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Add missing trailing parts to ipython notebooks
The conversion apparently wasnt 100% OK for all of them
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‎ipython/A_Numerical_Agnostic_Pyrex_Class.ipynb‎

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{
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"metadata": {
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"name": ""
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"name": "",
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"signature": "sha256:b664ac2ba452bc821ed4bfb4cb72116ee81b6c75ed2a481b7f029ba2cb13d901"
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},
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"nbformat": 3,
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"nbformat_minor": 0,
@@ -14,6 +15,8 @@
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"A numerical agnostic pyrex class\n",
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"======================================================================\n",
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"\n",
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"TAGS: Outdated\n",
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"\n",
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"**NOTE**: This entry was last updated 2006-11-04 and contains information\n",
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"that is not relevant today (as of 2013).\n",
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"\n",
@@ -284,6 +287,19 @@
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"language": "python",
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"metadata": {},
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"outputs": []
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"You can check the output here [test_output.txt](files/attachments/A_Numerical_Agnostic_Pyrex_Class/test_output.txt)\n",
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"\n",
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"See also\n",
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"--------\n",
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"\n",
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"* [\"Cookbook/Pyrex_and_NumPy\"]\n",
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"* [\"Cookbook/ArrayStruct_and_Pyrex\"] (The inspiring recipe)"
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]
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}
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],
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"metadata": {}

‎ipython/ApplyFIRFilter.ipynb‎

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{
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"metadata": {
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"name": ""
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"name": "",
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"signature": "sha256:b0f70faf76804e4e892dd86a863469122a6da843e126603581d892b1be8e2cd6"
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},
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"nbformat": 3,
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"nbformat_minor": 0,
@@ -268,6 +269,15 @@
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}
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],
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"prompt_number": 7
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"The plot shows that, depending on the number of taps, either scipy.ndimage.convolve1d,\n",
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"numpy.convolve or scipy.signal.fftconvolve is the fastest.\n",
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"The above script can be used to explore variations of these results."
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]
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}
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],
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"metadata": {}

‎ipython/ArrayStruct_and_Pyrex.ipynb‎

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{
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"metadata": {
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"name": ""
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"name": "",
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"signature": "sha256:c41ba98ca104eacba3468a716753a5977634547e66a51d7cb307161ae332cf4f"
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},
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"nbformat": 3,
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"nbformat_minor": 0,
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"language": "python",
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"metadata": {},
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"outputs": []
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Using data malloced elsewhere with a Pyrex-based extension\n",
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"\n",
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"One example is the get_data_copy() function of [_cam_iface_shm.pyx](http://code.astraw.com/projects/motmot/browser/trunk/cam_iface/src/_cam_iface_shm.pyx) in the [motmot camera utilities](http://code.astraw.com/projects/motmot) software. In this use example, an image is copied from shared memory into an externally malloced buffer supporting the {{{__array_struct__}}} interface. (The shared memory stuff has only been tested on linux, but the rest should work anywhere.)\n",
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"\n",
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"## See also\n",
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"\n",
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"* [\"Cookbook/Pyrex_and_NumPy\"]"
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]
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}
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],
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"metadata": {}

‎ipython/Ctypes.ipynb‎

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{
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"metadata": {
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"signature": "sha256:a72aa5d8dedcdcc4089b11f8e274e756008cf38d29a1c9d3fcdd1cc100b8d9bb"
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"signature": "sha256:24cb988253a312e3cca7456b080408ad758f6480f7b8d486135d4df298c66c27"
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},
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"nbformat": 3,
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"nbformat_minor": 0,
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"language": "python",
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"metadata": {},
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"outputs": []
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Pertinent Mailing List Threads\n",
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"\n",
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"Some useful threads on the ctypes-users mailing list:\n",
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"\n",
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" * [http://aspn.activestate.com/ASPN/Mail/Message/ctypes-users/3119087 IndexError when indexing on POINTER(POINTER(ctype))]\n",
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" * [http://aspn.activestate.com/ASPN/Mail/Message/ctypes-users/3118513 Adding ctypes support to NumPy]\n",
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" * [http://aspn.activestate.com/ASPN/Mail/Message/ctypes-users/3118656 Determining if a ctype is a pointer type (was RE: Adding ctypes support to NumPy)]\n",
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" * [http://aspn.activestate.com/ASPN/Mail/Message/ctypes-users/3117306 Check for NULL pointer without ValueError]\n",
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" * [http://aspn.activestate.com/ASPN/Mail/Message/ctypes-users/3205951 Problem with callbacks from C into Python]\n",
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" * [http://thread.gmane.org/gmane.comp.python.numeric.general/7418\\ ctypes and ndpointer]\n",
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" * [http://thread.gmane.org/gmane.comp.python.ctypes/3116 Problems with 64 signed integer]\n",
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"\n",
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"Thomas Heller's answers are particularly insightful.\n",
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"\n",
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"## Documentation\n",
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" * [http://starship.python.net/crew/theller/ctypes/tutorial.html ctypes tutorial]\n",
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" * [http://docs.python.org/dev/lib/module-ctypes.html 13.14 ctypes -- A foreign function library for Python.]"
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]
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}
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],
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"metadata": {}

‎ipython/F2Py.ipynb‎

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{
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"metadata": {
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"signature": "sha256:9430bc0c224d76c77db34576e6dbd7bb429b0ac1b2fb0837ad69c28bf3bf99c7"
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"signature": "sha256:627a3e6ccb2a6a4c222372198ad3e4d7a2417c1e1963f9606a53230a6bc3c907"
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},
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"nbformat": 3,
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"language": "python",
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"metadata": {},
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"outputs": []
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"A more complicated example about\n",
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"how to wrap routines for band matrices can be found at\n",
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"http://www.physik.tu-dresden.de/~baecker/comp_talks.html\n",
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"under \"Python and Co - some recent developments\".\n",
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"\n",
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"## Wrapping a simple C code\n",
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"\n",
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"f2py is also capable of handling C code. An example is found on the wiki: [\"Cookbook/f2py_and_NumPy\"].\n",
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"\n",
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"## Step by step wrapping of a simple numerical code: Interactive System for Ice sheet Simulation\n",
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"http://websrv.cs.umt.edu/isis/index.php/F2py_example"
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]
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}
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],
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"metadata": {}

‎ipython/FortranIO.ipynb‎

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{
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"metadata": {
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"signature": "sha256:011ea24e425b0a177275dd9aac8a7020e516017102e4a8179bc91ae81dea5d14"
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"signature": "sha256:a915964a56fadb1a14820eea93bbab3d8f15d0a6b29f5af10c377fb2c0d6bb1a"
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},
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"nbformat": 3,
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"language": "python",
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"metadata": {},
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"outputs": []
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"This example is designed to read [http://www.atnf.csiro.au/research/pulsar/tempo/ref_man_sections/output.txt a file] output \n",
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"by [http://www.atnf.csiro.au/research/pulsar/tempo/ TEMPO].\n",
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"Most of the fields, \"TOA\" up to \"preres_s\", are fields that are present and of interest in the file. The field \"pad3\" \n",
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"is either an undocumented addition to the file format or some kind of padding (it is always zero in my test file). The \n",
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"FORTRAN unformatted I/O adds the fields \"pad1\" and \"pad2\". Each should contain the length, in bytes, of each record (so the \n",
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"presence of the extra \"pad3\" field could be deduced). This code ignores t"
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]
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}
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],
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"metadata": {}

‎ipython/Indexing.ipynb‎

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{
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"metadata": {
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"signature": "sha256:b1854052b8a9a14f17e436056c38f82e4fd7391edc25d1da84132d91d0a6daea"
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"signature": "sha256:f71aa5c594c36f0b4aaf7097997e21d8fc4e922497e816c79bdc338e838e2c2b"
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"language": "python",
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"metadata": {},
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"outputs": []
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Array-like objects\n",
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"numpy and scipy provide a few other types that behave like arrays, in particular matrices and sparse matrices. Their indexing can differ from that of arrays in surprising ways.\n"
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]
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}
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],
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"metadata": {}

‎ipython/Intersection.ipynb‎

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{
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"metadata": {
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"signature": "sha256:a6392fdd52819a32188f6c671958a91df2239d78df53c3abca6e2dc1e35f3f9b"
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"signature": "sha256:3f8271dce541086cbbf0b841b2f2612eaeaf2f13eace057d9454676f3b365e27"
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},
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}
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],
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"prompt_number": 2
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"See also: http://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.fsolve.html#scipy.optimize.fsolve"
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]
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}
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],
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"metadata": {}

‎ipython/KDTree_example.ipynb‎

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"metadata": {
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"signature": "sha256:d802157eab6f42af73afc5ed8a4c0b4bde8d2b803a8c1febb31d46a67d68986c"
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],
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"language": "python",
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"cell_type": "markdown",
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],
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"ename": "IndexError",
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"evalue": "too many indices",
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"output_type": "pyerr",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mIndexError\u001b[0m Traceback (most recent call last)",
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"\u001b[0;32m<ipython-input-11-ee19bc143f1b>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 12\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0m__name__\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'__main__'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 13\u001b[0m \u001b[0mt0\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mclock\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 14\u001b[0;31m \u001b[0mtest\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 15\u001b[0m \u001b[0mt1\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mclock\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 16\u001b[0m \u001b[0;32mprint\u001b[0m \u001b[0;34m\"Elapsed time %.2f seconds\"\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0mt1\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0mt0\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;32m<ipython-input-11-ee19bc143f1b>\u001b[0m in \u001b[0;36mtest\u001b[0;34m()\u001b[0m\n\u001b[1;32m 8\u001b[0m \u001b[0mndim\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m12\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 9\u001b[0m \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m10\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mnumpy\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrandom\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrand\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mndata\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mndim\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreshape\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mndim\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mndata\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 10\u001b[0;31m \u001b[0mknn_search\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mK\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 11\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 12\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0m__name__\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'__main__'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;32m<ipython-input-8-f929dee5eaf0>\u001b[0m in \u001b[0;36mknn_search\u001b[0;34m(data, K)\u001b[0m\n\u001b[1;32m 8\u001b[0m \u001b[0midx\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnumpy\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mndata\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 9\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mnumpy\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mndata\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 10\u001b[0;31m \u001b[0m_knn\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mquadratic_knn_search\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0midx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mK\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# see above\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 11\u001b[0m \u001b[0mknn\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m \u001b[0m_knn\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 12\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mknn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;32m<ipython-input-7-622010d98eb1>\u001b[0m in \u001b[0;36mquadratic_knn_search\u001b[0;34m(data, lidx, ldata, K)\u001b[0m\n\u001b[1;32m 23\u001b[0m \u001b[0mK\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mK\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mK\u001b[0m \u001b[0;34m<\u001b[0m \u001b[0mndata\u001b[0m \u001b[0;32melse\u001b[0m \u001b[0mndata\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 24\u001b[0m \u001b[0mretval\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 25\u001b[0;31m \u001b[0msqd\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mldata\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0mndata\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msum\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# data.reshape((param,1)).repeat(ndata, axis=1);\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 26\u001b[0m \u001b[0midx\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnumpy\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0margsort\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msqd\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkind\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'mergesort'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 27\u001b[0m \u001b[0midx\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0midx\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0mK\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;31mIndexError\u001b[0m: too many indices"
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]
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}
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],
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"prompt_number": 11
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"outputs": []
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},
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{
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"cell_type": "code",

‎ipython/LASReader.ipynb‎

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{
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"metadata": {},
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"metadata": {
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"signature": "sha256:42da1643b7a565667c9798296135f6f3e596ecd72721fd193a4e88fd06ea067d"
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},
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"nbformat": 3,
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"nbformat_minor": 0,
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"worksheets": [
@@ -460,9 +462,22 @@
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"language": "python",
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"metadata": {},
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"outputs": []
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"It creates the following plot:\n",
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"\n",
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"[sample3plot.png](files/attachments/LASReader/sample3plot.png)\n",
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"\n",
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"The sample LAS file is here:\n",
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"\n",
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"[sample3.las](files/attachments/LASReader/sample3.las)\n"
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]
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}
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],
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"metadata": {}
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}
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]
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}
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}

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