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Merge pull request #257 from European-XFEL/dev
0.9.1
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‎README.md‎

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@@ -13,9 +13,9 @@ EXtra-foam
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![Overview](docs/images/extra_foam_0.9.0.jpg)
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*EXtra-foam* (previously known as *[karaboFAI](https://in.xfel.eu/readthedocs/docs/karabofai/en/latest/)*) is a
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framework that provides super fast on-line (real-time) and off-line data analysis and visualization for
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experiments at European XFEL that using 2D detectors (e.g. AGIPD, DSSC, LPD, ePix100, FastCCD, JungFrau,
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etc.), together with other 1D detectors (e.g. XGM, digitizer, etc.) and various control data.
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*EXtra-foam* is a framework that provides real-time and off-line data analysis (**detector geometry**,
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**pump-probe**, **azimuthal integration**, **ROI**, **statistics**, etc.) and visualization for experiments
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that use **2D area detectors** (*AGIPD*, *LPD*, *DSSC*, *FastCCD*, *JungFrau*, *ePix100*, etc.) and
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**1D detectors** (*Gotthard*, *XGM*, *digitizer*, etc.) at European XFEL.
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[Documentation](https://extra-foam.readthedocs.io/en/latest/)

‎benchmarks/azimuthal_integration.ipynb‎

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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# EXtra-foam azimuthal integration benchmark"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import os.path as osp\n",
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"\n",
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"import numpy as np\n",
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"from pyFAI.azimuthalIntegrator import AzimuthalIntegrator as PyfaiAzimuthalIntegrator\n",
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"from scipy.signal import find_peaks\n",
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"import matplotlib.pyplot as plt\n",
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"\n",
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"import extra_foam\n",
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"print(extra_foam.__version__)\n",
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"\n",
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"from extra_foam.algorithms import AzimuthalIntegrator, ConcentricRingsFinder\n",
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"from extra_foam.algorithms import mask_image_data"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"def load_image(filepath):\n",
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" img = np.load(osp.join(osp.expanduser('~'), filepath))\n",
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" mask = np.zeros_like(img, dtype=bool)\n",
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" mask_image_data(img, out=mask)\n",
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" _, ax = plt.subplots(figsize=(12, 12))\n",
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" ax.imshow(img)\n",
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" \n",
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" return img, mask\n",
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"\n",
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"# img, mask = load_image(\"jf_ring.npy\")\n",
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"img, mask = load_image(\"jf_ring_6modules.npy\")\n",
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"# img, mask = load_image(\"lpd.npy\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"dist = 1 # sample distance\n",
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"npt = 1024 # number of integration points\n",
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"pixel1, pixel2 = 0.75e-6, 0.75e-6 # pixel size (y, x)\n",
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"cy, cx = 537, 1132 \n",
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"poni1, poni2 = cy * pixel1, cx * pixel2 # integration center (y, x)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# %%timeit\n",
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"\n",
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"pyfai_integrator = PyfaiAzimuthalIntegrator(\n",
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" dist=dist, poni1=poni1, poni2=poni2, pixel1=pixel1, pixel2=pixel2, wavelength=1e-10)\n",
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"\n",
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"q_gt, I_gt = pyfai_integrator.integrate1d(img, npt, mask=mask, unit=\"q_A^-1\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# %%timeit\n",
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"\n",
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"integrator = AzimuthalIntegrator(\n",
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" dist=dist, poni1=poni1, poni2=poni2, pixel1=pixel1, pixel2=pixel2, wavelength=1e-10)\n",
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"\n",
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"q, I = integrator.integrate1d(img, npt=npt)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"_, ax = plt.subplots(figsize=(12, 6))\n",
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"\n",
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"ax.plot(1e-10 * q, I, '-', label='EXtra-foam')\n",
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"ax.plot(q_gt, I_gt, '--', label='pyFAI')\n",
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"ax.set_xlabel(\"q (1/A)\", fontsize=16)\n",
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"ax.set_ylabel(\"I (arb.)\", fontsize=16)\n",
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"ax.legend(fontsize=16)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# %%timeit\n",
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"\n",
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"min_count = 500\n",
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"prominence = 100\n",
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"distance = 10\n",
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"\n",
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"finder = ConcentricRingsFinder(pixel2, pixel1)\n",
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"cx, cy = finder.search(img, cx, cy, min_count=min_count)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"q, s = finder.integrate(img, cx, cy, min_count=min_count)\n",
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"\n",
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"i_peaks = find_peaks(s, distance=distance, prominence=prominence)[0]\n",
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"\n",
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"_, ax = plt.subplots(figsize=(12, 6))\n",
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"\n",
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"ax.plot(q, s, '-')\n",
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"ax.plot(q[i_peaks], s[i_peaks], 'x')\n",
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"ax.set_xlabel(\"Radial (pixel)\", fontsize=16)\n",
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"ax.set_ylabel(\"I (arb.)\", fontsize=16)\n",
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"\n",
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"print(\"Optimized cx = \", cx, \", cy = \", cy)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "foam-gcc6",
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"language": "python",
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"name": "foam-gcc6"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.6"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}

‎benchmarks/gui/benchmark_imageview.py‎

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All rights reserved.
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"""
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import time
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from collections import deque
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import numpy as np
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class BenchmarkImageViewSpeed:
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def __init__(self):
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self._dt = deque(maxlen=60)
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self._timer = QTimer()
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self._timer.timeout.connect(self.update)
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self._count += 1
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now = time.time()
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dt = now - self._prev_t
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self._dt.append(now - self._prev_t)
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self._prev_t = now
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fps = 1.0/dt
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fps = len(self._dt) / sum(self._dt)
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self._view.setTitle(f"{fps:.2f} fps")
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‎benchmarks/gui/benchmark_plotwidget.py‎

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"""
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import time
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from enum import IntEnum
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from collections import deque
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import numpy as np
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class BenchmarkPlotItemSpeed:
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def __init__(self, plot_type=PlotType.Line):
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self._dt = deque(maxlen=60)
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self._timer = QTimer()
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self._timer.timeout.connect(self.update)
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# self._timer.singleShot(1, self.update)
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self._widget = PlotWidgetF()
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self._widget.addLegend()
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if plot_type == PlotType.Line:
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self._graph = self._widget.plotCurve()
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self._graph = self._widget.plotCurve(name='line')
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n_pts = 5000
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elif plot_type == PlotType.Bar:
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self._graph = self._widget.plotBar()
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self._graph = self._widget.plotBar(name='bar')
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n_pts = 300
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elif plot_type == PlotType.StatisticsBar:
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self._graph = self._widget.plotStatisticsBar()
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self._graph = self._widget.plotStatisticsBar(name='statistics bar')
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self._graph.setBeam(1)
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n_pts = 500
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elif plot_type == PlotType.Scatter:
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self._graph = self._widget.plotScatter()
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n_pts = 3000
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self._graph = self._widget.plotScatter(name='scatter')
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n_pts = 5000
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else:
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raise ValueError(f"Unknown plot type: {plot_type}")
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now = time.time()
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dt = now - self._prev_t
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self._dt.append(now - self._prev_t)
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self._prev_t = now
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fps = 1.0 / dt
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fps = len(self._dt) / sum(self._dt)
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self._widget.setTitle(f"{fps:.2f} fps")
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app.processEvents() # force complete redraw for every plot
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if __name__ == '__main__':
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bench = BenchmarkPlotItemSpeed(PlotType.Line)
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bench = BenchmarkPlotItemSpeed(PlotType.Scatter)
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bench.start()
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app.exec_()

‎docs/changelog.rst‎

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CHANGELOG
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=========
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0.9.1 (15 July 2020)
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------------------------
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- **Bug Fix**
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- Fix transform type update in TransformView in ImageTool. #251
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- **Improvement**
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- PlotItem will not be shown in legend if its name is empty. #254
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- Improve y2-axis plot implementation. #253
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- Improve stack detector modules. #247
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- Implement ScatterPlotItem to replace the pyqtgraph one. #238
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- **New Feature**
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- Implement curve fitting in correlation window. #255
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- Implement azimuthal integration and concentric ring detection in C++. #252
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0.9.0 (30 June 2020)
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------------------------
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