a7", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "sp.add_jitter()" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "2b867e40", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "axes = ['sampleBias', 'dldTime']\n", | ||
| "bins = [6, 500]\n", | ||
| "ranges = [[0,6], [40000, 55000]]\n", | ||
| "res = sp.compute(bins=bins, axes=axes, ranges=ranges)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "62081458", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "sp.load_bias_series(binned_data=res)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "424af94e", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "ranges=(44500, 46000)\n", | ||
| "ref_id=3\n", | ||
| "sp.find_bias_peaks(ranges=ranges, ref_id=ref_id)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "034eff42", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "ref_id=3\n", | ||
| "ref_energy=-.3\n", | ||
| "sp.calibrate_energy_axis(ref_id=ref_id, ref_energy=ref_energy, method=\"lstsq\", order=3)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "bbbfe992", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "ref_id=3\n", | ||
| "ref_energy=-.3\n", | ||
| "sp.calibrate_energy_axis(ref_id=ref_id, ref_energy=ref_energy, method=\"lmfit\")" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "e14d6cef", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "sp.append_energy_axis(preview=True)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "59c83544", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "axes = ['sampleBias', 'energy']\n", | ||
| "bins = [6, 1000]\n", | ||
| "ranges = [[0,6], [-5, 5]]\n", | ||
| "res = sp.compute(bins=bins, axes=axes, ranges=ranges)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "addba4cb", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "plt.figure()\n", | ||
| "res[3,:].plot()" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "1676ec57", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "axes = ['sampleBias', 'energy', 'dldPosX']\n", | ||
| "bins = [6, 100, 480]\n", | ||
| "ranges = [[0,6], [-2, 1], [420,900]]\n", | ||
| "res = sp.compute(bins=bins, axes=axes, ranges=ranges)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "ad199c40", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "plt.figure()\n", | ||
| "res[3, :, :].plot()" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "3a4ae88c", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [] | ||
| } | ||
| ], | ||
| "metadata": { | ||
| "kernelspec": { | ||
| "display_name": ".pyenv", | ||
| "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": "3.8.12" | ||
| } | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 5 | ||
| } |
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