{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Nexus -> CBF #\n", "In this tutorial we will see how to export a Nexus archive produced by the Eiger detector from Dectris into a bunch of CBF files, similar to the one generated by Pilatus detectors, using the FabIO library to write images (and h5py which actually reads them).\n", "\n", "**Nota:** HDF5 files produced by Nexus detector use a specific LZ4/bitshuffle plugin for reading/writing. They require recent version of hdf5 (>= 1.8.10 ), h5py (>= 2.5.0) and those plugins installed:\n", "\n", "* https://github.com/nexusformat/HDF5-External-Filter-Plugins/tree/master/LZ4 \n", "* https://github.com/kiyo-masui/bitshuffle\n", "\n", "Under Windows, those plugins can easily be installed via this repository which provides binary DLLs: \n", "https://github.com/silx-kit/hdf5plugin\n", "\n" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": false }, "outputs": [], "source": [ "#Run as first to set the plugin path, very important to handle Eiger data:\n", "import os\n", "os.environ[\"HDF5_PLUGIN_PATH\"]=\"/usr/lib/x86_64-linux-gnu/hdf5/plugins\"" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": false }, "outputs": [], "source": [ "import fabio" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In this example we will use the Eiger 4M dataset which can be obtained from Dectris: \n", "https://www.dectris.com/datasets.html. You may register to get download access." ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Eiger dataset with 1800 frames from collect_01_00001_master.h5\n" ] } ], "source": [ "images = fabio.open(\"collect_01_00001_master.h5\")\n", "print(images)" ] }, { "cell_type": "markdown", "metadata": { "collapsed": false }, "source": [ "Each \"EigerImage\" object contains a list to the corresponding HDF5 opened with h5py.\n", "So one can retrieve all metadata associated:" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "beam_center_x: 1051.0\n", "beam_center_y: 1001.0\n", "bit_depth_readout: 32\n", "count_time: 0.099996\n", "countrate_correction_applied: 0\n", "description: b'Dectris Eiger 4M'\n", "detectorSpecific: unprintable\n", "detector_distance: 0.00733\n", "detector_number: b'E-08-0102'\n", "detector_readout_time: 3.78e-06\n", "efficiency_correction_applied: 0\n", "flatfield_correction_applied: 1\n", "frame_time: 0.1\n", "geometry: unprintable\n", "pixel_mask_applied: 0\n", "sensor_material: b'Si'\n", "sensor_thickness: 0.00032\n", "threshold_energy: 5635.65\n", "virtual_pixel_correction_applied: 1\n", "x_pixel_size: 7.5e-05\n", "y_pixel_size: 7.5e-05\n" ] } ], "source": [ "header = {}\n", "for key, value in images.h5[\"entry/instrument/detector\"].items():\n", " try:\n", " val = value[()]\n", " except:\n", " print(\"%s: unprintable\"%key)\n", " else:\n", " print(\"%s: %s\"%(key, val))\n", " header[key] = val\n", " " ] }, { "cell_type": "markdown", "metadata": { "collapsed": false }, "source": [ "Now we can translate every single image into a CBF file, here we do only a dozen of then:" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "collect_01_00001_0000.cbf\n", "collect_01_00001_0001.cbf\n", "collect_01_00001_0002.cbf\n", "collect_01_00001_0003.cbf\n", "collect_01_00001_0004.cbf\n", "collect_01_00001_0005.cbf\n", "collect_01_00001_0006.cbf\n", "collect_01_00001_0007.cbf\n", "collect_01_00001_0008.cbf\n", "collect_01_00001_0009.cbf\n", "collect_01_00001_0010.cbf\n", "collect_01_00001_0011.cbf\n" ] } ], "source": [ "for idx, frame in enumerate(images):\n", " cbf = fabio.cbfimage.cbfimage(header=header,data=frame.data)\n", " fname = \"collect_01_00001_%04i.cbf\"%idx\n", " cbf.write(fname)\n", " print(fname)\n", " if idx>10: \n", " break" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This is how to display an image using the notebook backend: " ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Populating the interactive namespace from numpy and matplotlib\n" ] } ], "source": [ "%pylab nbagg" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "collapsed": false }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/scisoft/users/jupyter/jupy34/lib/python3.4/site-packages/ipykernel/__main__.py:1: RuntimeWarning: divide by zero encountered in log\n", " if __name__ == '__main__':\n" ] }, { "data": { "application/javascript": [ "/* Put everything inside the global mpl namespace */\n", "window.mpl = {};\n", "\n", "mpl.get_websocket_type = function() {\n", " if (typeof(WebSocket) !== 'undefined') {\n", " return WebSocket;\n", " } else if (typeof(MozWebSocket) !== 'undefined') {\n", " return MozWebSocket;\n", " } else {\n", " alert('Your browser does not have WebSocket support.' +\n", " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", " 'Firefox 4 and 5 are also supported but you ' +\n", " 'have to enable WebSockets in about:config.');\n", " };\n", "}\n", "\n", "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n", " this.id = figure_id;\n", "\n", " this.ws = websocket;\n", "\n", " this.supports_binary = (this.ws.binaryType != undefined);\n", "\n", " if (!this.supports_binary) {\n", " var warnings = document.getElementById(\"mpl-warnings\");\n", " if (warnings) {\n", " warnings.style.display = 'block';\n", " warnings.textContent = (\n", " \"This browser does not support binary websocket messages. \" +\n", " \"Performance may be slow.\");\n", " }\n", " }\n", "\n", " this.imageObj = new Image();\n", "\n", " this.context = undefined;\n", " this.message = undefined;\n", " this.canvas = undefined;\n", " this.rubberband_canvas = undefined;\n", " this.rubberband_context = undefined;\n", " this.format_dropdown = undefined;\n", "\n", " this.image_mode = 'full';\n", "\n", " this.root = $('
');\n", " this._root_extra_style(this.root)\n", " this.root.attr('style', 'display: inline-block');\n", "\n", " $(parent_element).append(this.root);\n", "\n", " this._init_header(this);\n", " this._init_canvas(this);\n", " this._init_toolbar(this);\n", "\n", " var fig = this;\n", "\n", " this.waiting = false;\n", "\n", " this.ws.onopen = function () {\n", " fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n", " fig.send_message(\"send_image_mode\", {});\n", " fig.send_message(\"refresh\", {});\n", " }\n", "\n", " this.imageObj.onload = function() {\n", " if (fig.image_mode == 'full') {\n", " // Full images could contain transparency (where diff images\n", " // almost always do), so we need to clear the canvas so that\n", " // there is no ghosting.\n", " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", " }\n", " fig.context.drawImage(fig.imageObj, 0, 0);\n", " };\n", "\n", " this.imageObj.onunload = function() {\n", " this.ws.close();\n", " }\n", "\n", " this.ws.onmessage = this._make_on_message_function(this);\n", "\n", " this.ondownload = ondownload;\n", "}\n", "\n", "mpl.figure.prototype._init_header = function() {\n", " var titlebar = $(\n", " '
');\n", " var titletext = $(\n", " '
');\n", " titlebar.append(titletext)\n", " this.root.append(titlebar);\n", " this.header = titletext[0];\n", "}\n", "\n", "\n", "\n", "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n", "\n", "}\n", "\n", "\n", "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n", "\n", "}\n", "\n", "mpl.figure.prototype._init_canvas = function() {\n", " var fig = this;\n", "\n", " var canvas_div = $('
');\n", "\n", " canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n", "\n", " function canvas_keyboard_event(event) {\n", " return fig.key_event(event, event['data']);\n", " }\n", "\n", " canvas_div.keydown('key_press', canvas_keyboard_event);\n", " canvas_div.keyup('key_release', canvas_keyboard_event);\n", " this.canvas_div = canvas_div\n", " this._canvas_extra_style(canvas_div)\n", " this.root.append(canvas_div);\n", "\n", " var canvas = $('');\n", " canvas.addClass('mpl-canvas');\n", " canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n", "\n", " this.canvas = canvas[0];\n", " this.context = canvas[0].getContext(\"2d\");\n", "\n", " var rubberband = $('');\n", " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n", "\n", " var pass_mouse_events = true;\n", "\n", " canvas_div.resizable({\n", " start: function(event, ui) {\n", " pass_mouse_events = false;\n", " },\n", " resize: function(event, ui) {\n", " fig.request_resize(ui.size.width, ui.size.height);\n", " },\n", " stop: function(event, ui) {\n", " pass_mouse_events = true;\n", " fig.request_resize(ui.size.width, ui.size.height);\n", " },\n", " });\n", "\n", " function mouse_event_fn(event) {\n", " if (pass_mouse_events)\n", " return fig.mouse_event(event, event['data']);\n", " }\n", "\n", " rubberband.mousedown('button_press', mouse_event_fn);\n", " rubberband.mouseup('button_release', mouse_event_fn);\n", " // Throttle sequential mouse events to 1 every 20ms.\n", " rubberband.mousemove('motion_notify', mouse_event_fn);\n", "\n", " rubberband.mouseenter('figure_enter', mouse_event_fn);\n", " rubberband.mouseleave('figure_leave', mouse_event_fn);\n", "\n", " canvas_div.on(\"wheel\", function (event) {\n", " event = event.originalEvent;\n", " event['data'] = 'scroll'\n", " if (event.deltaY < 0) {\n", " event.step = 1;\n", " } else {\n", " event.step = -1;\n", " }\n", " mouse_event_fn(event);\n", " });\n", "\n", " canvas_div.append(canvas);\n", " canvas_div.append(rubberband);\n", "\n", " this.rubberband = rubberband;\n", " this.rubberband_canvas = rubberband[0];\n", " this.rubberband_context = rubberband[0].getContext(\"2d\");\n", " this.rubberband_context.strokeStyle = \"#000000\";\n", "\n", " this._resize_canvas = function(width, height) {\n", " // Keep the size of the canvas, canvas container, and rubber band\n", " // canvas in synch.\n", " canvas_div.css('width', width)\n", " canvas_div.css('height', height)\n", "\n", " canvas.attr('width', width);\n", " canvas.attr('height', height);\n", "\n", " rubberband.attr('width', width);\n", " rubberband.attr('height', height);\n", " }\n", "\n", " // Set the figure to an initial 600x600px, this will subsequently be updated\n", " // upon first draw.\n", " this._resize_canvas(600, 600);\n", "\n", " // Disable right mouse context menu.\n", " $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n", " return false;\n", " });\n", "\n", " function set_focus () {\n", " canvas.focus();\n", " canvas_div.focus();\n", " }\n", "\n", " window.setTimeout(set_focus, 100);\n", "}\n", "\n", "mpl.figure.prototype._init_toolbar = function() {\n", " var fig = this;\n", "\n", " var nav_element = $('
')\n", " nav_element.attr('style', 'width: 100%');\n", " this.root.append(nav_element);\n", "\n", " // Define a callback function for later on.\n", " function toolbar_event(event) {\n", " return fig.toolbar_button_onclick(event['data']);\n", " }\n", " function toolbar_mouse_event(event) {\n", " return fig.toolbar_button_onmouseover(event['data']);\n", " }\n", "\n", " for(var toolbar_ind in mpl.toolbar_items) {\n", " var name = mpl.toolbar_items[toolbar_ind][0];\n", " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", " var image = mpl.toolbar_items[toolbar_ind][2];\n", " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", "\n", " if (!name) {\n", " // put a spacer in here.\n", " continue;\n", " }\n", " var button = $('