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-rw-r--r--CHANGELOG.rst61
-rw-r--r--MANIFEST.in2
-rw-r--r--PKG-INFO7
-rw-r--r--README.rst4
-rw-r--r--doc/source/Tutorials/.ipynb_checkpoints/Image-checkpoint.ipynb1841
-rw-r--r--doc/source/Tutorials/Image.ipynb1873
-rw-r--r--doc/source/Tutorials/Sift/.ipynb_checkpoints/sift-checkpoint.ipynb4248
-rw-r--r--doc/source/Tutorials/Sift/sift.ipynb4321
-rw-r--r--doc/source/Tutorials/convert.rst28
-rw-r--r--doc/source/Tutorials/fit.rst164
-rw-r--r--doc/source/Tutorials/io.rst72
-rw-r--r--doc/source/Tutorials/specfile_to_hdf5.rst58
-rw-r--r--doc/source/Tutorials/writing_NXdata.rst357
-rw-r--r--doc/source/developers.rst98
-rw-r--r--doc/source/ext/snapshotqt_directive.py257
-rw-r--r--doc/source/index.rst2
-rw-r--r--doc/source/install.rst3
-rw-r--r--doc/source/modules/gui/colors.rst9
-rw-r--r--doc/source/modules/gui/dialog/colormapdialog.rst12
-rw-r--r--doc/source/modules/gui/dialog/groupdialog.rst8
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-rw-r--r--doc/source/modules/gui/dialog/index.rst14
-rw-r--r--doc/source/modules/gui/gallery.rst24
-rw-r--r--doc/source/modules/gui/hdf5/getting_started.rst65
-rw-r--r--doc/source/modules/gui/hdf5/hdf5headerview.rst9
-rw-r--r--doc/source/modules/gui/hdf5/index.rst1
-rw-r--r--doc/source/modules/gui/icons.rst57
-rw-r--r--doc/source/modules/gui/index.rst2
-rw-r--r--doc/source/modules/gui/plot/colormap.rst16
-rw-r--r--doc/source/modules/gui/plot/dev.rst18
-rw-r--r--doc/source/modules/gui/plot/getting_started.rst32
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-rw-r--r--doc/source/modules/gui/plot/index.rst24
-rw-r--r--doc/source/modules/gui/plot/items.rst7
-rw-r--r--doc/source/modules/gui/plot/plottools.rst36
-rw-r--r--doc/source/modules/gui/plot/plotwidget.rst1
-rw-r--r--doc/source/modules/gui/plot/scatterview.rst20
-rw-r--r--doc/source/modules/gui/plot/stats/index.rst18
-rw-r--r--doc/source/modules/gui/plot/stats/stats.rst6
-rw-r--r--doc/source/modules/gui/plot/stats/statshandler.rst7
-rw-r--r--doc/source/modules/gui/plot/statswidget.rst33
-rw-r--r--doc/source/modules/gui/plot/tools.rst108
-rw-r--r--doc/source/modules/gui/utils.rst12
-rw-r--r--doc/source/modules/image/index.rst3
-rw-r--r--doc/source/modules/image/marchingsquares.rst11
-rw-r--r--doc/source/modules/io/nxdata.rst6
-rw-r--r--doc/source/modules/math/colormap.rst6
-rw-r--r--doc/source/modules/math/combo.rst6
-rw-r--r--doc/source/modules/math/index.rst1
-rw-r--r--doc/source/modules/sx.rst6
-rw-r--r--doc/source/overview.rst6
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-rw-r--r--doc/source/sample_code/index.rst53
-rw-r--r--doc/source/tutorials.rst1
-rw-r--r--examples/blissPlot.py635
-rw-r--r--examples/colormapDialog.py8
-rw-r--r--examples/findContours.py704
-rwxr-xr-xexamples/hdf5widget.py10
-rwxr-xr-xexamples/imageview.py1
-rw-r--r--examples/plot3dSceneWindow.py5
-rw-r--r--examples/plotGL32.py46
-rw-r--r--examples/plotInteractiveImageROI.py110
-rw-r--r--examples/plotStats.py123
-rw-r--r--examples/plotTimeSeries.py33
-rw-r--r--examples/plotUpdateCurveFromThread.py (renamed from examples/plotUpdateFromThread.py)64
-rw-r--r--examples/plotUpdateImageFromThread.py133
-rw-r--r--examples/plotWidget.py100
-rw-r--r--examples/scatterMask.py6
-rw-r--r--package/debian8/control20
-rw-r--r--package/debian9/control20
-rw-r--r--package/desktop/silx.xml1
-rw-r--r--qtdesigner_plugins/README.rst10
-rw-r--r--requirements.txt6
-rwxr-xr-xrun_tests.py16
-rw-r--r--setup.py108
-rw-r--r--silx.egg-info/PKG-INFO7
-rw-r--r--silx.egg-info/SOURCES.txt175
-rw-r--r--silx.egg-info/requires.txt2
-rw-r--r--silx/__init__.py19
-rw-r--r--silx/__main__.py4
-rw-r--r--silx/_config.py83
-rw-r--r--silx/app/__init__.py4
-rw-r--r--silx/app/setup.py3
-rw-r--r--silx/app/test/__init__.py4
-rw-r--r--silx/app/test/test_view.py146
-rw-r--r--silx/app/view.py314
-rw-r--r--silx/app/view/About.py (renamed from silx/app/qtutils.py)35
-rw-r--r--silx/app/view/ApplicationContext.py194
-rw-r--r--silx/app/view/CustomNxdataWidget.py1008
-rw-r--r--silx/app/view/DataPanel.py171
-rw-r--r--silx/app/view/Viewer.py686
-rw-r--r--silx/app/view/__init__.py28
-rw-r--r--silx/app/view/main.py168
-rw-r--r--silx/app/view/setup.py40
-rw-r--r--silx/app/view/test/__init__.py41
-rw-r--r--silx/app/view/test/test_launcher.py145
-rw-r--r--silx/app/view/test/test_view.py402
-rw-r--r--silx/app/view/utils.py45
-rw-r--r--silx/gui/__init__.py24
-rw-r--r--silx/gui/_glutils/font.py7
-rw-r--r--silx/gui/colors.py732
-rw-r--r--silx/gui/console.py63
-rw-r--r--silx/gui/data/DataViewer.py37
-rw-r--r--silx/gui/data/DataViewerFrame.py9
-rw-r--r--silx/gui/data/DataViews.py260
-rw-r--r--silx/gui/data/Hdf5TableView.py62
-rw-r--r--silx/gui/data/HexaTableView.py10
-rw-r--r--silx/gui/data/NXdataWidgets.py32
-rw-r--r--silx/gui/data/TextFormatter.py18
-rw-r--r--silx/gui/data/test/test_dataviewer.py6
-rw-r--r--silx/gui/dialog/AbstractDataFileDialog.py6
-rw-r--r--silx/gui/dialog/ColormapDialog.py986
-rw-r--r--silx/gui/dialog/GroupDialog.py177
-rw-r--r--silx/gui/dialog/test/__init__.py4
-rw-r--r--silx/gui/dialog/test/test_colormapdialog.py (renamed from silx/gui/plot/test/testColormapDialog.py)29
-rw-r--r--silx/gui/dialog/test/test_datafiledialog.py24
-rw-r--r--silx/gui/dialog/test/test_imagefiledialog.py32
-rw-r--r--silx/gui/hdf5/Hdf5Formatter.py18
-rw-r--r--silx/gui/hdf5/Hdf5TreeModel.py90
-rw-r--r--silx/gui/hdf5/Hdf5TreeView.py17
-rw-r--r--silx/gui/hdf5/NexusSortFilterProxyModel.py59
-rw-r--r--silx/gui/hdf5/_utils.py22
-rw-r--r--silx/gui/hdf5/test/test_hdf5.py256
-rw-r--r--silx/gui/icons.py14
-rw-r--r--silx/gui/plot/ColorBar.py117
-rw-r--r--silx/gui/plot/Colormap.py567
-rw-r--r--silx/gui/plot/ColormapDialog.py964
-rw-r--r--silx/gui/plot/Colors.py122
-rw-r--r--silx/gui/plot/ComplexImageView.py6
-rw-r--r--silx/gui/plot/CurvesROIWidget.py195
-rw-r--r--silx/gui/plot/ImageView.py28
-rw-r--r--silx/gui/plot/MaskToolsWidget.py35
-rw-r--r--silx/gui/plot/PlotInteraction.py251
-rw-r--r--silx/gui/plot/PlotToolButtons.py95
-rw-r--r--silx/gui/plot/PlotTools.py289
-rw-r--r--silx/gui/plot/PlotWidget.py110
-rw-r--r--silx/gui/plot/PlotWindow.py181
-rw-r--r--silx/gui/plot/Profile.py12
-rw-r--r--silx/gui/plot/ProfileMainWindow.py4
-rw-r--r--silx/gui/plot/ScatterMaskToolsWidget.py68
-rw-r--r--silx/gui/plot/ScatterView.py353
-rw-r--r--silx/gui/plot/StackView.py72
-rw-r--r--silx/gui/plot/StatsWidget.py572
-rw-r--r--silx/gui/plot/_BaseMaskToolsWidget.py49
-rw-r--r--silx/gui/plot/__init__.py7
-rw-r--r--silx/gui/plot/_utils/dtime_ticklayout.py438
-rw-r--r--silx/gui/plot/_utils/test/__init__.py4
-rw-r--r--silx/gui/plot/_utils/test/testColormap.py648
-rw-r--r--silx/gui/plot/_utils/test/test_dtime_ticklayout.py93
-rw-r--r--silx/gui/plot/_utils/ticklayout.py85
-rw-r--r--silx/gui/plot/actions/control.py24
-rw-r--r--silx/gui/plot/actions/histogram.py4
-rw-r--r--silx/gui/plot/actions/io.py344
-rw-r--r--silx/gui/plot/actions/mode.py10
-rw-r--r--silx/gui/plot/backends/BackendBase.py43
-rw-r--r--silx/gui/plot/backends/BackendMatplotlib.py238
-rw-r--r--silx/gui/plot/backends/BackendOpenGL.py254
-rw-r--r--silx/gui/plot/backends/glutils/GLPlotCurve.py1070
-rw-r--r--silx/gui/plot/backends/glutils/GLPlotFrame.py97
-rw-r--r--silx/gui/plot/backends/glutils/GLPlotImage.py31
-rw-r--r--silx/gui/plot/backends/glutils/GLSupport.py37
-rw-r--r--silx/gui/plot/backends/glutils/GLText.py5
-rw-r--r--silx/gui/plot/items/axis.py154
-rw-r--r--silx/gui/plot/items/complex.py8
-rw-r--r--silx/gui/plot/items/core.py38
-rw-r--r--silx/gui/plot/items/curve.py8
-rw-r--r--silx/gui/plot/items/histogram.py37
-rw-r--r--silx/gui/plot/items/roi.py1416
-rw-r--r--silx/gui/plot/items/scatter.py6
-rw-r--r--silx/gui/plot/matplotlib/Colormap.py6
-rw-r--r--silx/gui/plot/matplotlib/__init__.py50
-rw-r--r--silx/gui/plot/setup.py6
-rw-r--r--silx/gui/plot/stats/__init__.py (renamed from silx/math/include/isnan.h)22
-rw-r--r--silx/gui/plot/stats/stats.py491
-rw-r--r--silx/gui/plot/stats/statshandler.py190
-rw-r--r--silx/gui/plot/test/__init__.py25
-rw-r--r--silx/gui/plot/test/testColorBar.py12
-rw-r--r--silx/gui/plot/test/testColors.py94
-rw-r--r--silx/gui/plot/test/testCurvesROIWidget.py24
-rw-r--r--silx/gui/plot/test/testImageView.py4
-rw-r--r--silx/gui/plot/test/testLimitConstraints.py6
-rw-r--r--silx/gui/plot/test/testPixelIntensityHistoAction.py104
-rw-r--r--silx/gui/plot/test/testPlotWidget.py71
-rw-r--r--silx/gui/plot/test/testPlotWidgetNoBackend.py12
-rw-r--r--silx/gui/plot/test/testSaveAction.py40
-rw-r--r--silx/gui/plot/test/testScatterView.py115
-rw-r--r--silx/gui/plot/test/testStackView.py15
-rw-r--r--silx/gui/plot/test/testStats.py561
-rw-r--r--silx/gui/plot/test/utils.py7
-rw-r--r--silx/gui/plot/tools/LimitsToolBar.py131
-rw-r--r--silx/gui/plot/tools/PositionInfo.py347
-rw-r--r--silx/gui/plot/tools/__init__.py50
-rw-r--r--silx/gui/plot/tools/profile/ImageProfileToolBar.py271
-rw-r--r--silx/gui/plot/tools/profile/ScatterProfileToolBar.py431
-rw-r--r--silx/gui/plot/tools/profile/_BaseProfileToolBar.py430
-rw-r--r--silx/gui/plot/tools/profile/__init__.py38
-rw-r--r--silx/gui/plot/tools/roi.py934
-rw-r--r--silx/gui/plot/tools/test/__init__.py48
-rw-r--r--silx/gui/plot/tools/test/testROI.py456
-rw-r--r--silx/gui/plot/tools/test/testScatterProfileToolBar.py216
-rw-r--r--silx/gui/plot/tools/test/testTools.py (renamed from silx/gui/plot/test/testPlotTools.py)103
-rw-r--r--silx/gui/plot/tools/toolbars.py356
-rw-r--r--silx/gui/plot/utils/axis.py50
-rw-r--r--silx/gui/plot3d/Plot3DWidget.py6
-rw-r--r--silx/gui/plot3d/SFViewParamTree.py8
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-rw-r--r--silx/gui/plot3d/SceneWidget.py6
-rw-r--r--silx/gui/plot3d/SceneWindow.py13
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-rw-r--r--silx/gui/plot3d/actions/io.py11
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-rw-r--r--silx/resources/gui/icons/tree-collapse-all.pngbin0 -> 508 bytes
-rw-r--r--silx/resources/gui/icons/tree-collapse-all.svg2
-rw-r--r--silx/resources/gui/icons/tree-expand-all.pngbin0 -> 602 bytes
-rw-r--r--silx/resources/gui/icons/tree-expand-all.svg2
-rw-r--r--silx/setup.py3
-rw-r--r--silx/sx/__init__.py70
-rw-r--r--silx/sx/_plot.py373
-rw-r--r--silx/sx/_plot3d.py8
-rw-r--r--silx/sx/test/__init__.py38
-rw-r--r--silx/sx/test/test_sx.py288
-rw-r--r--silx/test/__init__.py30
-rw-r--r--silx/test/test_sx.py279
-rw-r--r--silx/third_party/EdfFile.py2
-rw-r--r--silx/third_party/__init__.py7
-rw-r--r--silx/third_party/setup.py4
-rw-r--r--silx/utils/__init__.py28
-rw-r--r--silx/utils/_have_openmp.pxi49
-rw-r--r--silx/utils/debug.py102
-rw-r--r--silx/utils/include/silx_store_openmp.h10
-rw-r--r--silx/utils/number.py143
-rw-r--r--silx/utils/test/__init__.py6
-rw-r--r--silx/utils/test/test_debug.py99
-rw-r--r--silx/utils/test/test_number.py181
-rw-r--r--silx/utils/weakref.py4
-rw-r--r--version.py6
366 files changed, 226312 insertions, 62435 deletions
diff --git a/CHANGELOG.rst b/CHANGELOG.rst
index 2eb56e6..2a98a90 100644
--- a/CHANGELOG.rst
+++ b/CHANGELOG.rst
@@ -1,6 +1,67 @@
Change Log
==========
+0.8.0: 2018/07/04
+-----------------
+
+ * Graphical user interface:
+
+ * Plot:
+
+ * Adds support of x-axis date/time ticks for time series display (see `silx.gui.plot.items.XAxis.setTickMode`)
+ * Adds support of interactive authoring of regions of interest (see `silx.gui.plot.items.roi` and `silx.gui.plot.tools.roi`)
+ * Adds `StatsWidget` widget for displaying statistics on data displayed in a `PlotWidget`
+ * Adds `ScatterView` widget for displaying scatter plot with tools such as line profile and mask
+ * Overcomes the limitation to float32 precision with the OpenGL backend
+ * Splits plot toolbar is several reusable thematic toolbars
+
+ * Plot3D: Adds `SceneWidget` items to display many cubes, cylinders or hexagonal prisms at once
+ * Adds `silx.gui.utils` package with `submitToQtMainThread` for asynchronous execution of Qt-related functions
+ * Adds Qt signals to `Hdf5TreeView` to manage HDF5 file life-cycle
+ * Adds `GroupDialog` dialog to select a group in a HDF5 file
+ * Improves colormap computation with a Cython/OpenMP implementation
+
+ * Main API changes:
+
+ * `Colormap` is now part of `silx.gui.colors`
+ * `ColormapDialog` is now part of `silx.gui.dialogs`
+ * `MaskToolsWidget.getSelectionMask` method now returns `None` if no image is selected
+ * Clean-up `FrameBrowser` API
+
+ * Image
+
+ * Adds an optimized marching squares algorithm to compute many iso contours from the same image
+
+ * Input/output:
+
+ * Improves handling of empty Spec scans
+ * Add an API to `NXdata` parser to get messages about malformed input data
+
+ * `silx.sx`
+
+ * Allows to use `silx.sx` in script as in Python interpreter
+ * `sx.imshow` supports custom y-axis orientation using argument `origin=upper|lower`
+ * Adds `sx.enable_gui()` to enable silx widgets in IPython notebooks
+
+ * `silx convert`
+
+ * Improves conversion from EDF file series to HDF5
+
+ * `silx view`
+
+ * Adds user preferences to restore colormap, plot backend, y-axis of plot image,...
+ * Adds `--fresh` option to clean up user preferences at startup
+ * Adds a widget to create custom viewable `NXdata` by combining different datasets
+ * Supports `CTRL+C` shortcut in the terminal to close the application
+ * Adds buttons to collapse/expand tree items
+ * NXdata view now uses the `ScatterView` widget for scatters
+
+ * Miscellaneous
+
+ * Drops official support of Debian 7
+ * Drops versions of IPython console widget before the `qtconsole` package
+ * Fixes EDF file size written by `EdfFile` module with Python 3
+
0.7.0: 2018/02/27
-----------------
diff --git a/MANIFEST.in b/MANIFEST.in
index 0a8a964..4e9b35f 100644
--- a/MANIFEST.in
+++ b/MANIFEST.in
@@ -11,7 +11,7 @@ include requirements.txt
include requirements-dev.txt
recursive-include silx *.pyx *.pxd *.pxi
recursive-include silx *.h *.c *.hpp *.cpp
-recursive-include doc/source *.py *.rst *.png *.ico
+recursive-include doc/source *.py *.rst *.png *.ico *.ipynb
recursive-include qtdesigner_plugins *.py *.rst
recursive-include silx/resources *
recursive-include examples *
diff --git a/PKG-INFO b/PKG-INFO
index 907a50f..ecb8d4f 100644
--- a/PKG-INFO
+++ b/PKG-INFO
@@ -1,6 +1,6 @@
Metadata-Version: 1.1
Name: silx
-Version: 0.7.0
+Version: 0.8.0
Summary: Software library for X-ray data analysis
Home-page: http://www.silx.org/
Author: data analysis unit
@@ -102,9 +102,9 @@ Description:
*silx* releases can be cited via their DOI on Zenodo: |zenodo DOI|
.. |Travis Status| image:: https://travis-ci.org/silx-kit/silx.svg?branch=master
- :target: https://travis-ci.org/silx-kit/silx
+ :target: https://travis-ci.org/silx-kit/silx?branch=master
.. |Appveyor Status| image:: https://ci.appveyor.com/api/projects/status/qgox9ei0wxwfagrb/branch/master?svg=true
- :target: https://ci.appveyor.com/project/ESRF/silx
+ :target: https://ci.appveyor.com/project/ESRF/silx?branch=master
.. |zenodo DOI| image:: https://zenodo.org/badge/DOI/10.5281/zenodo.591709.svg
:target: https://doi.org/10.5281/zenodo.591709
@@ -126,6 +126,7 @@ Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
+Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Topic :: Software Development :: Libraries :: Python Modules
diff --git a/README.rst b/README.rst
index b6ab6c2..8e420fd 100644
--- a/README.rst
+++ b/README.rst
@@ -94,8 +94,8 @@ Citation
*silx* releases can be cited via their DOI on Zenodo: |zenodo DOI|
.. |Travis Status| image:: https://travis-ci.org/silx-kit/silx.svg?branch=master
- :target: https://travis-ci.org/silx-kit/silx
+ :target: https://travis-ci.org/silx-kit/silx?branch=master
.. |Appveyor Status| image:: https://ci.appveyor.com/api/projects/status/qgox9ei0wxwfagrb/branch/master?svg=true
- :target: https://ci.appveyor.com/project/ESRF/silx
+ :target: https://ci.appveyor.com/project/ESRF/silx?branch=master
.. |zenodo DOI| image:: https://zenodo.org/badge/DOI/10.5281/zenodo.591709.svg
:target: https://doi.org/10.5281/zenodo.591709
diff --git a/doc/source/Tutorials/.ipynb_checkpoints/Image-checkpoint.ipynb b/doc/source/Tutorials/.ipynb_checkpoints/Image-checkpoint.ipynb
new file mode 100644
index 0000000..8042fc7
--- /dev/null
+++ b/doc/source/Tutorials/.ipynb_checkpoints/Image-checkpoint.ipynb
@@ -0,0 +1,1841 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Image processing performance optimisation\n",
+ "\n",
+ "The idea of this tutorial is to give some suggestion how optimise image processing.\n",
+ "In the following example we decompress a CBF image from a Pilatus 6M, take the log-scale and calculate the histogram of pixel intensities before plotting. \n",
+ "This very simple operation takes >300ms, what makes it unpractical for live display of images coming from a detector. "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Populating the interactive namespace from numpy and matplotlib\n"
+ ]
+ }
+ ],
+ "source": [
+ "%pylab nbagg"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Using silx version 0.8.0-dev0\n",
+ "filename powder_200_2_0001.cbf\n"
+ ]
+ },
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "/media/data_unused/tvincent/venvs/py3env/lib/python3.4/importlib/_bootstrap.py:321: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
+ " return f(*args, **kwds)\n"
+ ]
+ }
+ ],
+ "source": [
+ "import time, os\n",
+ "start_time = time.time()\n",
+ "import silx\n",
+ "print(\"Using silx version \",silx.version)\n",
+ "from silx.resources import ExternalResources\n",
+ "downloader = ExternalResources(\"pyFAI\", \"http://www.silx.org/pub/pyFAI/testimages\", \"PYFAI_DATA\")\n",
+ "fname = downloader.getfile(\"powder_200_2_0001.cbf\")\n",
+ "print(\"filename\", os.path.basename(fname))\n",
+ "import fabio\n",
+ "nbins = 1000"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "CPU times: user 380 ms, sys: 40 ms, total: 420 ms\n",
+ "Wall time: 420 ms\n"
+ ]
+ }
+ ],
+ "source": [
+ "%%time\n",
+ "\n",
+ "#Display an image and the histogram of values (in log scale)\n",
+ "img = fabio.open(fname).data\n",
+ "log_img = numpy.arcsinh(img) # arcsinh is well behaved log-like function\n",
+ "his, edges = numpy.histogram(log_img, nbins)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {},
+ "outputs": [
+ {
+ "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 = $('<div/>');\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",
+ " '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
+ " 'ui-helper-clearfix\"/>');\n",
+ " var titletext = $(\n",
+ " '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
+ " 'text-align: center; padding: 3px;\"/>');\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 = $('<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 = $('<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 = $('<canvas/>');\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 = $('<div/>')\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 = $('<button/>');\n",
+ " button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
+ " 'ui-button-icon-only');\n",
+ " button.attr('role', 'button');\n",
+ " button.attr('aria-disabled', 'false');\n",
+ " button.click(method_name, toolbar_event);\n",
+ " button.mouseover(tooltip, toolbar_mouse_event);\n",
+ "\n",
+ " var icon_img = $('<span/>');\n",
+ " icon_img.addClass('ui-button-icon-primary ui-icon');\n",
+ " icon_img.addClass(image);\n",
+ " icon_img.addClass('ui-corner-all');\n",
+ "\n",
+ " var tooltip_span = $('<span/>');\n",
+ " tooltip_span.addClass('ui-button-text');\n",
+ " tooltip_span.html(tooltip);\n",
+ "\n",
+ " button.append(icon_img);\n",
+ " button.append(tooltip_span);\n",
+ "\n",
+ " nav_element.append(button);\n",
+ " }\n",
+ "\n",
+ " var fmt_picker_span = $('<span/>');\n",
+ "\n",
+ " var fmt_picker = $('<select/>');\n",
+ " fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
+ " fmt_picker_span.append(fmt_picker);\n",
+ " nav_element.append(fmt_picker_span);\n",
+ " this.format_dropdown = fmt_picker[0];\n",
+ "\n",
+ " for (var ind in mpl.extensions) {\n",
+ " var fmt = mpl.extensions[ind];\n",
+ " var option = $(\n",
+ " '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
+ " fmt_picker.append(option)\n",
+ " }\n",
+ "\n",
+ " // Add hover states to the ui-buttons\n",
+ " $( \".ui-button\" ).hover(\n",
+ " function() { $(this).addClass(\"ui-state-hover\");},\n",
+ " function() { $(this).removeClass(\"ui-state-hover\");}\n",
+ " );\n",
+ "\n",
+ " var status_bar = $('<span class=\"mpl-message\"/>');\n",
+ " nav_element.append(status_bar);\n",
+ " this.message = status_bar[0];\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
+ " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+ " // which will in turn request a refresh of the image.\n",
+ " this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.send_message = function(type, properties) {\n",
+ " properties['type'] = type;\n",
+ " properties['figure_id'] = this.id;\n",
+ " this.ws.send(JSON.stringify(properties));\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.send_draw_message = function() {\n",
+ " if (!this.waiting) {\n",
+ " this.waiting = true;\n",
+ " this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
+ " }\n",
+ "}\n",
+ "\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+ " var format_dropdown = fig.format_dropdown;\n",
+ " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+ " fig.ondownload(fig, format);\n",
+ "}\n",
+ "\n",
+ "\n",
+ "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
+ " var size = msg['size'];\n",
+ " if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
+ " fig._resize_canvas(size[0], size[1]);\n",
+ " fig.send_message(\"refresh\", {});\n",
+ " };\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
+ " var x0 = msg['x0'];\n",
+ " var y0 = fig.canvas.height - msg['y0'];\n",
+ " var x1 = msg['x1'];\n",
+ " var y1 = fig.canvas.height - msg['y1'];\n",
+ " x0 = Math.floor(x0) + 0.5;\n",
+ " y0 = Math.floor(y0) + 0.5;\n",
+ " x1 = Math.floor(x1) + 0.5;\n",
+ " y1 = Math.floor(y1) + 0.5;\n",
+ " var min_x = Math.min(x0, x1);\n",
+ " var min_y = Math.min(y0, y1);\n",
+ " var width = Math.abs(x1 - x0);\n",
+ " var height = Math.abs(y1 - y0);\n",
+ "\n",
+ " fig.rubberband_context.clearRect(\n",
+ " 0, 0, fig.canvas.width, fig.canvas.height);\n",
+ "\n",
+ " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
+ " // Updates the figure title.\n",
+ " fig.header.textContent = msg['label'];\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
+ " var cursor = msg['cursor'];\n",
+ " switch(cursor)\n",
+ " {\n",
+ " case 0:\n",
+ " cursor = 'pointer';\n",
+ " break;\n",
+ " case 1:\n",
+ " cursor = 'default';\n",
+ " break;\n",
+ " case 2:\n",
+ " cursor = 'crosshair';\n",
+ " break;\n",
+ " case 3:\n",
+ " cursor = 'move';\n",
+ " break;\n",
+ " }\n",
+ " fig.rubberband_canvas.style.cursor = cursor;\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
+ " fig.message.textContent = msg['message'];\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
+ " // Request the server to send over a new figure.\n",
+ " fig.send_draw_message();\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
+ " fig.image_mode = msg['mode'];\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function() {\n",
+ " // Called whenever the canvas gets updated.\n",
+ " this.send_message(\"ack\", {});\n",
+ "}\n",
+ "\n",
+ "// A function to construct a web socket function for onmessage handling.\n",
+ "// Called in the figure constructor.\n",
+ "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
+ " return function socket_on_message(evt) {\n",
+ " if (evt.data instanceof Blob) {\n",
+ " /* FIXME: We get \"Resource interpreted as Image but\n",
+ " * transferred with MIME type text/plain:\" errors on\n",
+ " * Chrome. But how to set the MIME type? It doesn't seem\n",
+ " * to be part of the websocket stream */\n",
+ " evt.data.type = \"image/png\";\n",
+ "\n",
+ " /* Free the memory for the previous frames */\n",
+ " if (fig.imageObj.src) {\n",
+ " (window.URL || window.webkitURL).revokeObjectURL(\n",
+ " fig.imageObj.src);\n",
+ " }\n",
+ "\n",
+ " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+ " evt.data);\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " }\n",
+ " else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
+ " fig.imageObj.src = evt.data;\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " var msg = JSON.parse(evt.data);\n",
+ " var msg_type = msg['type'];\n",
+ "\n",
+ " // Call the \"handle_{type}\" callback, which takes\n",
+ " // the figure and JSON message as its only arguments.\n",
+ " try {\n",
+ " var callback = fig[\"handle_\" + msg_type];\n",
+ " } catch (e) {\n",
+ " console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " if (callback) {\n",
+ " try {\n",
+ " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+ " callback(fig, msg);\n",
+ " } catch (e) {\n",
+ " console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
+ " }\n",
+ " }\n",
+ " };\n",
+ "}\n",
+ "\n",
+ "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+ "mpl.findpos = function(e) {\n",
+ " //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+ " var targ;\n",
+ " if (!e)\n",
+ " e = window.event;\n",
+ " if (e.target)\n",
+ " targ = e.target;\n",
+ " else if (e.srcElement)\n",
+ " targ = e.srcElement;\n",
+ " if (targ.nodeType == 3) // defeat Safari bug\n",
+ " targ = targ.parentNode;\n",
+ "\n",
+ " // jQuery normalizes the pageX and pageY\n",
+ " // pageX,Y are the mouse positions relative to the document\n",
+ " // offset() returns the position of the element relative to the document\n",
+ " var x = e.pageX - $(targ).offset().left;\n",
+ " var y = e.pageY - $(targ).offset().top;\n",
+ "\n",
+ " return {\"x\": x, \"y\": y};\n",
+ "};\n",
+ "\n",
+ "/*\n",
+ " * return a copy of an object with only non-object keys\n",
+ " * we need this to avoid circular references\n",
+ " * http://stackoverflow.com/a/24161582/3208463\n",
+ " */\n",
+ "function simpleKeys (original) {\n",
+ " return Object.keys(original).reduce(function (obj, key) {\n",
+ " if (typeof original[key] !== 'object')\n",
+ " obj[key] = original[key]\n",
+ " return obj;\n",
+ " }, {});\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.mouse_event = function(event, name) {\n",
+ " var canvas_pos = mpl.findpos(event)\n",
+ "\n",
+ " if (name === 'button_press')\n",
+ " {\n",
+ " this.canvas.focus();\n",
+ " this.canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " var x = canvas_pos.x;\n",
+ " var y = canvas_pos.y;\n",
+ "\n",
+ " this.send_message(name, {x: x, y: y, button: event.button,\n",
+ " step: event.step,\n",
+ " guiEvent: simpleKeys(event)});\n",
+ "\n",
+ " /* This prevents the web browser from automatically changing to\n",
+ " * the text insertion cursor when the button is pressed. We want\n",
+ " * to control all of the cursor setting manually through the\n",
+ " * 'cursor' event from matplotlib */\n",
+ " event.preventDefault();\n",
+ " return false;\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+ " // Handle any extra behaviour associated with a key event\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.key_event = function(event, name) {\n",
+ "\n",
+ " // Prevent repeat events\n",
+ " if (name == 'key_press')\n",
+ " {\n",
+ " if (event.which === this._key)\n",
+ " return;\n",
+ " else\n",
+ " this._key = event.which;\n",
+ " }\n",
+ " if (name == 'key_release')\n",
+ " this._key = null;\n",
+ "\n",
+ " var value = '';\n",
+ " if (event.ctrlKey && event.which != 17)\n",
+ " value += \"ctrl+\";\n",
+ " if (event.altKey && event.which != 18)\n",
+ " value += \"alt+\";\n",
+ " if (event.shiftKey && event.which != 16)\n",
+ " value += \"shift+\";\n",
+ "\n",
+ " value += 'k';\n",
+ " value += event.which.toString();\n",
+ "\n",
+ " this._key_event_extra(event, name);\n",
+ "\n",
+ " this.send_message(name, {key: value,\n",
+ " guiEvent: simpleKeys(event)});\n",
+ " return false;\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
+ " if (name == 'download') {\n",
+ " this.handle_save(this, null);\n",
+ " } else {\n",
+ " this.send_message(\"toolbar_button\", {name: name});\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
+ " this.message.textContent = tooltip;\n",
+ "};\n",
+ "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+ "\n",
+ "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
+ "\n",
+ "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
+ " // Create a \"websocket\"-like object which calls the given IPython comm\n",
+ " // object with the appropriate methods. Currently this is a non binary\n",
+ " // socket, so there is still some room for performance tuning.\n",
+ " var ws = {};\n",
+ "\n",
+ " ws.close = function() {\n",
+ " comm.close()\n",
+ " };\n",
+ " ws.send = function(m) {\n",
+ " //console.log('sending', m);\n",
+ " comm.send(m);\n",
+ " };\n",
+ " // Register the callback with on_msg.\n",
+ " comm.on_msg(function(msg) {\n",
+ " //console.log('receiving', msg['content']['data'], msg);\n",
+ " // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
+ " ws.onmessage(msg['content']['data'])\n",
+ " });\n",
+ " return ws;\n",
+ "}\n",
+ "\n",
+ "mpl.mpl_figure_comm = function(comm, msg) {\n",
+ " // This is the function which gets called when the mpl process\n",
+ " // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
+ "\n",
+ " var id = msg.content.data.id;\n",
+ " // Get hold of the div created by the display call when the Comm\n",
+ " // socket was opened in Python.\n",
+ " var element = $(\"#\" + id);\n",
+ " var ws_proxy = comm_websocket_adapter(comm)\n",
+ "\n",
+ " function ondownload(figure, format) {\n",
+ " window.open(figure.imageObj.src);\n",
+ " }\n",
+ "\n",
+ " var fig = new mpl.figure(id, ws_proxy,\n",
+ " ondownload,\n",
+ " element.get(0));\n",
+ "\n",
+ " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
+ " // web socket which is closed, not our websocket->open comm proxy.\n",
+ " ws_proxy.onopen();\n",
+ "\n",
+ " fig.parent_element = element.get(0);\n",
+ " fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
+ " if (!fig.cell_info) {\n",
+ " console.error(\"Failed to find cell for figure\", id, fig);\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " var output_index = fig.cell_info[2]\n",
+ " var cell = fig.cell_info[0];\n",
+ "\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
+ " fig.root.unbind('remove')\n",
+ "\n",
+ " // Update the output cell to use the data from the current canvas.\n",
+ " fig.push_to_output();\n",
+ " var dataURL = fig.canvas.toDataURL();\n",
+ " // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+ " // the notebook keyboard shortcuts fail.\n",
+ " IPython.keyboard_manager.enable()\n",
+ " $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
+ " fig.close_ws(fig, msg);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.close_ws = function(fig, msg){\n",
+ " fig.send_message('closing', msg);\n",
+ " // fig.ws.close()\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
+ " // Turn the data on the canvas into data in the output cell.\n",
+ " var dataURL = this.canvas.toDataURL();\n",
+ " this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function() {\n",
+ " // Tell IPython that the notebook contents must change.\n",
+ " IPython.notebook.set_dirty(true);\n",
+ " this.send_message(\"ack\", {});\n",
+ " var fig = this;\n",
+ " // Wait a second, then push the new image to the DOM so\n",
+ " // that it is saved nicely (might be nice to debounce this).\n",
+ " setTimeout(function () { fig.push_to_output() }, 1000);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function() {\n",
+ " var fig = this;\n",
+ "\n",
+ " var nav_element = $('<div/>')\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) { continue; };\n",
+ "\n",
+ " var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
+ " button.click(method_name, toolbar_event);\n",
+ " button.mouseover(tooltip, toolbar_mouse_event);\n",
+ " nav_element.append(button);\n",
+ " }\n",
+ "\n",
+ " // Add the status bar.\n",
+ " var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
+ " nav_element.append(status_bar);\n",
+ " this.message = status_bar[0];\n",
+ "\n",
+ " // Add the close button to the window.\n",
+ " var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
+ " var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
+ " button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
+ " button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
+ " buttongrp.append(button);\n",
+ " var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
+ " titlebar.prepend(buttongrp);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function(el){\n",
+ " var fig = this\n",
+ " el.on(\"remove\", function(){\n",
+ "\tfig.close_ws(fig, {});\n",
+ " });\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function(el){\n",
+ " // this is important to make the div 'focusable\n",
+ " el.attr('tabindex', 0)\n",
+ " // reach out to IPython and tell the keyboard manager to turn it's self\n",
+ " // off when our div gets focus\n",
+ "\n",
+ " // location in version 3\n",
+ " if (IPython.notebook.keyboard_manager) {\n",
+ " IPython.notebook.keyboard_manager.register_events(el);\n",
+ " }\n",
+ " else {\n",
+ " // location in version 2\n",
+ " IPython.keyboard_manager.register_events(el);\n",
+ " }\n",
+ "\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+ " var manager = IPython.notebook.keyboard_manager;\n",
+ " if (!manager)\n",
+ " manager = IPython.keyboard_manager;\n",
+ "\n",
+ " // Check for shift+enter\n",
+ " if (event.shiftKey && event.which == 13) {\n",
+ " this.canvas_div.blur();\n",
+ " event.shiftKey = false;\n",
+ " // Send a \"J\" for go to next cell\n",
+ " event.which = 74;\n",
+ " event.keyCode = 74;\n",
+ " manager.command_mode();\n",
+ " manager.handle_keydown(event);\n",
+ " }\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+ " fig.ondownload(fig, null);\n",
+ "}\n",
+ "\n",
+ "\n",
+ "mpl.find_output_cell = function(html_output) {\n",
+ " // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+ " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+ " // IPython event is triggered only after the cells have been serialised, which for\n",
+ " // our purposes (turning an active figure into a static one), is too late.\n",
+ " var cells = IPython.notebook.get_cells();\n",
+ " var ncells = cells.length;\n",
+ " for (var i=0; i<ncells; i++) {\n",
+ " var cell = cells[i];\n",
+ " if (cell.cell_type === 'code'){\n",
+ " for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
+ " var data = cell.output_area.outputs[j];\n",
+ " if (data.data) {\n",
+ " // IPython >= 3 moved mimebundle to data attribute of output\n",
+ " data = data.data;\n",
+ " }\n",
+ " if (data['text/html'] == html_output) {\n",
+ " return [cell, data, j];\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ "}\n",
+ "\n",
+ "// Register the function which deals with the matplotlib target/channel.\n",
+ "// The kernel may be null if the page has been refreshed.\n",
+ "if (IPython.notebook.kernel != null) {\n",
+ " IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
+ "}\n"
+ ],
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\">"
+ ],
+ "text/plain": [
+ "<IPython.core.display.HTML object>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "text/plain": [
+ "[<matplotlib.lines.Line2D at 0x7f57a47b0588>]"
+ ]
+ },
+ "execution_count": 4,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "fig, ax = subplots(1,2,)\n",
+ "center = (edges[1:] + edges[:-1])/2.0 # this is the center of the bins \n",
+ "ax[1].imshow(log_img, cmap=\"inferno\")\n",
+ "ax[0].plot(center,his)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Optimised GPU code\n",
+ "\n",
+ "The code below prepares a GPU to be able to perform the same calculation as in the previous example.\n",
+ "\n",
+ "3 operations have to be carried out:\n",
+ "\n",
+ "* Decompress the CBF image\n",
+ "* Calculate the log scale (arcsinh values)\n",
+ "* Calculate the histogram\n",
+ "\n",
+ "Both can be performed on the GPU without additional memory transfer"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "#switch this to \"CPU\" to have a fail safe \n",
+ "devicetype = \"GPU\"\n",
+ "from silx.opencl.codec.byte_offset import ByteOffset\n",
+ "from silx.opencl.image import ImageProcessing\n",
+ "import pyopencl, pyopencl.array, pyopencl.elementwise\n",
+ "cbf = fabio.cbfimage.CbfImage()\n",
+ "bo = ByteOffset(os.path.getsize(fname), img.size, devicetype=devicetype)\n",
+ "ash = pyopencl.elementwise.ElementwiseKernel(bo.ctx, \n",
+ " arguments=\"float* data, float* res\", \n",
+ " operation=\"res[i] = asinh(data[i])\", \n",
+ " name='arcsinh_kernel')\n",
+ "ip = ImageProcessing(template=img, ctx=bo.ctx)\n",
+ "res = pyopencl.array.empty(bo.queue, img.shape, dtype=float32)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "CPU times: user 432 ms, sys: 36 ms, total: 468 ms\n",
+ "Wall time: 486 ms\n"
+ ]
+ }
+ ],
+ "source": [
+ "%%time \n",
+ "raw = cbf.read(fname, only_raw=True)\n",
+ "dec = bo(raw, as_float=True)\n",
+ "ash(dec, res)\n",
+ "his, edges = ip.histogram(res, nbins, copy=False)\n",
+ "log_img = res.get()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {},
+ "outputs": [
+ {
+ "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 = $('<div/>');\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",
+ " '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
+ " 'ui-helper-clearfix\"/>');\n",
+ " var titletext = $(\n",
+ " '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
+ " 'text-align: center; padding: 3px;\"/>');\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 = $('<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 = $('<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 = $('<canvas/>');\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 = $('<div/>')\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 = $('<button/>');\n",
+ " button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
+ " 'ui-button-icon-only');\n",
+ " button.attr('role', 'button');\n",
+ " button.attr('aria-disabled', 'false');\n",
+ " button.click(method_name, toolbar_event);\n",
+ " button.mouseover(tooltip, toolbar_mouse_event);\n",
+ "\n",
+ " var icon_img = $('<span/>');\n",
+ " icon_img.addClass('ui-button-icon-primary ui-icon');\n",
+ " icon_img.addClass(image);\n",
+ " icon_img.addClass('ui-corner-all');\n",
+ "\n",
+ " var tooltip_span = $('<span/>');\n",
+ " tooltip_span.addClass('ui-button-text');\n",
+ " tooltip_span.html(tooltip);\n",
+ "\n",
+ " button.append(icon_img);\n",
+ " button.append(tooltip_span);\n",
+ "\n",
+ " nav_element.append(button);\n",
+ " }\n",
+ "\n",
+ " var fmt_picker_span = $('<span/>');\n",
+ "\n",
+ " var fmt_picker = $('<select/>');\n",
+ " fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
+ " fmt_picker_span.append(fmt_picker);\n",
+ " nav_element.append(fmt_picker_span);\n",
+ " this.format_dropdown = fmt_picker[0];\n",
+ "\n",
+ " for (var ind in mpl.extensions) {\n",
+ " var fmt = mpl.extensions[ind];\n",
+ " var option = $(\n",
+ " '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
+ " fmt_picker.append(option)\n",
+ " }\n",
+ "\n",
+ " // Add hover states to the ui-buttons\n",
+ " $( \".ui-button\" ).hover(\n",
+ " function() { $(this).addClass(\"ui-state-hover\");},\n",
+ " function() { $(this).removeClass(\"ui-state-hover\");}\n",
+ " );\n",
+ "\n",
+ " var status_bar = $('<span class=\"mpl-message\"/>');\n",
+ " nav_element.append(status_bar);\n",
+ " this.message = status_bar[0];\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
+ " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+ " // which will in turn request a refresh of the image.\n",
+ " this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.send_message = function(type, properties) {\n",
+ " properties['type'] = type;\n",
+ " properties['figure_id'] = this.id;\n",
+ " this.ws.send(JSON.stringify(properties));\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.send_draw_message = function() {\n",
+ " if (!this.waiting) {\n",
+ " this.waiting = true;\n",
+ " this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
+ " }\n",
+ "}\n",
+ "\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+ " var format_dropdown = fig.format_dropdown;\n",
+ " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+ " fig.ondownload(fig, format);\n",
+ "}\n",
+ "\n",
+ "\n",
+ "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
+ " var size = msg['size'];\n",
+ " if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
+ " fig._resize_canvas(size[0], size[1]);\n",
+ " fig.send_message(\"refresh\", {});\n",
+ " };\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
+ " var x0 = msg['x0'];\n",
+ " var y0 = fig.canvas.height - msg['y0'];\n",
+ " var x1 = msg['x1'];\n",
+ " var y1 = fig.canvas.height - msg['y1'];\n",
+ " x0 = Math.floor(x0) + 0.5;\n",
+ " y0 = Math.floor(y0) + 0.5;\n",
+ " x1 = Math.floor(x1) + 0.5;\n",
+ " y1 = Math.floor(y1) + 0.5;\n",
+ " var min_x = Math.min(x0, x1);\n",
+ " var min_y = Math.min(y0, y1);\n",
+ " var width = Math.abs(x1 - x0);\n",
+ " var height = Math.abs(y1 - y0);\n",
+ "\n",
+ " fig.rubberband_context.clearRect(\n",
+ " 0, 0, fig.canvas.width, fig.canvas.height);\n",
+ "\n",
+ " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
+ " // Updates the figure title.\n",
+ " fig.header.textContent = msg['label'];\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
+ " var cursor = msg['cursor'];\n",
+ " switch(cursor)\n",
+ " {\n",
+ " case 0:\n",
+ " cursor = 'pointer';\n",
+ " break;\n",
+ " case 1:\n",
+ " cursor = 'default';\n",
+ " break;\n",
+ " case 2:\n",
+ " cursor = 'crosshair';\n",
+ " break;\n",
+ " case 3:\n",
+ " cursor = 'move';\n",
+ " break;\n",
+ " }\n",
+ " fig.rubberband_canvas.style.cursor = cursor;\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
+ " fig.message.textContent = msg['message'];\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
+ " // Request the server to send over a new figure.\n",
+ " fig.send_draw_message();\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
+ " fig.image_mode = msg['mode'];\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function() {\n",
+ " // Called whenever the canvas gets updated.\n",
+ " this.send_message(\"ack\", {});\n",
+ "}\n",
+ "\n",
+ "// A function to construct a web socket function for onmessage handling.\n",
+ "// Called in the figure constructor.\n",
+ "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
+ " return function socket_on_message(evt) {\n",
+ " if (evt.data instanceof Blob) {\n",
+ " /* FIXME: We get \"Resource interpreted as Image but\n",
+ " * transferred with MIME type text/plain:\" errors on\n",
+ " * Chrome. But how to set the MIME type? It doesn't seem\n",
+ " * to be part of the websocket stream */\n",
+ " evt.data.type = \"image/png\";\n",
+ "\n",
+ " /* Free the memory for the previous frames */\n",
+ " if (fig.imageObj.src) {\n",
+ " (window.URL || window.webkitURL).revokeObjectURL(\n",
+ " fig.imageObj.src);\n",
+ " }\n",
+ "\n",
+ " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+ " evt.data);\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " }\n",
+ " else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
+ " fig.imageObj.src = evt.data;\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " var msg = JSON.parse(evt.data);\n",
+ " var msg_type = msg['type'];\n",
+ "\n",
+ " // Call the \"handle_{type}\" callback, which takes\n",
+ " // the figure and JSON message as its only arguments.\n",
+ " try {\n",
+ " var callback = fig[\"handle_\" + msg_type];\n",
+ " } catch (e) {\n",
+ " console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " if (callback) {\n",
+ " try {\n",
+ " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+ " callback(fig, msg);\n",
+ " } catch (e) {\n",
+ " console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
+ " }\n",
+ " }\n",
+ " };\n",
+ "}\n",
+ "\n",
+ "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+ "mpl.findpos = function(e) {\n",
+ " //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+ " var targ;\n",
+ " if (!e)\n",
+ " e = window.event;\n",
+ " if (e.target)\n",
+ " targ = e.target;\n",
+ " else if (e.srcElement)\n",
+ " targ = e.srcElement;\n",
+ " if (targ.nodeType == 3) // defeat Safari bug\n",
+ " targ = targ.parentNode;\n",
+ "\n",
+ " // jQuery normalizes the pageX and pageY\n",
+ " // pageX,Y are the mouse positions relative to the document\n",
+ " // offset() returns the position of the element relative to the document\n",
+ " var x = e.pageX - $(targ).offset().left;\n",
+ " var y = e.pageY - $(targ).offset().top;\n",
+ "\n",
+ " return {\"x\": x, \"y\": y};\n",
+ "};\n",
+ "\n",
+ "/*\n",
+ " * return a copy of an object with only non-object keys\n",
+ " * we need this to avoid circular references\n",
+ " * http://stackoverflow.com/a/24161582/3208463\n",
+ " */\n",
+ "function simpleKeys (original) {\n",
+ " return Object.keys(original).reduce(function (obj, key) {\n",
+ " if (typeof original[key] !== 'object')\n",
+ " obj[key] = original[key]\n",
+ " return obj;\n",
+ " }, {});\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.mouse_event = function(event, name) {\n",
+ " var canvas_pos = mpl.findpos(event)\n",
+ "\n",
+ " if (name === 'button_press')\n",
+ " {\n",
+ " this.canvas.focus();\n",
+ " this.canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " var x = canvas_pos.x;\n",
+ " var y = canvas_pos.y;\n",
+ "\n",
+ " this.send_message(name, {x: x, y: y, button: event.button,\n",
+ " step: event.step,\n",
+ " guiEvent: simpleKeys(event)});\n",
+ "\n",
+ " /* This prevents the web browser from automatically changing to\n",
+ " * the text insertion cursor when the button is pressed. We want\n",
+ " * to control all of the cursor setting manually through the\n",
+ " * 'cursor' event from matplotlib */\n",
+ " event.preventDefault();\n",
+ " return false;\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+ " // Handle any extra behaviour associated with a key event\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.key_event = function(event, name) {\n",
+ "\n",
+ " // Prevent repeat events\n",
+ " if (name == 'key_press')\n",
+ " {\n",
+ " if (event.which === this._key)\n",
+ " return;\n",
+ " else\n",
+ " this._key = event.which;\n",
+ " }\n",
+ " if (name == 'key_release')\n",
+ " this._key = null;\n",
+ "\n",
+ " var value = '';\n",
+ " if (event.ctrlKey && event.which != 17)\n",
+ " value += \"ctrl+\";\n",
+ " if (event.altKey && event.which != 18)\n",
+ " value += \"alt+\";\n",
+ " if (event.shiftKey && event.which != 16)\n",
+ " value += \"shift+\";\n",
+ "\n",
+ " value += 'k';\n",
+ " value += event.which.toString();\n",
+ "\n",
+ " this._key_event_extra(event, name);\n",
+ "\n",
+ " this.send_message(name, {key: value,\n",
+ " guiEvent: simpleKeys(event)});\n",
+ " return false;\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
+ " if (name == 'download') {\n",
+ " this.handle_save(this, null);\n",
+ " } else {\n",
+ " this.send_message(\"toolbar_button\", {name: name});\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
+ " this.message.textContent = tooltip;\n",
+ "};\n",
+ "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+ "\n",
+ "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
+ "\n",
+ "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
+ " // Create a \"websocket\"-like object which calls the given IPython comm\n",
+ " // object with the appropriate methods. Currently this is a non binary\n",
+ " // socket, so there is still some room for performance tuning.\n",
+ " var ws = {};\n",
+ "\n",
+ " ws.close = function() {\n",
+ " comm.close()\n",
+ " };\n",
+ " ws.send = function(m) {\n",
+ " //console.log('sending', m);\n",
+ " comm.send(m);\n",
+ " };\n",
+ " // Register the callback with on_msg.\n",
+ " comm.on_msg(function(msg) {\n",
+ " //console.log('receiving', msg['content']['data'], msg);\n",
+ " // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
+ " ws.onmessage(msg['content']['data'])\n",
+ " });\n",
+ " return ws;\n",
+ "}\n",
+ "\n",
+ "mpl.mpl_figure_comm = function(comm, msg) {\n",
+ " // This is the function which gets called when the mpl process\n",
+ " // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
+ "\n",
+ " var id = msg.content.data.id;\n",
+ " // Get hold of the div created by the display call when the Comm\n",
+ " // socket was opened in Python.\n",
+ " var element = $(\"#\" + id);\n",
+ " var ws_proxy = comm_websocket_adapter(comm)\n",
+ "\n",
+ " function ondownload(figure, format) {\n",
+ " window.open(figure.imageObj.src);\n",
+ " }\n",
+ "\n",
+ " var fig = new mpl.figure(id, ws_proxy,\n",
+ " ondownload,\n",
+ " element.get(0));\n",
+ "\n",
+ " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
+ " // web socket which is closed, not our websocket->open comm proxy.\n",
+ " ws_proxy.onopen();\n",
+ "\n",
+ " fig.parent_element = element.get(0);\n",
+ " fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
+ " if (!fig.cell_info) {\n",
+ " console.error(\"Failed to find cell for figure\", id, fig);\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " var output_index = fig.cell_info[2]\n",
+ " var cell = fig.cell_info[0];\n",
+ "\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
+ " fig.root.unbind('remove')\n",
+ "\n",
+ " // Update the output cell to use the data from the current canvas.\n",
+ " fig.push_to_output();\n",
+ " var dataURL = fig.canvas.toDataURL();\n",
+ " // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+ " // the notebook keyboard shortcuts fail.\n",
+ " IPython.keyboard_manager.enable()\n",
+ " $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
+ " fig.close_ws(fig, msg);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.close_ws = function(fig, msg){\n",
+ " fig.send_message('closing', msg);\n",
+ " // fig.ws.close()\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
+ " // Turn the data on the canvas into data in the output cell.\n",
+ " var dataURL = this.canvas.toDataURL();\n",
+ " this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function() {\n",
+ " // Tell IPython that the notebook contents must change.\n",
+ " IPython.notebook.set_dirty(true);\n",
+ " this.send_message(\"ack\", {});\n",
+ " var fig = this;\n",
+ " // Wait a second, then push the new image to the DOM so\n",
+ " // that it is saved nicely (might be nice to debounce this).\n",
+ " setTimeout(function () { fig.push_to_output() }, 1000);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function() {\n",
+ " var fig = this;\n",
+ "\n",
+ " var nav_element = $('<div/>')\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) { continue; };\n",
+ "\n",
+ " var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
+ " button.click(method_name, toolbar_event);\n",
+ " button.mouseover(tooltip, toolbar_mouse_event);\n",
+ " nav_element.append(button);\n",
+ " }\n",
+ "\n",
+ " // Add the status bar.\n",
+ " var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
+ " nav_element.append(status_bar);\n",
+ " this.message = status_bar[0];\n",
+ "\n",
+ " // Add the close button to the window.\n",
+ " var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
+ " var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
+ " button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
+ " button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
+ " buttongrp.append(button);\n",
+ " var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
+ " titlebar.prepend(buttongrp);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function(el){\n",
+ " var fig = this\n",
+ " el.on(\"remove\", function(){\n",
+ "\tfig.close_ws(fig, {});\n",
+ " });\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function(el){\n",
+ " // this is important to make the div 'focusable\n",
+ " el.attr('tabindex', 0)\n",
+ " // reach out to IPython and tell the keyboard manager to turn it's self\n",
+ " // off when our div gets focus\n",
+ "\n",
+ " // location in version 3\n",
+ " if (IPython.notebook.keyboard_manager) {\n",
+ " IPython.notebook.keyboard_manager.register_events(el);\n",
+ " }\n",
+ " else {\n",
+ " // location in version 2\n",
+ " IPython.keyboard_manager.register_events(el);\n",
+ " }\n",
+ "\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+ " var manager = IPython.notebook.keyboard_manager;\n",
+ " if (!manager)\n",
+ " manager = IPython.keyboard_manager;\n",
+ "\n",
+ " // Check for shift+enter\n",
+ " if (event.shiftKey && event.which == 13) {\n",
+ " this.canvas_div.blur();\n",
+ " event.shiftKey = false;\n",
+ " // Send a \"J\" for go to next cell\n",
+ " event.which = 74;\n",
+ " event.keyCode = 74;\n",
+ " manager.command_mode();\n",
+ " manager.handle_keydown(event);\n",
+ " }\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+ " fig.ondownload(fig, null);\n",
+ "}\n",
+ "\n",
+ "\n",
+ "mpl.find_output_cell = function(html_output) {\n",
+ " // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+ " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+ " // IPython event is triggered only after the cells have been serialised, which for\n",
+ " // our purposes (turning an active figure into a static one), is too late.\n",
+ " var cells = IPython.notebook.get_cells();\n",
+ " var ncells = cells.length;\n",
+ " for (var i=0; i<ncells; i++) {\n",
+ " var cell = cells[i];\n",
+ " if (cell.cell_type === 'code'){\n",
+ " for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
+ " var data = cell.output_area.outputs[j];\n",
+ " if (data.data) {\n",
+ " // IPython >= 3 moved mimebundle to data attribute of output\n",
+ " data = data.data;\n",
+ " }\n",
+ " if (data['text/html'] == html_output) {\n",
+ " return [cell, data, j];\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ "}\n",
+ "\n",
+ "// Register the function which deals with the matplotlib target/channel.\n",
+ "// The kernel may be null if the page has been refreshed.\n",
+ "if (IPython.notebook.kernel != null) {\n",
+ " IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
+ "}\n"
+ ],
+ "text/plain": [
+ "<IPython.core.display.Javascript object>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
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\">"
+ ],
+ "text/plain": [
+ "<IPython.core.display.HTML object>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "text/plain": [
+ "[<matplotlib.lines.Line2D at 0x7f5759b03ef0>]"
+ ]
+ },
+ "execution_count": 7,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "fig, ax = subplots(1,2,)\n",
+ "center = (edges[1:] + edges[:-1])/2.0 # this is the center of the bins \n",
+ "ax[1].imshow(log_img, cmap=\"inferno\")\n",
+ "ax[0].plot(center,his)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "The results are the same and the processing time is 6x faster. Hence, one can envisage realtime visualisation of images coming from detectors.\n",
+ "\n",
+ "## Investigation of the timings"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "\n",
+ "Profiling info for OpenCL ByteOffset\n",
+ " copy raw H -> D:\t1.048ms\n",
+ " memset mask:\t0.374ms\n",
+ " memset counter:\t0.006ms\n",
+ " mark exceptions:\t0.688ms\n",
+ " copy counter D -> H:\t0.003ms\n",
+ " treat_exceptions:\t0.122ms\n",
+ " double scan:\t1.672ms\n",
+ " copy_results:\t1.220ms\n",
+ "________________________________________________________________________________\n",
+ " Total execution time:\t5.132ms\n",
+ "\n",
+ "Profiling info for OpenCL ImageProcessing\n",
+ " copy D->D:\t3.041ms\n",
+ " max_min_stage1:\t0.873ms\n",
+ " max_min_stage2:\t0.009ms\n",
+ " histogram:\t0.775ms\n",
+ "________________________________________________________________________________\n",
+ " Total execution time:\t4.699ms\n"
+ ]
+ }
+ ],
+ "source": [
+ "ip.set_profiling(True)\n",
+ "bo.set_profiling(True)\n",
+ "ip.reset_log()\n",
+ "bo.reset_log()\n",
+ "raw = cbf.read(fname, only_raw=True)\n",
+ "dec = bo(raw, as_float=True)\n",
+ "ash(dec, res)\n",
+ "his, edges = ip.histogram(res, nbins, copy=False)\n",
+ "log_img = res.get()\n",
+ "import os\n",
+ "print(os.linesep.join(bo.log_profile()))\n",
+ "print(os.linesep.join(ip.log_profile()))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Conclusion\n",
+ "This notebook explains how to optimise some heavy numerical processing up to 10x speed-up for realtime image processing using GPU."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "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": "3.4.2"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/doc/source/Tutorials/Image.ipynb b/doc/source/Tutorials/Image.ipynb
new file mode 100644
index 0000000..5ddab38
--- /dev/null
+++ b/doc/source/Tutorials/Image.ipynb
@@ -0,0 +1,1873 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Image processing performance optimisation\n",
+ "\n",
+ "The idea of this tutorial is to give some suggestion how optimise image processing.\n",
+ "In the following example we decompress a CBF image from a Pilatus 6M, take the log-scale and calculate the histogram of pixel intensities before plotting. \n",
+ "This very simple operation takes >300ms, what makes it unpractical for live display of images coming from a detector. "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Populating the interactive namespace from numpy and matplotlib\n"
+ ]
+ }
+ ],
+ "source": [
+ "%pylab nbagg"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Using silx version 0.7.0-dev0\n",
+ "filename powder_200_2_0001.cbf\n"
+ ]
+ },
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "/users/kieffer/VirtualEnvs/py3/lib/python3.5/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
+ " from ._conv import register_converters as _register_converters\n"
+ ]
+ }
+ ],
+ "source": [
+ "import time, os\n",
+ "start_time = time.time()\n",
+ "import silx\n",
+ "print(\"Using silx version \",silx.version)\n",
+ "from silx.resources import ExternalResources\n",
+ "downloader = ExternalResources(\"pyFAI\", \"http://www.silx.org/pub/pyFAI/testimages\", \"PYFAI_DATA\")\n",
+ "fname = downloader.getfile(\"powder_200_2_0001.cbf\")\n",
+ "print(\"filename\", os.path.basename(fname))\n",
+ "import fabio\n",
+ "nbins = 1000"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "CPU times: user 252 ms, sys: 32 ms, total: 284 ms\n",
+ "Wall time: 280 ms\n"
+ ]
+ }
+ ],
+ "source": [
+ "%%time\n",
+ "\n",
+ "#Display an image and the histogram of values (in log scale)\n",
+ "img = fabio.open(fname).data\n",
+ "log_img = numpy.arcsinh(img) # arcsinh is well behaved log-like function\n",
+ "his, edges = numpy.histogram(log_img, nbins)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "application/javascript": [
+ "/* Put everything inside the global mpl namespace */\n",
+ "window.mpl = {};\n",
+ "\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 = $('<div/>');\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",
+ " if (mpl.ratio != 1) {\n",
+ " fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
+ " }\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",
+ " fig.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",
+ " '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
+ " 'ui-helper-clearfix\"/>');\n",
+ " var titletext = $(\n",
+ " '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
+ " 'text-align: center; padding: 3px;\"/>');\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 = $('<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 = $('<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 backingStore = this.context.backingStorePixelRatio ||\n",
+ "\tthis.context.webkitBackingStorePixelRatio ||\n",
+ "\tthis.context.mozBackingStorePixelRatio ||\n",
+ "\tthis.context.msBackingStorePixelRatio ||\n",
+ "\tthis.context.oBackingStorePixelRatio ||\n",
+ "\tthis.context.backingStorePixelRatio || 1;\n",
+ "\n",
+ " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
+ "\n",
+ " var rubberband = $('<canvas/>');\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 * mpl.ratio);\n",
+ " canvas.attr('height', height * mpl.ratio);\n",
+ " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\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 = $('<div/>')\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 = $('<button/>');\n",
+ " button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
+ " 'ui-button-icon-only');\n",
+ " button.attr('role', 'button');\n",
+ " button.attr('aria-disabled', 'false');\n",
+ " button.click(method_name, toolbar_event);\n",
+ " button.mouseover(tooltip, toolbar_mouse_event);\n",
+ "\n",
+ " var icon_img = $('<span/>');\n",
+ " icon_img.addClass('ui-button-icon-primary ui-icon');\n",
+ " icon_img.addClass(image);\n",
+ " icon_img.addClass('ui-corner-all');\n",
+ "\n",
+ " var tooltip_span = $('<span/>');\n",
+ " tooltip_span.addClass('ui-button-text');\n",
+ " tooltip_span.html(tooltip);\n",
+ "\n",
+ " button.append(icon_img);\n",
+ " button.append(tooltip_span);\n",
+ "\n",
+ " nav_element.append(button);\n",
+ " }\n",
+ "\n",
+ " var fmt_picker_span = $('<span/>');\n",
+ "\n",
+ " var fmt_picker = $('<select/>');\n",
+ " fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
+ " fmt_picker_span.append(fmt_picker);\n",
+ " nav_element.append(fmt_picker_span);\n",
+ " this.format_dropdown = fmt_picker[0];\n",
+ "\n",
+ " for (var ind in mpl.extensions) {\n",
+ " var fmt = mpl.extensions[ind];\n",
+ " var option = $(\n",
+ " '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
+ " fmt_picker.append(option)\n",
+ " }\n",
+ "\n",
+ " // Add hover states to the ui-buttons\n",
+ " $( \".ui-button\" ).hover(\n",
+ " function() { $(this).addClass(\"ui-state-hover\");},\n",
+ " function() { $(this).removeClass(\"ui-state-hover\");}\n",
+ " );\n",
+ "\n",
+ " var status_bar = $('<span class=\"mpl-message\"/>');\n",
+ " nav_element.append(status_bar);\n",
+ " this.message = status_bar[0];\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
+ " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+ " // which will in turn request a refresh of the image.\n",
+ " this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.send_message = function(type, properties) {\n",
+ " properties['type'] = type;\n",
+ " properties['figure_id'] = this.id;\n",
+ " this.ws.send(JSON.stringify(properties));\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.send_draw_message = function() {\n",
+ " if (!this.waiting) {\n",
+ " this.waiting = true;\n",
+ " this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
+ " }\n",
+ "}\n",
+ "\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+ " var format_dropdown = fig.format_dropdown;\n",
+ " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+ " fig.ondownload(fig, format);\n",
+ "}\n",
+ "\n",
+ "\n",
+ "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
+ " var size = msg['size'];\n",
+ " if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
+ " fig._resize_canvas(size[0], size[1]);\n",
+ " fig.send_message(\"refresh\", {});\n",
+ " };\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
+ " var x0 = msg['x0'] / mpl.ratio;\n",
+ " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
+ " var x1 = msg['x1'] / mpl.ratio;\n",
+ " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
+ " x0 = Math.floor(x0) + 0.5;\n",
+ " y0 = Math.floor(y0) + 0.5;\n",
+ " x1 = Math.floor(x1) + 0.5;\n",
+ " y1 = Math.floor(y1) + 0.5;\n",
+ " var min_x = Math.min(x0, x1);\n",
+ " var min_y = Math.min(y0, y1);\n",
+ " var width = Math.abs(x1 - x0);\n",
+ " var height = Math.abs(y1 - y0);\n",
+ "\n",
+ " fig.rubberband_context.clearRect(\n",
+ " 0, 0, fig.canvas.width, fig.canvas.height);\n",
+ "\n",
+ " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
+ " // Updates the figure title.\n",
+ " fig.header.textContent = msg['label'];\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
+ " var cursor = msg['cursor'];\n",
+ " switch(cursor)\n",
+ " {\n",
+ " case 0:\n",
+ " cursor = 'pointer';\n",
+ " break;\n",
+ " case 1:\n",
+ " cursor = 'default';\n",
+ " break;\n",
+ " case 2:\n",
+ " cursor = 'crosshair';\n",
+ " break;\n",
+ " case 3:\n",
+ " cursor = 'move';\n",
+ " break;\n",
+ " }\n",
+ " fig.rubberband_canvas.style.cursor = cursor;\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
+ " fig.message.textContent = msg['message'];\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
+ " // Request the server to send over a new figure.\n",
+ " fig.send_draw_message();\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
+ " fig.image_mode = msg['mode'];\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function() {\n",
+ " // Called whenever the canvas gets updated.\n",
+ " this.send_message(\"ack\", {});\n",
+ "}\n",
+ "\n",
+ "// A function to construct a web socket function for onmessage handling.\n",
+ "// Called in the figure constructor.\n",
+ "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
+ " return function socket_on_message(evt) {\n",
+ " if (evt.data instanceof Blob) {\n",
+ " /* FIXME: We get \"Resource interpreted as Image but\n",
+ " * transferred with MIME type text/plain:\" errors on\n",
+ " * Chrome. But how to set the MIME type? It doesn't seem\n",
+ " * to be part of the websocket stream */\n",
+ " evt.data.type = \"image/png\";\n",
+ "\n",
+ " /* Free the memory for the previous frames */\n",
+ " if (fig.imageObj.src) {\n",
+ " (window.URL || window.webkitURL).revokeObjectURL(\n",
+ " fig.imageObj.src);\n",
+ " }\n",
+ "\n",
+ " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+ " evt.data);\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " }\n",
+ " else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
+ " fig.imageObj.src = evt.data;\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " var msg = JSON.parse(evt.data);\n",
+ " var msg_type = msg['type'];\n",
+ "\n",
+ " // Call the \"handle_{type}\" callback, which takes\n",
+ " // the figure and JSON message as its only arguments.\n",
+ " try {\n",
+ " var callback = fig[\"handle_\" + msg_type];\n",
+ " } catch (e) {\n",
+ " console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " if (callback) {\n",
+ " try {\n",
+ " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+ " callback(fig, msg);\n",
+ " } catch (e) {\n",
+ " console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
+ " }\n",
+ " }\n",
+ " };\n",
+ "}\n",
+ "\n",
+ "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+ "mpl.findpos = function(e) {\n",
+ " //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+ " var targ;\n",
+ " if (!e)\n",
+ " e = window.event;\n",
+ " if (e.target)\n",
+ " targ = e.target;\n",
+ " else if (e.srcElement)\n",
+ " targ = e.srcElement;\n",
+ " if (targ.nodeType == 3) // defeat Safari bug\n",
+ " targ = targ.parentNode;\n",
+ "\n",
+ " // jQuery normalizes the pageX and pageY\n",
+ " // pageX,Y are the mouse positions relative to the document\n",
+ " // offset() returns the position of the element relative to the document\n",
+ " var x = e.pageX - $(targ).offset().left;\n",
+ " var y = e.pageY - $(targ).offset().top;\n",
+ "\n",
+ " return {\"x\": x, \"y\": y};\n",
+ "};\n",
+ "\n",
+ "/*\n",
+ " * return a copy of an object with only non-object keys\n",
+ " * we need this to avoid circular references\n",
+ " * http://stackoverflow.com/a/24161582/3208463\n",
+ " */\n",
+ "function simpleKeys (original) {\n",
+ " return Object.keys(original).reduce(function (obj, key) {\n",
+ " if (typeof original[key] !== 'object')\n",
+ " obj[key] = original[key]\n",
+ " return obj;\n",
+ " }, {});\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.mouse_event = function(event, name) {\n",
+ " var canvas_pos = mpl.findpos(event)\n",
+ "\n",
+ " if (name === 'button_press')\n",
+ " {\n",
+ " this.canvas.focus();\n",
+ " this.canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " var x = canvas_pos.x * mpl.ratio;\n",
+ " var y = canvas_pos.y * mpl.ratio;\n",
+ "\n",
+ " this.send_message(name, {x: x, y: y, button: event.button,\n",
+ " step: event.step,\n",
+ " guiEvent: simpleKeys(event)});\n",
+ "\n",
+ " /* This prevents the web browser from automatically changing to\n",
+ " * the text insertion cursor when the button is pressed. We want\n",
+ " * to control all of the cursor setting manually through the\n",
+ " * 'cursor' event from matplotlib */\n",
+ " event.preventDefault();\n",
+ " return false;\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+ " // Handle any extra behaviour associated with a key event\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.key_event = function(event, name) {\n",
+ "\n",
+ " // Prevent repeat events\n",
+ " if (name == 'key_press')\n",
+ " {\n",
+ " if (event.which === this._key)\n",
+ " return;\n",
+ " else\n",
+ " this._key = event.which;\n",
+ " }\n",
+ " if (name == 'key_release')\n",
+ " this._key = null;\n",
+ "\n",
+ " var value = '';\n",
+ " if (event.ctrlKey && event.which != 17)\n",
+ " value += \"ctrl+\";\n",
+ " if (event.altKey && event.which != 18)\n",
+ " value += \"alt+\";\n",
+ " if (event.shiftKey && event.which != 16)\n",
+ " value += \"shift+\";\n",
+ "\n",
+ " value += 'k';\n",
+ " value += event.which.toString();\n",
+ "\n",
+ " this._key_event_extra(event, name);\n",
+ "\n",
+ " this.send_message(name, {key: value,\n",
+ " guiEvent: simpleKeys(event)});\n",
+ " return false;\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
+ " if (name == 'download') {\n",
+ " this.handle_save(this, null);\n",
+ " } else {\n",
+ " this.send_message(\"toolbar_button\", {name: name});\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
+ " this.message.textContent = tooltip;\n",
+ "};\n",
+ "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+ "\n",
+ "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
+ "\n",
+ "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
+ " // Create a \"websocket\"-like object which calls the given IPython comm\n",
+ " // object with the appropriate methods. Currently this is a non binary\n",
+ " // socket, so there is still some room for performance tuning.\n",
+ " var ws = {};\n",
+ "\n",
+ " ws.close = function() {\n",
+ " comm.close()\n",
+ " };\n",
+ " ws.send = function(m) {\n",
+ " //console.log('sending', m);\n",
+ " comm.send(m);\n",
+ " };\n",
+ " // Register the callback with on_msg.\n",
+ " comm.on_msg(function(msg) {\n",
+ " //console.log('receiving', msg['content']['data'], msg);\n",
+ " // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
+ " ws.onmessage(msg['content']['data'])\n",
+ " });\n",
+ " return ws;\n",
+ "}\n",
+ "\n",
+ "mpl.mpl_figure_comm = function(comm, msg) {\n",
+ " // This is the function which gets called when the mpl process\n",
+ " // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
+ "\n",
+ " var id = msg.content.data.id;\n",
+ " // Get hold of the div created by the display call when the Comm\n",
+ " // socket was opened in Python.\n",
+ " var element = $(\"#\" + id);\n",
+ " var ws_proxy = comm_websocket_adapter(comm)\n",
+ "\n",
+ " function ondownload(figure, format) {\n",
+ " window.open(figure.imageObj.src);\n",
+ " }\n",
+ "\n",
+ " var fig = new mpl.figure(id, ws_proxy,\n",
+ " ondownload,\n",
+ " element.get(0));\n",
+ "\n",
+ " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
+ " // web socket which is closed, not our websocket->open comm proxy.\n",
+ " ws_proxy.onopen();\n",
+ "\n",
+ " fig.parent_element = element.get(0);\n",
+ " fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
+ " if (!fig.cell_info) {\n",
+ " console.error(\"Failed to find cell for figure\", id, fig);\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " var output_index = fig.cell_info[2]\n",
+ " var cell = fig.cell_info[0];\n",
+ "\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
+ " var width = fig.canvas.width/mpl.ratio\n",
+ " fig.root.unbind('remove')\n",
+ "\n",
+ " // Update the output cell to use the data from the current canvas.\n",
+ " fig.push_to_output();\n",
+ " var dataURL = fig.canvas.toDataURL();\n",
+ " // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+ " // the notebook keyboard shortcuts fail.\n",
+ " IPython.keyboard_manager.enable()\n",
+ " $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
+ " fig.close_ws(fig, msg);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.close_ws = function(fig, msg){\n",
+ " fig.send_message('closing', msg);\n",
+ " // fig.ws.close()\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
+ " // Turn the data on the canvas into data in the output cell.\n",
+ " var width = this.canvas.width/mpl.ratio\n",
+ " var dataURL = this.canvas.toDataURL();\n",
+ " this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function() {\n",
+ " // Tell IPython that the notebook contents must change.\n",
+ " IPython.notebook.set_dirty(true);\n",
+ " this.send_message(\"ack\", {});\n",
+ " var fig = this;\n",
+ " // Wait a second, then push the new image to the DOM so\n",
+ " // that it is saved nicely (might be nice to debounce this).\n",
+ " setTimeout(function () { fig.push_to_output() }, 1000);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function() {\n",
+ " var fig = this;\n",
+ "\n",
+ " var nav_element = $('<div/>')\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) { continue; };\n",
+ "\n",
+ " var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
+ " button.click(method_name, toolbar_event);\n",
+ " button.mouseover(tooltip, toolbar_mouse_event);\n",
+ " nav_element.append(button);\n",
+ " }\n",
+ "\n",
+ " // Add the status bar.\n",
+ " var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
+ " nav_element.append(status_bar);\n",
+ " this.message = status_bar[0];\n",
+ "\n",
+ " // Add the close button to the window.\n",
+ " var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
+ " var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
+ " button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
+ " button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
+ " buttongrp.append(button);\n",
+ " var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
+ " titlebar.prepend(buttongrp);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function(el){\n",
+ " var fig = this\n",
+ " el.on(\"remove\", function(){\n",
+ "\tfig.close_ws(fig, {});\n",
+ " });\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function(el){\n",
+ " // this is important to make the div 'focusable\n",
+ " el.attr('tabindex', 0)\n",
+ " // reach out to IPython and tell the keyboard manager to turn it's self\n",
+ " // off when our div gets focus\n",
+ "\n",
+ " // location in version 3\n",
+ " if (IPython.notebook.keyboard_manager) {\n",
+ " IPython.notebook.keyboard_manager.register_events(el);\n",
+ " }\n",
+ " else {\n",
+ " // location in version 2\n",
+ " IPython.keyboard_manager.register_events(el);\n",
+ " }\n",
+ "\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+ " var manager = IPython.notebook.keyboard_manager;\n",
+ " if (!manager)\n",
+ " manager = IPython.keyboard_manager;\n",
+ "\n",
+ " // Check for shift+enter\n",
+ " if (event.shiftKey && event.which == 13) {\n",
+ " this.canvas_div.blur();\n",
+ " event.shiftKey = false;\n",
+ " // Send a \"J\" for go to next cell\n",
+ " event.which = 74;\n",
+ " event.keyCode = 74;\n",
+ " manager.command_mode();\n",
+ " manager.handle_keydown(event);\n",
+ " }\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+ " fig.ondownload(fig, null);\n",
+ "}\n",
+ "\n",
+ "\n",
+ "mpl.find_output_cell = function(html_output) {\n",
+ " // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+ " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+ " // IPython event is triggered only after the cells have been serialised, which for\n",
+ " // our purposes (turning an active figure into a static one), is too late.\n",
+ " var cells = IPython.notebook.get_cells();\n",
+ " var ncells = cells.length;\n",
+ " for (var i=0; i<ncells; i++) {\n",
+ " var cell = cells[i];\n",
+ " if (cell.cell_type === 'code'){\n",
+ " for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
+ " var data = cell.output_area.outputs[j];\n",
+ " if (data.data) {\n",
+ " // IPython >= 3 moved mimebundle to data attribute of output\n",
+ " data = data.data;\n",
+ " }\n",
+ " if (data['text/html'] == html_output) {\n",
+ " return [cell, data, j];\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ "}\n",
+ "\n",
+ "// Register the function which deals with the matplotlib target/channel.\n",
+ "// The kernel may be null if the page has been refreshed.\n",
+ "if (IPython.notebook.kernel != null) {\n",
+ " IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
+ "}\n"
+ ],
+ "text/plain": [
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+ ]
+ },
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+ "output_type": "display_data"
+ },
+ {
+ "data": {
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\" width=\"639.8333142648146\">"
+ ],
+ "text/plain": [
+ "<IPython.core.display.HTML object>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "text/plain": [
+ "[<matplotlib.lines.Line2D at 0x7fdf03bb7cf8>]"
+ ]
+ },
+ "execution_count": 4,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "fig, ax = subplots(1,2,)\n",
+ "center = (edges[1:] + edges[:-1])/2.0 # this is the center of the bins \n",
+ "ax[1].imshow(log_img, cmap=\"inferno\")\n",
+ "ax[0].plot(center,his)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Optimised GPU code\n",
+ "\n",
+ "The code below prepares a GPU to be able to perform the same calculation as in the previous example.\n",
+ "\n",
+ "3 operations have to be carried out:\n",
+ "\n",
+ "* Decompress the CBF image\n",
+ "* Calculate the log scale (arcsinh values)\n",
+ "* Calculate the histogram\n",
+ "\n",
+ "Both can be performed on the GPU without additional memory transfer"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "#switch this to \"CPU\" to have a fail safe \n",
+ "devicetype = \"GPU\"\n",
+ "from silx.opencl.codec.byte_offset import ByteOffset\n",
+ "from silx.opencl.image import ImageProcessing\n",
+ "import pyopencl, pyopencl.array, pyopencl.elementwise\n",
+ "cbf = fabio.cbfimage.CbfImage()\n",
+ "bo = ByteOffset(os.path.getsize(fname), img.size, devicetype=devicetype)\n",
+ "ash = pyopencl.elementwise.ElementwiseKernel(bo.ctx, \n",
+ " arguments=\"float* data, float* res\", \n",
+ " operation=\"res[i] = asinh(data[i])\", \n",
+ " name='arcsinh_kernel')\n",
+ "ip = ImageProcessing(template=img, ctx=bo.ctx)\n",
+ "res = pyopencl.array.empty(bo.queue, img.shape, dtype=float32)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "CPU times: user 16 ms, sys: 16 ms, total: 32 ms\n",
+ "Wall time: 28.8 ms\n"
+ ]
+ }
+ ],
+ "source": [
+ "%%time \n",
+ "raw = cbf.read(fname, only_raw=True)\n",
+ "dec = bo(raw, as_float=True)\n",
+ "ash(dec, res)\n",
+ "his, edges = ip.histogram(res, nbins, copy=False)\n",
+ "log_img = res.get()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "application/javascript": [
+ "/* Put everything inside the global mpl namespace */\n",
+ "window.mpl = {};\n",
+ "\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 = $('<div/>');\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",
+ " if (mpl.ratio != 1) {\n",
+ " fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
+ " }\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",
+ " fig.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",
+ " '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
+ " 'ui-helper-clearfix\"/>');\n",
+ " var titletext = $(\n",
+ " '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
+ " 'text-align: center; padding: 3px;\"/>');\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 = $('<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 = $('<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 backingStore = this.context.backingStorePixelRatio ||\n",
+ "\tthis.context.webkitBackingStorePixelRatio ||\n",
+ "\tthis.context.mozBackingStorePixelRatio ||\n",
+ "\tthis.context.msBackingStorePixelRatio ||\n",
+ "\tthis.context.oBackingStorePixelRatio ||\n",
+ "\tthis.context.backingStorePixelRatio || 1;\n",
+ "\n",
+ " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
+ "\n",
+ " var rubberband = $('<canvas/>');\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 * mpl.ratio);\n",
+ " canvas.attr('height', height * mpl.ratio);\n",
+ " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\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 = $('<div/>')\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 = $('<button/>');\n",
+ " button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
+ " 'ui-button-icon-only');\n",
+ " button.attr('role', 'button');\n",
+ " button.attr('aria-disabled', 'false');\n",
+ " button.click(method_name, toolbar_event);\n",
+ " button.mouseover(tooltip, toolbar_mouse_event);\n",
+ "\n",
+ " var icon_img = $('<span/>');\n",
+ " icon_img.addClass('ui-button-icon-primary ui-icon');\n",
+ " icon_img.addClass(image);\n",
+ " icon_img.addClass('ui-corner-all');\n",
+ "\n",
+ " var tooltip_span = $('<span/>');\n",
+ " tooltip_span.addClass('ui-button-text');\n",
+ " tooltip_span.html(tooltip);\n",
+ "\n",
+ " button.append(icon_img);\n",
+ " button.append(tooltip_span);\n",
+ "\n",
+ " nav_element.append(button);\n",
+ " }\n",
+ "\n",
+ " var fmt_picker_span = $('<span/>');\n",
+ "\n",
+ " var fmt_picker = $('<select/>');\n",
+ " fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
+ " fmt_picker_span.append(fmt_picker);\n",
+ " nav_element.append(fmt_picker_span);\n",
+ " this.format_dropdown = fmt_picker[0];\n",
+ "\n",
+ " for (var ind in mpl.extensions) {\n",
+ " var fmt = mpl.extensions[ind];\n",
+ " var option = $(\n",
+ " '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
+ " fmt_picker.append(option)\n",
+ " }\n",
+ "\n",
+ " // Add hover states to the ui-buttons\n",
+ " $( \".ui-button\" ).hover(\n",
+ " function() { $(this).addClass(\"ui-state-hover\");},\n",
+ " function() { $(this).removeClass(\"ui-state-hover\");}\n",
+ " );\n",
+ "\n",
+ " var status_bar = $('<span class=\"mpl-message\"/>');\n",
+ " nav_element.append(status_bar);\n",
+ " this.message = status_bar[0];\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
+ " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+ " // which will in turn request a refresh of the image.\n",
+ " this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.send_message = function(type, properties) {\n",
+ " properties['type'] = type;\n",
+ " properties['figure_id'] = this.id;\n",
+ " this.ws.send(JSON.stringify(properties));\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.send_draw_message = function() {\n",
+ " if (!this.waiting) {\n",
+ " this.waiting = true;\n",
+ " this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
+ " }\n",
+ "}\n",
+ "\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+ " var format_dropdown = fig.format_dropdown;\n",
+ " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+ " fig.ondownload(fig, format);\n",
+ "}\n",
+ "\n",
+ "\n",
+ "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
+ " var size = msg['size'];\n",
+ " if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
+ " fig._resize_canvas(size[0], size[1]);\n",
+ " fig.send_message(\"refresh\", {});\n",
+ " };\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
+ " var x0 = msg['x0'] / mpl.ratio;\n",
+ " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
+ " var x1 = msg['x1'] / mpl.ratio;\n",
+ " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
+ " x0 = Math.floor(x0) + 0.5;\n",
+ " y0 = Math.floor(y0) + 0.5;\n",
+ " x1 = Math.floor(x1) + 0.5;\n",
+ " y1 = Math.floor(y1) + 0.5;\n",
+ " var min_x = Math.min(x0, x1);\n",
+ " var min_y = Math.min(y0, y1);\n",
+ " var width = Math.abs(x1 - x0);\n",
+ " var height = Math.abs(y1 - y0);\n",
+ "\n",
+ " fig.rubberband_context.clearRect(\n",
+ " 0, 0, fig.canvas.width, fig.canvas.height);\n",
+ "\n",
+ " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
+ " // Updates the figure title.\n",
+ " fig.header.textContent = msg['label'];\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
+ " var cursor = msg['cursor'];\n",
+ " switch(cursor)\n",
+ " {\n",
+ " case 0:\n",
+ " cursor = 'pointer';\n",
+ " break;\n",
+ " case 1:\n",
+ " cursor = 'default';\n",
+ " break;\n",
+ " case 2:\n",
+ " cursor = 'crosshair';\n",
+ " break;\n",
+ " case 3:\n",
+ " cursor = 'move';\n",
+ " break;\n",
+ " }\n",
+ " fig.rubberband_canvas.style.cursor = cursor;\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
+ " fig.message.textContent = msg['message'];\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
+ " // Request the server to send over a new figure.\n",
+ " fig.send_draw_message();\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
+ " fig.image_mode = msg['mode'];\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function() {\n",
+ " // Called whenever the canvas gets updated.\n",
+ " this.send_message(\"ack\", {});\n",
+ "}\n",
+ "\n",
+ "// A function to construct a web socket function for onmessage handling.\n",
+ "// Called in the figure constructor.\n",
+ "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
+ " return function socket_on_message(evt) {\n",
+ " if (evt.data instanceof Blob) {\n",
+ " /* FIXME: We get \"Resource interpreted as Image but\n",
+ " * transferred with MIME type text/plain:\" errors on\n",
+ " * Chrome. But how to set the MIME type? It doesn't seem\n",
+ " * to be part of the websocket stream */\n",
+ " evt.data.type = \"image/png\";\n",
+ "\n",
+ " /* Free the memory for the previous frames */\n",
+ " if (fig.imageObj.src) {\n",
+ " (window.URL || window.webkitURL).revokeObjectURL(\n",
+ " fig.imageObj.src);\n",
+ " }\n",
+ "\n",
+ " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+ " evt.data);\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " }\n",
+ " else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
+ " fig.imageObj.src = evt.data;\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " var msg = JSON.parse(evt.data);\n",
+ " var msg_type = msg['type'];\n",
+ "\n",
+ " // Call the \"handle_{type}\" callback, which takes\n",
+ " // the figure and JSON message as its only arguments.\n",
+ " try {\n",
+ " var callback = fig[\"handle_\" + msg_type];\n",
+ " } catch (e) {\n",
+ " console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " if (callback) {\n",
+ " try {\n",
+ " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+ " callback(fig, msg);\n",
+ " } catch (e) {\n",
+ " console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
+ " }\n",
+ " }\n",
+ " };\n",
+ "}\n",
+ "\n",
+ "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+ "mpl.findpos = function(e) {\n",
+ " //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+ " var targ;\n",
+ " if (!e)\n",
+ " e = window.event;\n",
+ " if (e.target)\n",
+ " targ = e.target;\n",
+ " else if (e.srcElement)\n",
+ " targ = e.srcElement;\n",
+ " if (targ.nodeType == 3) // defeat Safari bug\n",
+ " targ = targ.parentNode;\n",
+ "\n",
+ " // jQuery normalizes the pageX and pageY\n",
+ " // pageX,Y are the mouse positions relative to the document\n",
+ " // offset() returns the position of the element relative to the document\n",
+ " var x = e.pageX - $(targ).offset().left;\n",
+ " var y = e.pageY - $(targ).offset().top;\n",
+ "\n",
+ " return {\"x\": x, \"y\": y};\n",
+ "};\n",
+ "\n",
+ "/*\n",
+ " * return a copy of an object with only non-object keys\n",
+ " * we need this to avoid circular references\n",
+ " * http://stackoverflow.com/a/24161582/3208463\n",
+ " */\n",
+ "function simpleKeys (original) {\n",
+ " return Object.keys(original).reduce(function (obj, key) {\n",
+ " if (typeof original[key] !== 'object')\n",
+ " obj[key] = original[key]\n",
+ " return obj;\n",
+ " }, {});\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.mouse_event = function(event, name) {\n",
+ " var canvas_pos = mpl.findpos(event)\n",
+ "\n",
+ " if (name === 'button_press')\n",
+ " {\n",
+ " this.canvas.focus();\n",
+ " this.canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " var x = canvas_pos.x * mpl.ratio;\n",
+ " var y = canvas_pos.y * mpl.ratio;\n",
+ "\n",
+ " this.send_message(name, {x: x, y: y, button: event.button,\n",
+ " step: event.step,\n",
+ " guiEvent: simpleKeys(event)});\n",
+ "\n",
+ " /* This prevents the web browser from automatically changing to\n",
+ " * the text insertion cursor when the button is pressed. We want\n",
+ " * to control all of the cursor setting manually through the\n",
+ " * 'cursor' event from matplotlib */\n",
+ " event.preventDefault();\n",
+ " return false;\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+ " // Handle any extra behaviour associated with a key event\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.key_event = function(event, name) {\n",
+ "\n",
+ " // Prevent repeat events\n",
+ " if (name == 'key_press')\n",
+ " {\n",
+ " if (event.which === this._key)\n",
+ " return;\n",
+ " else\n",
+ " this._key = event.which;\n",
+ " }\n",
+ " if (name == 'key_release')\n",
+ " this._key = null;\n",
+ "\n",
+ " var value = '';\n",
+ " if (event.ctrlKey && event.which != 17)\n",
+ " value += \"ctrl+\";\n",
+ " if (event.altKey && event.which != 18)\n",
+ " value += \"alt+\";\n",
+ " if (event.shiftKey && event.which != 16)\n",
+ " value += \"shift+\";\n",
+ "\n",
+ " value += 'k';\n",
+ " value += event.which.toString();\n",
+ "\n",
+ " this._key_event_extra(event, name);\n",
+ "\n",
+ " this.send_message(name, {key: value,\n",
+ " guiEvent: simpleKeys(event)});\n",
+ " return false;\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
+ " if (name == 'download') {\n",
+ " this.handle_save(this, null);\n",
+ " } else {\n",
+ " this.send_message(\"toolbar_button\", {name: name});\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
+ " this.message.textContent = tooltip;\n",
+ "};\n",
+ "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+ "\n",
+ "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
+ "\n",
+ "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
+ " // Create a \"websocket\"-like object which calls the given IPython comm\n",
+ " // object with the appropriate methods. Currently this is a non binary\n",
+ " // socket, so there is still some room for performance tuning.\n",
+ " var ws = {};\n",
+ "\n",
+ " ws.close = function() {\n",
+ " comm.close()\n",
+ " };\n",
+ " ws.send = function(m) {\n",
+ " //console.log('sending', m);\n",
+ " comm.send(m);\n",
+ " };\n",
+ " // Register the callback with on_msg.\n",
+ " comm.on_msg(function(msg) {\n",
+ " //console.log('receiving', msg['content']['data'], msg);\n",
+ " // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
+ " ws.onmessage(msg['content']['data'])\n",
+ " });\n",
+ " return ws;\n",
+ "}\n",
+ "\n",
+ "mpl.mpl_figure_comm = function(comm, msg) {\n",
+ " // This is the function which gets called when the mpl process\n",
+ " // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
+ "\n",
+ " var id = msg.content.data.id;\n",
+ " // Get hold of the div created by the display call when the Comm\n",
+ " // socket was opened in Python.\n",
+ " var element = $(\"#\" + id);\n",
+ " var ws_proxy = comm_websocket_adapter(comm)\n",
+ "\n",
+ " function ondownload(figure, format) {\n",
+ " window.open(figure.imageObj.src);\n",
+ " }\n",
+ "\n",
+ " var fig = new mpl.figure(id, ws_proxy,\n",
+ " ondownload,\n",
+ " element.get(0));\n",
+ "\n",
+ " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
+ " // web socket which is closed, not our websocket->open comm proxy.\n",
+ " ws_proxy.onopen();\n",
+ "\n",
+ " fig.parent_element = element.get(0);\n",
+ " fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
+ " if (!fig.cell_info) {\n",
+ " console.error(\"Failed to find cell for figure\", id, fig);\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " var output_index = fig.cell_info[2]\n",
+ " var cell = fig.cell_info[0];\n",
+ "\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
+ " var width = fig.canvas.width/mpl.ratio\n",
+ " fig.root.unbind('remove')\n",
+ "\n",
+ " // Update the output cell to use the data from the current canvas.\n",
+ " fig.push_to_output();\n",
+ " var dataURL = fig.canvas.toDataURL();\n",
+ " // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+ " // the notebook keyboard shortcuts fail.\n",
+ " IPython.keyboard_manager.enable()\n",
+ " $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
+ " fig.close_ws(fig, msg);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.close_ws = function(fig, msg){\n",
+ " fig.send_message('closing', msg);\n",
+ " // fig.ws.close()\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
+ " // Turn the data on the canvas into data in the output cell.\n",
+ " var width = this.canvas.width/mpl.ratio\n",
+ " var dataURL = this.canvas.toDataURL();\n",
+ " this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function() {\n",
+ " // Tell IPython that the notebook contents must change.\n",
+ " IPython.notebook.set_dirty(true);\n",
+ " this.send_message(\"ack\", {});\n",
+ " var fig = this;\n",
+ " // Wait a second, then push the new image to the DOM so\n",
+ " // that it is saved nicely (might be nice to debounce this).\n",
+ " setTimeout(function () { fig.push_to_output() }, 1000);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function() {\n",
+ " var fig = this;\n",
+ "\n",
+ " var nav_element = $('<div/>')\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) { continue; };\n",
+ "\n",
+ " var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
+ " button.click(method_name, toolbar_event);\n",
+ " button.mouseover(tooltip, toolbar_mouse_event);\n",
+ " nav_element.append(button);\n",
+ " }\n",
+ "\n",
+ " // Add the status bar.\n",
+ " var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
+ " nav_element.append(status_bar);\n",
+ " this.message = status_bar[0];\n",
+ "\n",
+ " // Add the close button to the window.\n",
+ " var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
+ " var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
+ " button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
+ " button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
+ " buttongrp.append(button);\n",
+ " var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
+ " titlebar.prepend(buttongrp);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function(el){\n",
+ " var fig = this\n",
+ " el.on(\"remove\", function(){\n",
+ "\tfig.close_ws(fig, {});\n",
+ " });\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function(el){\n",
+ " // this is important to make the div 'focusable\n",
+ " el.attr('tabindex', 0)\n",
+ " // reach out to IPython and tell the keyboard manager to turn it's self\n",
+ " // off when our div gets focus\n",
+ "\n",
+ " // location in version 3\n",
+ " if (IPython.notebook.keyboard_manager) {\n",
+ " IPython.notebook.keyboard_manager.register_events(el);\n",
+ " }\n",
+ " else {\n",
+ " // location in version 2\n",
+ " IPython.keyboard_manager.register_events(el);\n",
+ " }\n",
+ "\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+ " var manager = IPython.notebook.keyboard_manager;\n",
+ " if (!manager)\n",
+ " manager = IPython.keyboard_manager;\n",
+ "\n",
+ " // Check for shift+enter\n",
+ " if (event.shiftKey && event.which == 13) {\n",
+ " this.canvas_div.blur();\n",
+ " event.shiftKey = false;\n",
+ " // Send a \"J\" for go to next cell\n",
+ " event.which = 74;\n",
+ " event.keyCode = 74;\n",
+ " manager.command_mode();\n",
+ " manager.handle_keydown(event);\n",
+ " }\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+ " fig.ondownload(fig, null);\n",
+ "}\n",
+ "\n",
+ "\n",
+ "mpl.find_output_cell = function(html_output) {\n",
+ " // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+ " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+ " // IPython event is triggered only after the cells have been serialised, which for\n",
+ " // our purposes (turning an active figure into a static one), is too late.\n",
+ " var cells = IPython.notebook.get_cells();\n",
+ " var ncells = cells.length;\n",
+ " for (var i=0; i<ncells; i++) {\n",
+ " var cell = cells[i];\n",
+ " if (cell.cell_type === 'code'){\n",
+ " for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
+ " var data = cell.output_area.outputs[j];\n",
+ " if (data.data) {\n",
+ " // IPython >= 3 moved mimebundle to data attribute of output\n",
+ " data = data.data;\n",
+ " }\n",
+ " if (data['text/html'] == html_output) {\n",
+ " return [cell, data, j];\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ "}\n",
+ "\n",
+ "// Register the function which deals with the matplotlib target/channel.\n",
+ "// The kernel may be null if the page has been refreshed.\n",
+ "if (IPython.notebook.kernel != null) {\n",
+ " IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
+ "}\n"
+ ],
+ "text/plain": [
+ "<IPython.core.display.Javascript object>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "text/html": [
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\" width=\"639.8333142648146\">"
+ ],
+ "text/plain": [
+ "<IPython.core.display.HTML object>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "text/plain": [
+ "[<matplotlib.lines.Line2D at 0x7fdebd059390>]"
+ ]
+ },
+ "execution_count": 7,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "fig, ax = subplots(1,2,)\n",
+ "center = (edges[1:] + edges[:-1])/2.0 # this is the center of the bins \n",
+ "ax[1].imshow(log_img, cmap=\"inferno\")\n",
+ "ax[0].plot(center,his)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "The results are the same and the processing time is 6x faster. Hence, one can envisage realtime visualisation of images coming from detectors.\n",
+ "\n",
+ "## Investigation of the timings"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "\n",
+ "Profiling info for OpenCL ByteOffset\n",
+ " copy raw H -> D:\t0.972ms\n",
+ " memset mask:\t0.091ms\n",
+ " memset counter:\t0.005ms\n",
+ " mark exceptions:\t0.092ms\n",
+ " copy counter D -> H:\t0.002ms\n",
+ " treat_exceptions:\t0.027ms\n",
+ " double scan:\t0.200ms\n",
+ " copy_results:\t0.141ms\n",
+ "________________________________________________________________________________\n",
+ " Total execution time:\t1.530ms\n",
+ "\n",
+ "Profiling info for OpenCL ImageProcessing\n",
+ " copy D->D :\t0.104ms\n",
+ " max_min_stage1:\t0.069ms\n",
+ " max_min_stage2:\t0.009ms\n",
+ " histogram:\t0.098ms\n",
+ "________________________________________________________________________________\n",
+ " Total execution time:\t0.281ms\n"
+ ]
+ }
+ ],
+ "source": [
+ "ip.set_profiling(True)\n",
+ "bo.set_profiling(True)\n",
+ "ip.reset_log()\n",
+ "bo.reset_log()\n",
+ "raw = cbf.read(fname, only_raw=True)\n",
+ "dec = bo(raw, as_float=True)\n",
+ "ash(dec, res)\n",
+ "his, edges = ip.histogram(res, nbins, copy=False)\n",
+ "log_img = res.get()\n",
+ "import os\n",
+ "print(os.linesep.join(bo.log_profile()))\n",
+ "print(os.linesep.join(ip.log_profile()))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Conclusion\n",
+ "This notebook explains how to optimise some heavy numerical processing up to 10x speed-up for realtime image processing using GPU."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "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": "3.4.2"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/doc/source/Tutorials/Sift/.ipynb_checkpoints/sift-checkpoint.ipynb b/doc/source/Tutorials/Sift/.ipynb_checkpoints/sift-checkpoint.ipynb
new file mode 100644
index 0000000..f6544c1
--- /dev/null
+++ b/doc/source/Tutorials/Sift/.ipynb_checkpoints/sift-checkpoint.ipynb
@@ -0,0 +1,4248 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# SIFT image alignment tutorial\n",
+ "\n",
+ "SIFT (Scale-Invariant Feature Transform) is an algorithm developped by David Lowe in 1999. \n",
+ "It is a worldwide reference for image alignment and object recognition. \n",
+ "The robustness of this method enables to detect features at different scales, angles and illumination of a scene. \n",
+ "\n",
+ "Silx provides an implementation of SIFT in OpenCL, meaning that it can run on Graphics Processing Units and Central Processing Units as well. \n",
+ "Interest points are detected in the image, then data structures called *descriptors* are built to be characteristic of the scene, so that two different images of the same scene have similar descriptors. \n",
+ "They are robust to transformations like translation, rotation, rescaling and illumination change, which make SIFT interesting for image stitching. \n",
+ "\n",
+ "In the fist stage, descriptors are computed from the input images. \n",
+ "Then, they are compared to determine the geometric transformation to apply in order to align the images. \n",
+ "This implementation can run on most graphic cards and CPU, making it usable on many setups. \n",
+ "OpenCL processes are handled from Python with PyOpenCL, a module to access OpenCL parallel computation API.\n",
+ "\n",
+ "This tutuorial explains the three subsequent steps:\n",
+ "\n",
+ "* keypoint extraction\n",
+ "* Keypoint matching\n",
+ "* image alignment\n",
+ "\n",
+ "All the tutorial has been made using the Jupyter notebook."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Populating the interactive namespace from numpy and matplotlib\n"
+ ]
+ }
+ ],
+ "source": [
+ "import time\n",
+ "start_time = time.time()\n",
+ "%pylab nbagg"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Silx version 0.8.0-dev0\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 = $('<div/>');\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",
+ " '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
+ " 'ui-helper-clearfix\"/>');\n",
+ " var titletext = $(\n",
+ " '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
+ " 'text-align: center; padding: 3px;\"/>');\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 = $('<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 = $('<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 = $('<canvas/>');\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 = $('<div/>')\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 = $('<button/>');\n",
+ " button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
+ " 'ui-button-icon-only');\n",
+ " button.attr('role', 'button');\n",
+ " button.attr('aria-disabled', 'false');\n",
+ " button.click(method_name, toolbar_event);\n",
+ " button.mouseover(tooltip, toolbar_mouse_event);\n",
+ "\n",
+ " var icon_img = $('<span/>');\n",
+ " icon_img.addClass('ui-button-icon-primary ui-icon');\n",
+ " icon_img.addClass(image);\n",
+ " icon_img.addClass('ui-corner-all');\n",
+ "\n",
+ " var tooltip_span = $('<span/>');\n",
+ " tooltip_span.addClass('ui-button-text');\n",
+ " tooltip_span.html(tooltip);\n",
+ "\n",
+ " button.append(icon_img);\n",
+ " button.append(tooltip_span);\n",
+ "\n",
+ " nav_element.append(button);\n",
+ " }\n",
+ "\n",
+ " var fmt_picker_span = $('<span/>');\n",
+ "\n",
+ " var fmt_picker = $('<select/>');\n",
+ " fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
+ " fmt_picker_span.append(fmt_picker);\n",
+ " nav_element.append(fmt_picker_span);\n",
+ " this.format_dropdown = fmt_picker[0];\n",
+ "\n",
+ " for (var ind in mpl.extensions) {\n",
+ " var fmt = mpl.extensions[ind];\n",
+ " var option = $(\n",
+ " '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
+ " fmt_picker.append(option)\n",
+ " }\n",
+ "\n",
+ " // Add hover states to the ui-buttons\n",
+ " $( \".ui-button\" ).hover(\n",
+ " function() { $(this).addClass(\"ui-state-hover\");},\n",
+ " function() { $(this).removeClass(\"ui-state-hover\");}\n",
+ " );\n",
+ "\n",
+ " var status_bar = $('<span class=\"mpl-message\"/>');\n",
+ " nav_element.append(status_bar);\n",
+ " this.message = status_bar[0];\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
+ " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+ " // which will in turn request a refresh of the image.\n",
+ " this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.send_message = function(type, properties) {\n",
+ " properties['type'] = type;\n",
+ " properties['figure_id'] = this.id;\n",
+ " this.ws.send(JSON.stringify(properties));\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.send_draw_message = function() {\n",
+ " if (!this.waiting) {\n",
+ " this.waiting = true;\n",
+ " this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
+ " }\n",
+ "}\n",
+ "\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+ " var format_dropdown = fig.format_dropdown;\n",
+ " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+ " fig.ondownload(fig, format);\n",
+ "}\n",
+ "\n",
+ "\n",
+ "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
+ " var size = msg['size'];\n",
+ " if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
+ " fig._resize_canvas(size[0], size[1]);\n",
+ " fig.send_message(\"refresh\", {});\n",
+ " };\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
+ " var x0 = msg['x0'];\n",
+ " var y0 = fig.canvas.height - msg['y0'];\n",
+ " var x1 = msg['x1'];\n",
+ " var y1 = fig.canvas.height - msg['y1'];\n",
+ " x0 = Math.floor(x0) + 0.5;\n",
+ " y0 = Math.floor(y0) + 0.5;\n",
+ " x1 = Math.floor(x1) + 0.5;\n",
+ " y1 = Math.floor(y1) + 0.5;\n",
+ " var min_x = Math.min(x0, x1);\n",
+ " var min_y = Math.min(y0, y1);\n",
+ " var width = Math.abs(x1 - x0);\n",
+ " var height = Math.abs(y1 - y0);\n",
+ "\n",
+ " fig.rubberband_context.clearRect(\n",
+ " 0, 0, fig.canvas.width, fig.canvas.height);\n",
+ "\n",
+ " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
+ " // Updates the figure title.\n",
+ " fig.header.textContent = msg['label'];\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
+ " var cursor = msg['cursor'];\n",
+ " switch(cursor)\n",
+ " {\n",
+ " case 0:\n",
+ " cursor = 'pointer';\n",
+ " break;\n",
+ " case 1:\n",
+ " cursor = 'default';\n",
+ " break;\n",
+ " case 2:\n",
+ " cursor = 'crosshair';\n",
+ " break;\n",
+ " case 3:\n",
+ " cursor = 'move';\n",
+ " break;\n",
+ " }\n",
+ " fig.rubberband_canvas.style.cursor = cursor;\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
+ " fig.message.textContent = msg['message'];\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
+ " // Request the server to send over a new figure.\n",
+ " fig.send_draw_message();\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
+ " fig.image_mode = msg['mode'];\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function() {\n",
+ " // Called whenever the canvas gets updated.\n",
+ " this.send_message(\"ack\", {});\n",
+ "}\n",
+ "\n",
+ "// A function to construct a web socket function for onmessage handling.\n",
+ "// Called in the figure constructor.\n",
+ "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
+ " return function socket_on_message(evt) {\n",
+ " if (evt.data instanceof Blob) {\n",
+ " /* FIXME: We get \"Resource interpreted as Image but\n",
+ " * transferred with MIME type text/plain:\" errors on\n",
+ " * Chrome. But how to set the MIME type? It doesn't seem\n",
+ " * to be part of the websocket stream */\n",
+ " evt.data.type = \"image/png\";\n",
+ "\n",
+ " /* Free the memory for the previous frames */\n",
+ " if (fig.imageObj.src) {\n",
+ " (window.URL || window.webkitURL).revokeObjectURL(\n",
+ " fig.imageObj.src);\n",
+ " }\n",
+ "\n",
+ " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+ " evt.data);\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " }\n",
+ " else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
+ " fig.imageObj.src = evt.data;\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " var msg = JSON.parse(evt.data);\n",
+ " var msg_type = msg['type'];\n",
+ "\n",
+ " // Call the \"handle_{type}\" callback, which takes\n",
+ " // the figure and JSON message as its only arguments.\n",
+ " try {\n",
+ " var callback = fig[\"handle_\" + msg_type];\n",
+ " } catch (e) {\n",
+ " console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " if (callback) {\n",
+ " try {\n",
+ " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+ " callback(fig, msg);\n",
+ " } catch (e) {\n",
+ " console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
+ " }\n",
+ " }\n",
+ " };\n",
+ "}\n",
+ "\n",
+ "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+ "mpl.findpos = function(e) {\n",
+ " //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+ " var targ;\n",
+ " if (!e)\n",
+ " e = window.event;\n",
+ " if (e.target)\n",
+ " targ = e.target;\n",
+ " else if (e.srcElement)\n",
+ " targ = e.srcElement;\n",
+ " if (targ.nodeType == 3) // defeat Safari bug\n",
+ " targ = targ.parentNode;\n",
+ "\n",
+ " // jQuery normalizes the pageX and pageY\n",
+ " // pageX,Y are the mouse positions relative to the document\n",
+ " // offset() returns the position of the element relative to the document\n",
+ " var x = e.pageX - $(targ).offset().left;\n",
+ " var y = e.pageY - $(targ).offset().top;\n",
+ "\n",
+ " return {\"x\": x, \"y\": y};\n",
+ "};\n",
+ "\n",
+ "/*\n",
+ " * return a copy of an object with only non-object keys\n",
+ " * we need this to avoid circular references\n",
+ " * http://stackoverflow.com/a/24161582/3208463\n",
+ " */\n",
+ "function simpleKeys (original) {\n",
+ " return Object.keys(original).reduce(function (obj, key) {\n",
+ " if (typeof original[key] !== 'object')\n",
+ " obj[key] = original[key]\n",
+ " return obj;\n",
+ " }, {});\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.mouse_event = function(event, name) {\n",
+ " var canvas_pos = mpl.findpos(event)\n",
+ "\n",
+ " if (name === 'button_press')\n",
+ " {\n",
+ " this.canvas.focus();\n",
+ " this.canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " var x = canvas_pos.x;\n",
+ " var y = canvas_pos.y;\n",
+ "\n",
+ " this.send_message(name, {x: x, y: y, button: event.button,\n",
+ " step: event.step,\n",
+ " guiEvent: simpleKeys(event)});\n",
+ "\n",
+ " /* This prevents the web browser from automatically changing to\n",
+ " * the text insertion cursor when the button is pressed. We want\n",
+ " * to control all of the cursor setting manually through the\n",
+ " * 'cursor' event from matplotlib */\n",
+ " event.preventDefault();\n",
+ " return false;\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+ " // Handle any extra behaviour associated with a key event\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.key_event = function(event, name) {\n",
+ "\n",
+ " // Prevent repeat events\n",
+ " if (name == 'key_press')\n",
+ " {\n",
+ " if (event.which === this._key)\n",
+ " return;\n",
+ " else\n",
+ " this._key = event.which;\n",
+ " }\n",
+ " if (name == 'key_release')\n",
+ " this._key = null;\n",
+ "\n",
+ " var value = '';\n",
+ " if (event.ctrlKey && event.which != 17)\n",
+ " value += \"ctrl+\";\n",
+ " if (event.altKey && event.which != 18)\n",
+ " value += \"alt+\";\n",
+ " if (event.shiftKey && event.which != 16)\n",
+ " value += \"shift+\";\n",
+ "\n",
+ " value += 'k';\n",
+ " value += event.which.toString();\n",
+ "\n",
+ " this._key_event_extra(event, name);\n",
+ "\n",
+ " this.send_message(name, {key: value,\n",
+ " guiEvent: simpleKeys(event)});\n",
+ " return false;\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
+ " if (name == 'download') {\n",
+ " this.handle_save(this, null);\n",
+ " } else {\n",
+ " this.send_message(\"toolbar_button\", {name: name});\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
+ " this.message.textContent = tooltip;\n",
+ "};\n",
+ "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+ "\n",
+ "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
+ "\n",
+ "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
+ " // Create a \"websocket\"-like object which calls the given IPython comm\n",
+ " // object with the appropriate methods. Currently this is a non binary\n",
+ " // socket, so there is still some room for performance tuning.\n",
+ " var ws = {};\n",
+ "\n",
+ " ws.close = function() {\n",
+ " comm.close()\n",
+ " };\n",
+ " ws.send = function(m) {\n",
+ " //console.log('sending', m);\n",
+ " comm.send(m);\n",
+ " };\n",
+ " // Register the callback with on_msg.\n",
+ " comm.on_msg(function(msg) {\n",
+ " //console.log('receiving', msg['content']['data'], msg);\n",
+ " // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
+ " ws.onmessage(msg['content']['data'])\n",
+ " });\n",
+ " return ws;\n",
+ "}\n",
+ "\n",
+ "mpl.mpl_figure_comm = function(comm, msg) {\n",
+ " // This is the function which gets called when the mpl process\n",
+ " // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
+ "\n",
+ " var id = msg.content.data.id;\n",
+ " // Get hold of the div created by the display call when the Comm\n",
+ " // socket was opened in Python.\n",
+ " var element = $(\"#\" + id);\n",
+ " var ws_proxy = comm_websocket_adapter(comm)\n",
+ "\n",
+ " function ondownload(figure, format) {\n",
+ " window.open(figure.imageObj.src);\n",
+ " }\n",
+ "\n",
+ " var fig = new mpl.figure(id, ws_proxy,\n",
+ " ondownload,\n",
+ " element.get(0));\n",
+ "\n",
+ " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
+ " // web socket which is closed, not our websocket->open comm proxy.\n",
+ " ws_proxy.onopen();\n",
+ "\n",
+ " fig.parent_element = element.get(0);\n",
+ " fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
+ " if (!fig.cell_info) {\n",
+ " console.error(\"Failed to find cell for figure\", id, fig);\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " var output_index = fig.cell_info[2]\n",
+ " var cell = fig.cell_info[0];\n",
+ "\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
+ " fig.root.unbind('remove')\n",
+ "\n",
+ " // Update the output cell to use the data from the current canvas.\n",
+ " fig.push_to_output();\n",
+ " var dataURL = fig.canvas.toDataURL();\n",
+ " // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+ " // the notebook keyboard shortcuts fail.\n",
+ " IPython.keyboard_manager.enable()\n",
+ " $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
+ " fig.close_ws(fig, msg);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.close_ws = function(fig, msg){\n",
+ " fig.send_message('closing', msg);\n",
+ " // fig.ws.close()\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
+ " // Turn the data on the canvas into data in the output cell.\n",
+ " var dataURL = this.canvas.toDataURL();\n",
+ " this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function() {\n",
+ " // Tell IPython that the notebook contents must change.\n",
+ " IPython.notebook.set_dirty(true);\n",
+ " this.send_message(\"ack\", {});\n",
+ " var fig = this;\n",
+ " // Wait a second, then push the new image to the DOM so\n",
+ " // that it is saved nicely (might be nice to debounce this).\n",
+ " setTimeout(function () { fig.push_to_output() }, 1000);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function() {\n",
+ " var fig = this;\n",
+ "\n",
+ " var nav_element = $('<div/>')\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) { continue; };\n",
+ "\n",
+ " var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
+ " button.click(method_name, toolbar_event);\n",
+ " button.mouseover(tooltip, toolbar_mouse_event);\n",
+ " nav_element.append(button);\n",
+ " }\n",
+ "\n",
+ " // Add the status bar.\n",
+ " var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
+ " nav_element.append(status_bar);\n",
+ " this.message = status_bar[0];\n",
+ "\n",
+ " // Add the close button to the window.\n",
+ " var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
+ " var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
+ " button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
+ " button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
+ " buttongrp.append(button);\n",
+ " var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
+ " titlebar.prepend(buttongrp);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function(el){\n",
+ " var fig = this\n",
+ " el.on(\"remove\", function(){\n",
+ "\tfig.close_ws(fig, {});\n",
+ " });\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function(el){\n",
+ " // this is important to make the div 'focusable\n",
+ " el.attr('tabindex', 0)\n",
+ " // reach out to IPython and tell the keyboard manager to turn it's self\n",
+ " // off when our div gets focus\n",
+ "\n",
+ " // location in version 3\n",
+ " if (IPython.notebook.keyboard_manager) {\n",
+ " IPython.notebook.keyboard_manager.register_events(el);\n",
+ " }\n",
+ " else {\n",
+ " // location in version 2\n",
+ " IPython.keyboard_manager.register_events(el);\n",
+ " }\n",
+ "\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+ " var manager = IPython.notebook.keyboard_manager;\n",
+ " if (!manager)\n",
+ " manager = IPython.keyboard_manager;\n",
+ "\n",
+ " // Check for shift+enter\n",
+ " if (event.shiftKey && event.which == 13) {\n",
+ " this.canvas_div.blur();\n",
+ " event.shiftKey = false;\n",
+ " // Send a \"J\" for go to next cell\n",
+ " event.which = 74;\n",
+ " event.keyCode = 74;\n",
+ " manager.command_mode();\n",
+ " manager.handle_keydown(event);\n",
+ " }\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+ " fig.ondownload(fig, null);\n",
+ "}\n",
+ "\n",
+ "\n",
+ "mpl.find_output_cell = function(html_output) {\n",
+ " // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+ " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+ " // IPython event is triggered only after the cells have been serialised, which for\n",
+ " // our purposes (turning an active figure into a static one), is too late.\n",
+ " var cells = IPython.notebook.get_cells();\n",
+ " var ncells = cells.length;\n",
+ " for (var i=0; i<ncells; i++) {\n",
+ " var cell = cells[i];\n",
+ " if (cell.cell_type === 'code'){\n",
+ " for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
+ " var data = cell.output_area.outputs[j];\n",
+ " if (data.data) {\n",
+ " // IPython >= 3 moved mimebundle to data attribute of output\n",
+ " data = data.data;\n",
+ " }\n",
+ " if (data['text/html'] == html_output) {\n",
+ " return [cell, data, j];\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ "}\n",
+ "\n",
+ "// Register the function which deals with the matplotlib target/channel.\n",
+ "// The kernel may be null if the page has been refreshed.\n",
+ "if (IPython.notebook.kernel != null) {\n",
+ " IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
+ "}\n"
+ ],
+ "text/plain": [
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+ },
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+ "output_type": "display_data"
+ },
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