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Forked from daletovar/gcxs_blogpost_take2.ipynb
Last active December 30, 2020 23:51
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def task_data():
"download the sample data"
return dict(actions=["wget https://docs.google.com/uc?id=1rkoE_xoUN7YMefnUcJ-LXAlI5gU8qYLv&export=download -O test_FA.nii.gz".split()], targets=["test_FA.nii.gz"])
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# multi dimensional sparse datasets in python"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"_pictures of sparse matrices_"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Sparsity is a feature of data structures in scientific computing. Sparse data structures consist mostly of the same repeated value, typically zero. Sparse matrix implementations focus on the representations of the non-repeated values to speed up storage and runtime. This post discusses the relationship between sparse implementation using [`scipy.sparse`][scipy.sparse] and [`sparse`][sparse]. We'll demonstrate how the `sparse` library extends sparse representations to N-D data structures when [`scipy.sparse`][scipy.sparse] is strictly limited to 2-D shapes.\n",
"\n",
"[scipy.sparse]: https://docs.scipy.org/doc/scipy/reference/sparse.html\n",
"[sparse]: https://sparse.pydata.org/en/stable/"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
" import sparse, scipy.sparse"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"There are [different forms that represent sparse matrices](https://en.wikipedia.org/wiki/Sparse_matrix#Storing_a_sparse_matrix) that are commonly shorted with acronyms.: \n",
"\n",
"* dictionary of keys (DOK)\n",
"* compressed sparse column (CSC)\n",
"* compressed sparse row (CSR)\n",
"* coordinate list (COO)\n",
"\n",
"Each of these are available in the `scipy.sparse` library. "
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
" scipy.sparse.dok_matrix, scipy.sparse.csc_matrix, scipy.sparse.csr_matrix, scipy.sparse.coo_matrix;"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Alone any of them can encode 2-D sparse matrices, but that is where they stop, and `sparse` picks up. recently, `sparse` added the GCXS format that provides n-dimensional sparse data structures by combining the DOK and COO sparse forms. The objects created by `sparse` comply with the standard `numpy.ndarray` interface and provide element-wise operations, reductions, dot and tensordot operations. `sparse` is compatible with `xarray` and `dask`."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Sparse neurological images.\n",
"\n",
"MRI data in neuroimaging has sparse form, and has more than 2 dimensions. The standard Montreal Neurological Institute space (MNI152) is a benchmark dataset with the dimensions (91, 109, 91).\n",
"\n",
"Neuroimaging analysis is a burgeoning community in the scientific python ecosystem, and we use their tooling to load and plot data. Below, we load the `mri` data with `nibabel` and plot two different realizations of the `mri` data."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 475.2x187.2 with 4 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 475.2x187.2 with 4 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
" import nilearn.plotting, nibabel\n",
" mri = nibabel.load('test_FA.nii.gz')\n",
" nilearn.plotting.plot_anat(mri.slicer[...,0]), nilearn.plotting.plot_anat(mri.slicer[...,1]);"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"A summary of the shape of the `mri` data."
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'mri has the shape (91, 109, 91, 16) and it is 68% sparse.'"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
" F\"\"\"mri has the shape {mri.shape} and it is {\n",
" int((mri.get_fdata() == 0).ravel().mean() *100)\n",
" }% sparse.\"\"\""
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The shape of the `mri` data exceeds the ability of the `scipy.sparse` We'll use the `sparse` library's GCXS format which can handle high dimensional datasets like our `mri` data."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"In the code below we cast the `mri` data to a `sparse._compressed.GCXS` that is capable of a high degrees of compression for N-dimensional datatsets. The object representation describes features of the sparse matrix."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<table><tbody><tr><th style=\"text-align: left\">Format</th><td style=\"text-align: left\">gcxs</td></tr><tr><th style=\"text-align: left\">Data Type</th><td style=\"text-align: left\">float64</td></tr><tr><th style=\"text-align: left\">Shape</th><td style=\"text-align: left\">(91, 109, 91, 16)</td></tr><tr><th style=\"text-align: left\">nnz</th><td style=\"text-align: left\">4597231</td></tr><tr><th style=\"text-align: left\">Density</th><td style=\"text-align: left\">0.31832229797624495</td></tr><tr><th style=\"text-align: left\">Read-only</th><td style=\"text-align: left\">True</td></tr><tr><th style=\"text-align: left\">Size</th><td style=\"text-align: left\">70.1M</td></tr><tr><th style=\"text-align: left\">Storage ratio</th><td style=\"text-align: left\">0.6</td></tr><tr><th style=\"text-align: left\">Compressed Axes</th><td style=\"text-align: left\">(3,)</td></tr></tbody></table>"
],
"text/plain": [
"<GCXS: shape=(91, 109, 91, 16), dtype=float64, nnz=4597231, fill_value=0.0, compressed_axes=(3,)>"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
" data = sparse._compressed.GCXS.from_numpy(mri.get_fdata(), compressed_axes=[3]); data"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We can operate on the GXCS dataset like any `numpy.ndarray`. For example, we take the mean along the third axis below."
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
" mean = data.mean(axis=3)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The `mean` feature can be projected onto the `mri` to reveal different patterns in the images. Below we mask a dataset shown into a density plot with different thresholds."
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 525.6x187.2 with 5 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 525.6x187.2 with 5 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
" dense, header = mean.todense(), mri.header\n",
" header['cal_min'], header['cal_max'] = mean.min(), mean.max()\n",
" nilearn.plotting.plot_stat_map(\n",
" nibabel.Nifti1Image(dense, header=header, affine=mri.affine)\n",
" );\n",
" dense[dense<.2] = 0\n",
" nilearn.plotting.plot_stat_map(\n",
" nibabel.Nifti1Image(dense, header=header, affine=mri.affine)\n",
" );"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Sparse singular value decomposition with `scipy`"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Singular value decomposition is a critical procedure for a lot of data analytics applications. Using `sparse` arrays alongside `scipy` makes this procedure feel natural. Similar to generating \"eigen faces,\" with the SVD we can look at the low-rank structure of our data and visualize \"eigen brains,\" possibly to denoise the data or examine structure, but mostly for fun."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Singular value decomposition requires that we fold the sparse into a new shape. Otherwise we raise an error."
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
" try: scipy.sparse.linalg.svds(data, 15)\n",
" except ValueError: ..."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"A singular value decomposition can now operate on the `folded` 2-D form."
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
" folded = sparse._compressed.GCXS(\n",
" (data.data, data.indices, data.indptr),\n",
" shape=data._compressed_shape[::-1], \n",
" compressed_axes=[1])\n",
"\n",
" U, S, Vᵀ = scipy.sparse.linalg.svds(folded, 15)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"\n",
"\n",
"The columns of `U` hold the dominant spatial patterns of the data. We can reshape these vectors and project them onto brains:\n"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 525.6x187.2 with 5 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 525.6x187.2 with 5 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 525.6x187.2 with 5 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"for i in range(3):\n",
" image = U[:,i].reshape((91,109,91))\n",
" header['cal_min'], header['cal_max'] = image.min(), image.max()\n",
" brain = nibabel.Nifti1Image(image, header=header, affine=mri.affine)\n",
" nilearn.plotting.plot_stat_map(brain)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Conclusion\n",
"\n",
"Problems involving sparsity are pervasive in scientific computing. Efficiently storing and manipulating large sparse arrays requires thoughtful storage formats. In an ecosystem where more and more libraries emulate and interact with NumPy, it's important that sparse arrays be compatable, especially with libraries like Dask, for predictablity of behavior and scalability. Pydata/sparse arrays offer these features. Each storage format offers different advantages. Because GCXS is identical to CSR/CSC for two-dimensional arrays, it is primed to work effectively in all the libraries that expect CSR/CSC. It also excels in the same areas as CSR/CSC; namely in fast matrix multiplication. Above and beyond this, GCXS offers good compression for high-dimensional arrays.\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Appendix\n",
"\n",
"### Deep dive in the GXCS object"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Understanding how GCXS works requires first understanding how the CSR/CSC model works for matrices. For a CSR matrix, we store three arrays: the nonzero data, the indices corresponding the columns of each of the each the nonzero data, and an array of integers that point to where each row begins in the indices array."
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"import sparse, numpy, pandas, scipy.sparse, nibabel, nilearn\n",
"__import__(\"warnings\").filterwarnings('ignore')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To demonstrate `sparse` usage we'll between with a random 5x5 CSR matrix"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"matrix = sparse.random((5,5), density=.2, format='gcxs')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"`sparse` objects provide descriptions of the sparsity."
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<table><tbody><tr><th style=\"text-align: left\">Format</th><td style=\"text-align: left\">gcxs</td></tr><tr><th style=\"text-align: left\">Data Type</th><td style=\"text-align: left\">float64</td></tr><tr><th style=\"text-align: left\">Shape</th><td style=\"text-align: left\">(5, 5)</td></tr><tr><th style=\"text-align: left\">nnz</th><td style=\"text-align: left\">5</td></tr><tr><th style=\"text-align: left\">Density</th><td style=\"text-align: left\">0.2</td></tr><tr><th style=\"text-align: left\">Read-only</th><td style=\"text-align: left\">True</td></tr><tr><th style=\"text-align: left\">Size</th><td style=\"text-align: left\">128</td></tr><tr><th style=\"text-align: left\">Storage ratio</th><td style=\"text-align: left\">0.6</td></tr><tr><th style=\"text-align: left\">Compressed Axes</th><td style=\"text-align: left\">(0,)</td></tr></tbody></table>"
],
"text/plain": [
"<GCXS: shape=(5, 5), dtype=float64, nnz=5, fill_value=0.0, compressed_axes=(0,)>"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"matrix"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The `matrix` can be turned into a dense `numpy.ndarray`"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([[0. , 0. , 0. , 0. , 0. ],\n",
" [0. , 0. , 0. , 0. , 0.6618865 ],\n",
" [0. , 0.76018912, 0. , 0. , 0. ],\n",
" [0.24542568, 0. , 0. , 0.08408683, 0.97623756],\n",
" [0. , 0. , 0. , 0. , 0. ]])"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"matrix.todense()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The `matrix` is represented by row-major ordered `matrix.data`"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"As we can see, the data is sorted in row-major ordering:"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([0.6618865 , 0.76018912, 0.24542568, 0.08408683, 0.97623756])"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"matrix.data"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"where each value corresponds to column labelled by `matrix.indices`"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The indices store which columns have nonzeros:"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([4, 1, 0, 3, 4])"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"matrix.indices"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"and the index pointer allows mapping into rows"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(2, 5)"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"matrix.indptr[3],matrix.indptr[4]"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The nonzero columns of row 1 []\n",
"The nonzero columns of row 2 [4]\n",
"The nonzero columns of row 3 [1]\n",
"The nonzero columns of row 4 [0 3 4]\n",
"The nonzero columns of row 5 []\n"
]
}
],
"source": [
"for i in range(5): print(\n",
" \"The nonzero columns of row %s \" %(i+1), \n",
" matrix.indices[\n",
" matrix.indptr[i]:matrix.indptr[i+1] \n",
" ]\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The CSC data structure uses the same idea but stores the data in column-major ordering:"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<table><tbody><tr><th style=\"text-align: left\">Format</th><td style=\"text-align: left\">gcxs</td></tr><tr><th style=\"text-align: left\">Data Type</th><td style=\"text-align: left\">float64</td></tr><tr><th style=\"text-align: left\">Shape</th><td style=\"text-align: left\">(5, 5)</td></tr><tr><th style=\"text-align: left\">nnz</th><td style=\"text-align: left\">5</td></tr><tr><th style=\"text-align: left\">Density</th><td style=\"text-align: left\">0.2</td></tr><tr><th style=\"text-align: left\">Read-only</th><td style=\"text-align: left\">True</td></tr><tr><th style=\"text-align: left\">Size</th><td style=\"text-align: left\">128</td></tr><tr><th style=\"text-align: left\">Storage ratio</th><td style=\"text-align: left\">0.6</td></tr><tr><th style=\"text-align: left\">Compressed Axes</th><td style=\"text-align: left\">(1,)</td></tr></tbody></table>"
],
"text/plain": [
"<GCXS: shape=(5, 5), dtype=float64, nnz=5, fill_value=0.0, compressed_axes=(1,)>"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"b = matrix.change_compressed_axes([1])\n",
"b"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([[0. , 0. , 0. , 0. , 0. ],\n",
" [0. , 0. , 0. , 0. , 0.6618865 ],\n",
" [0. , 0.76018912, 0. , 0. , 0. ],\n",
" [0.24542568, 0. , 0. , 0.08408683, 0.97623756],\n",
" [0. , 0. , 0. , 0. , 0. ]])"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"b.todense()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now the data is sorted in column-major form:"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([0.24542568, 0.76018912, 0.08408683, 0.6618865 , 0.97623756])"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"b.data"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The 'indices' array now stores the rows of the nonzero values:"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([3, 2, 3, 1, 3])"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"b.indices"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"And now the index pointer array tells us which of the rows in 'indices' correspond to what column:"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([0, 1, 2, 2, 3, 5])"
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"b.indptr"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The nonzero rows of column 0 [3]\n",
"The nonzero rows of column 1 [2]\n",
"The nonzero rows of column 2 []\n",
"The nonzero rows of column 3 [3]\n",
"The nonzero rows of column 4 [1 3]\n"
]
}
],
"source": [
"for i in range(5):\n",
" print(\"The nonzero rows of column %s \" %(i), b.indices[b.indptr[i]:b.indptr[i+1]])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"For GCXS, CSR and CSC can be thought of as the same data structure, but with a different compressed axis. For CSR the first axis (rows) are compressed whereas for CSC the second axis (columns) are compressed."
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"((0,), (1,))"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"matrix.compressed_axes, b.compressed_axes"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The way we can work with arrays of higher dimensions using this kind of scheme is by transposing axes and reshaping the original array into a two-dimensional array and applying the same methods. We transpose the axes to put the compressed axes first and the reshape the array to two dimensions with the resulting shape: (product of compressed axes, product of uncompressed axes). For a 3x4x5 array, if we compress the first axis then we will store a CSR matrix with a shape of (3, 4x5=20)."
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [],
"source": [
"x = sparse.random((3,4,5), density=.2, format='gcxs')"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(3, 20)"
]
},
"execution_count": 27,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"x._compressed_shape"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"If we compress the second axis, then we transpose the array and reshape it into a (4, 3x5=15) matrix."
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(4, 15)"
]
},
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"x.change_compressed_axes([1])._compressed_shape"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We can also compress multiple axes:"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(15, 4)"
]
},
"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"x.change_compressed_axes([0,2])._compressed_shape"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Different choices in compressed axes affects the degree of compression and the speed of certain operations, especially indexing. Like CSR/CSC, the storage demands are determined by the size of the compressed axes and the number of nonzeros. Because the storage demands of a GCXS array are not dependent on the number of dimensions of the array, GCXS compresses well even with high dimensional arrays. The best compression is achieved by compressing the smallest axis:"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>compressed_axes</th>\n",
" <th>percent_compression</th>\n",
" <th>compressed_shape</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>[0]</td>\n",
" <td>30.003429</td>\n",
" <td>(5, 35000)</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>[1]</td>\n",
" <td>30.012000</td>\n",
" <td>(20, 8750)</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>[2]</td>\n",
" <td>30.020571</td>\n",
" <td>(35, 5000)</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>[3]</td>\n",
" <td>30.029143</td>\n",
" <td>(50, 3500)</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>[0, 1]</td>\n",
" <td>30.057714</td>\n",
" <td>(100, 1750)</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>[0, 2]</td>\n",
" <td>30.100571</td>\n",
" <td>(175, 1000)</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>[0, 3]</td>\n",
" <td>30.143429</td>\n",
" <td>(250, 700)</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>[1, 2]</td>\n",
" <td>30.400571</td>\n",
" <td>(700, 250)</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>[1, 3]</td>\n",
" <td>30.572000</td>\n",
" <td>(1000, 175)</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>[2, 3]</td>\n",
" <td>31.000571</td>\n",
" <td>(1750, 100)</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>[0, 1, 2]</td>\n",
" <td>32.000571</td>\n",
" <td>(3500, 50)</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>[0, 2, 3]</td>\n",
" <td>35.000571</td>\n",
" <td>(8750, 20)</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>[1, 2, 3]</td>\n",
" <td>50.000571</td>\n",
" <td>(35000, 5)</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" compressed_axes percent_compression compressed_shape\n",
"0 [0] 30.003429 (5, 35000)\n",
"1 [1] 30.012000 (20, 8750)\n",
"2 [2] 30.020571 (35, 5000)\n",
"3 [3] 30.029143 (50, 3500)\n",
"4 [0, 1] 30.057714 (100, 1750)\n",
"5 [0, 2] 30.100571 (175, 1000)\n",
"6 [0, 3] 30.143429 (250, 700)\n",
"7 [1, 2] 30.400571 (700, 250)\n",
"8 [1, 3] 30.572000 (1000, 175)\n",
"9 [2, 3] 31.000571 (1750, 100)\n",
"10 [0, 1, 2] 32.000571 (3500, 50)\n",
"11 [0, 2, 3] 35.000571 (8750, 20)\n",
"12 [1, 2, 3] 50.000571 (35000, 5)"
]
},
"execution_count": 30,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"y = sparse.random((5,20,35,50), density=.15, format='gcxs')\n",
"axes = ([0], [1], [2], [3], [0,1], \n",
" [0,2], [0,3], [1,2], \n",
" [1,3], [2,3], [0,1,2],\n",
" [0,2,3], [1,2,3])\n",
"percent_stored = []\n",
"shapes = []\n",
"for axis in axes:\n",
" y = y.change_compressed_axes(axis)\n",
" percent_stored.append(y.nbytes/(numpy.prod(y.shape)*y.dtype.itemsize) *100)\n",
" shapes.append(y._compressed_shape)\n",
" #print('compressed axes: %s compression ratio: %s ' %(axis, y.nbytes/(np.prod(y.shape)*y.dtype.itemsize) *100),\n",
" # 'shape of underlying matrix: ', y._compressed_shape)\n",
"df = pandas.DataFrame()\n",
"df['compressed_axes'] = axes\n",
"df['percent_compression'] = percent_stored\n",
"df['compressed_shape'] = shapes\n",
"df"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"As we can see, compressing the three largest axes together gets the worst compression. Nonetheless, in this example the worst compression still results in storing only half of the bytes needed for the equivelant dense array. Also, with this number of dimensions, the compression will usually be much better than COO:"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"75.0"
]
},
"execution_count": 31,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"y.tocoo().nbytes/(numpy.prod(y.shape)*y.dtype.itemsize) *100"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"GCXS arrays compress well and look and behave like NumPy arrays. GCXS currently supports the following operations:\n",
" - indexing\n",
" - multiplication\n",
" - dot\n",
" - tensordot\n",
" - matmul\n",
" - element-wise operations (including broadcasting)\n",
" - np.sin\n",
" - np.sqrt\n",
" - np.add\n",
" - np.log\n",
" - ...\n",
" - reductions\n",
" - min\n",
" - max\n",
" - sum\n",
" - prod\n",
" - mean\n",
" - std\n",
" - var\n",
" - ..."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"_fin_"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
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git+https://github.com/pydata/sparse@master
scipy
numpy
pandas
nibabel
nilearn
doit
matplotlib
pytest
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