diff --git a/MANIFEST.in b/MANIFEST.in index ebd679e..08f6f60 100644 --- a/MANIFEST.in +++ b/MANIFEST.in @@ -1,2 +1,3 @@ include *.txt include *.md +include persim/landscapes/* diff --git a/README.md b/README.md index 1ca7509..ae6ae05 100644 --- a/README.md +++ b/README.md @@ -12,6 +12,7 @@ Persim is a Python package for many tools used in analyzing Persistence Diagrams. It currently houses implementations of - Persistence Images +- Persistence Landscapes - Bottleneck distance - Modified Gromov–Hausdorff distance - Sliced Wasserstein Kernel diff --git a/RELEASE.txt b/RELEASE.txt index feea28c..79ac881 100644 --- a/RELEASE.txt +++ b/RELEASE.txt @@ -1,3 +1,6 @@ +0.3.0 + - Add implementations of Persistence Landscapes, including plotting methods, a transformer, and additional notebooks. + 0.2.1 - Allowed for more than 9 diagram labels in plot_persistence_diagrams. diff --git a/docs/index.rst b/docs/index.rst index 9f2fe17..ff929b6 100644 --- a/docs/index.rst +++ b/docs/index.rst @@ -1,8 +1,9 @@ |PyPI version| |Downloads| |Build Status| |Codecov| |License: MIT| -Persim is a Python package for many tools used in analyzing Persistence Diagrams. It currently houses implementations of +Persim is a Python package for many tools used in analyzing Persistence Diagrams. It currently includes implementations of most of the popular methods of working with persistence diagrams, including - Persistence Images +- Persistence Landscapes - Bottleneck distance - Modified Gromov--Hausdorff distance - Sliced Wasserstein Kernel @@ -26,11 +27,11 @@ We welcome contributions of all shapes and sizes. There are lots of opportunitie To contribute please fork the project make your changes and submit a pull request. We will do our best to work through any issues with you and get your code merged into the main branch. - +Documentation +-------------- .. toctree:: :maxdepth: 1 - :hidden: :caption: User Guide notebooks/Persistence images @@ -40,11 +41,12 @@ To contribute please fork the project make your changes and submit a pull reques .. toctree:: :maxdepth: 1 - :hidden: :caption: Tutorials notebooks/Classification with persistence images notebooks/Persistence barcode measure + notebooks/Differentiation with Persistence Landscapes + notebooks/Persistence Landscapes and Machine Learning .. |Downloads| image:: https://pypip.in/download/persim/badge.svg diff --git a/docs/notebooks/Differentiation with Persistence Landscapes.ipynb b/docs/notebooks/Differentiation with Persistence Landscapes.ipynb new file mode 100644 index 0000000..2e7952e --- /dev/null +++ b/docs/notebooks/Differentiation with Persistence Landscapes.ipynb @@ -0,0 +1,378 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "bulgarian-conviction", + "metadata": {}, + "source": [ + "## Distinguishing spheres using persistence landscapes" + ] + }, + { + "cell_type": "markdown", + "id": "neither-david", + "metadata": {}, + "source": [ + "In this notebook, we will highlight some basic functionality of the `PersLandscapeApprox` class and how it can be used to perform a permutation test through a simple experiment. \n", + "\n", + "The experiment is to determine if persistent homology can distinguish between spheres of different dimensions. Here we restrict to differentiating $S^2$ from $S^3$. We will further restrict ourselves to persistent homology in degree one (but one can use all relevant homological degrees as well). A priori, we would not expect this to be an effective discriminator, since the ordinary first homology of both spheres is trivial. Note that this is a simplified version of the experiment from Bubenik and Dlotko's *A persistence landscapes toolbox for topological statistics* [1]. \n", + "\n", + "In detail: \n", + "- Repeat the following `num_runs = 100` times:\n", + " - Sample `num_pts = 100` points from the 2-sphere and the 3-sphere. We rescale the spheres so the average distance between the points on each sphere is approximately 1.\n", + " - Compute the VR persistent homology (using `ripser`) and compute the associated landscapes. Store each of these landscapes.\n", + " - Compute the average landscape for $S^2$ and $S^3$. Take the difference of these two, and finally compute its supremum norm. This yields a real number; call it `significance`.\n", + "- We have thus established a baseline significance and we will see if the labelling of landscapes by dimension of their underlying sphere is significant as follows. Repeat the following `num_perms = 1000` times:\n", + " - Using the stored landscapes, randomly label half as belonging to class A and the other half as class B. \n", + " - Compute the average landscape of class A, the average landscape of class B. Compute their difference and its sup norm.\n", + " - If the sup norm of a shuffled set of labels is larger than `significance`, then we say that particular shuffling of labels was significant. If the sup norm is smaller than `significance`, then that labelling was not significant.\n", + " - Take the total number of significant labellings and divide by `num_perms` to get the p-value of this permutation test. If this p-value is less than some threshold (say 0.05), then we accept the hypothesis that the labelling based on the sphere's dimension is significant. Otherwise, we reject." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "straight-catch", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import random\n", + "\n", + "from ripser import ripser\n", + "from persim.landscapes import (\n", + " PersLandscapeApprox, \n", + " average_approx, \n", + " snap_pl, \n", + " plot_landscape, \n", + " plot_landscape_simple\n", + ")\n", + "from tadasets import dsphere" + ] + }, + { + "cell_type": "markdown", + "id": "marine-writer", + "metadata": {}, + "source": [ + "The aforementioned parameters taken from [1]. We modify these parameters below to speed up the computation." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "behavioral-biology", + "metadata": {}, + "outputs": [], + "source": [ + "num_pts = 100\n", + "num_runs = 100\n", + "num_perms = 1000" + ] + }, + { + "cell_type": "markdown", + "id": "special-correspondence", + "metadata": {}, + "source": [ + "#### Establish the baseline" + ] + }, + { + "cell_type": "markdown", + "id": "intense-counter", + "metadata": {}, + "source": [ + "The following cell samples the points, computes the persistent homology and the landscapes. Depending on the above parameters, it could take a while.\n", + "\n", + "We also scale the points according to the average distance between points on $S^2$ and $S^3$, respectively (given here https://math.stackexchange.com/q/2366580/22378). One could compute the actual distance on each run and normalize by that number, but that is more computationally intensive and isn't needed for this simple exercise. Note that `tadasets` implementation of `dsphere` samples points uniformly." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "broadband-tribune", + "metadata": {}, + "outputs": [], + "source": [ + "sph2_pl1 = []\n", + "sph3_pl1 = []\n", + "\n", + "for _ in range(num_runs):\n", + " sph2 = dsphere(n=num_pts, d=2)/1.3333 # sample points, scaling appropriately\n", + " sph2_dgm = ripser(sph2, maxdim=2)['dgms'] # compute PH0, PH1, PH2\n", + " sph2_pl = PersLandscapeApprox(dgms=sph2_dgm, hom_deg=1) # compute persistence landscape\n", + " sph2_pl1.append(sph2_pl)\n", + " \n", + " sph3 = dsphere(n=num_pts, d=3)/1.3581 # sample points, scaling appropriately\n", + " sph3_dgm = ripser(sph3, maxdim=2)['dgms'] # compute PH0, PH1, PH2\n", + " sph3_pl = PersLandscapeApprox(dgms=sph3_dgm, hom_deg=1) # compute persistence landscape\n", + " sph3_pl1.append(sph3_pl)\n" + ] + }, + { + "cell_type": "markdown", + "id": "severe-torture", + "metadata": {}, + "source": [ + "We now compute the average landscape of each list of landscapes. This can be done manually, but there is a method `average_approx` that will snap each entry to a common grid and compute the average efficiently." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "cooperative-palestinian", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Approximate persistence landscape in homological degree 1 on grid from 0.09949636459350586 to 0.7782959342002869 with 500 steps \n", + "\n", + "Approximate persistence landscape in homological degree 1 on grid from 0.17646454274654388 to 0.8208808898925781 with 500 steps\n" + ] + } + ], + "source": [ + "avg_sph2 = average_approx(sph2_pl1)\n", + "avg_sph3 = average_approx(sph3_pl1)\n", + "print(avg_sph2, '\\n') \n", + "print(avg_sph3)" + ] + }, + { + "cell_type": "markdown", + "id": "running-jonathan", + "metadata": {}, + "source": [ + "Each of these average landscapes have been computed, but are on different grids, so we must first snapt them to a common grid before taking their difference." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "instructional-chuck", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The threshold for significance is 0.059529044219766306.\n" + ] + } + ], + "source": [ + "[avg_sph2_snapped, avg_sph3_snapped] = snap_pl([avg_sph2, avg_sph3])\n", + "true_diff_pl = avg_sph2_snapped - avg_sph3_snapped\n", + "significance = true_diff_pl.sup_norm()\n", + "\n", + "print(f'The threshold for significance is {significance}.')" + ] + }, + { + "cell_type": "markdown", + "id": "southern-industry", + "metadata": {}, + "source": [ + "Can we see the differences qualititatively?" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "dependent-coalition", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# view figures in notebook\n", + "# %matplotlib inline \n", + "\n", + "plot_landscape_simple(avg_sph2_snapped,title='Average $PL_1$ for $S^2$.')" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "mediterranean-canyon", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plot_landscape_simple(true_diff_pl,title='Difference of average PLs')" + ] + }, + { + "cell_type": "markdown", + "id": "explicit-building", + "metadata": {}, + "source": [ + "The last figure has a lot going on. We can try the 3d plotting method as well to see more depth. This method is slower, and better used for final figure and not exploration." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "computational-maryland", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plot_landscape(true_diff_pl,title='Difference of average PLs')" + ] + }, + { + "cell_type": "markdown", + "id": "right-syria", + "metadata": {}, + "source": [ + "#### Perform the permutation test" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "understanding-snapshot", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "There were 0 shuffles out of 1000 that were more significant than the true labelling. Thus, the p-value is 0.0.\n" + ] + } + ], + "source": [ + "comb_pl = sph2_pl1 + sph3_pl1\n", + "sig_count = 0\n", + "\n", + "for shuffle in range(num_perms):\n", + " A_indices = random.sample(range(2*num_runs),num_runs)\n", + " B_indices = [_ for _ in range(2*num_runs) if _ not in A_indices]\n", + " \n", + " A_pl = [comb_pl[i] for i in A_indices]\n", + " B_pl = [comb_pl[j] for j in B_indices]\n", + " \n", + " A_avg = average_approx(A_pl)\n", + " B_avg = average_approx(B_pl)\n", + " [A_avg_sn, B_avg_sn] = snap_pl([A_avg,B_avg])\n", + " \n", + " shuff_diff = A_avg_sn - B_avg_sn\n", + " if (shuff_diff.sup_norm() >= significance): sig_count += 1\n", + "\n", + "pval = sig_count/num_perms\n", + "\n", + "print(f'There were {sig_count} shuffles out of {num_perms} that',\n", + " 'were more significant than the true labelling. Thus, the',\n", + " f'p-value is {pval}.')" + ] + }, + { + "cell_type": "markdown", + "id": "dedicated-homeless", + "metadata": {}, + "source": [ + "So there wasn't a single run of our experiment that resulted in a more significant labelling than the original one based on each sphere's dimension! Therefore we conclude there is a strong statistical difference between the persistence landscapes in degree one for $S^2$ and $S^3$." + ] + }, + { + "cell_type": "markdown", + "id": "satellite-protection", + "metadata": {}, + "source": [ + "#### References" + ] + }, + { + "cell_type": "markdown", + "id": "choice-azerbaijan", + "metadata": {}, + "source": [ + "[1] Bubenik, P. & Dlotko, P. A persistence landscapes toolbox for topological statistics. Journal of Symbolic Computation **78**, 91–114 (2017).\n" + ] + } + ], + "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": "3.8.5" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/docs/notebooks/Persistence Landscapes and Machine Learning.ipynb b/docs/notebooks/Persistence Landscapes and Machine Learning.ipynb new file mode 100644 index 0000000..56b92ad --- /dev/null +++ b/docs/notebooks/Persistence Landscapes and Machine Learning.ipynb @@ -0,0 +1,731 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Persistence Landscapes and Machine Learning\n", + "\n", + "This notebook gives usage examples for the persistence landscape functionality in `persim` and how they connect with other tools from `scikit-learn`. We will construct persistence landscapes for two different datasets (a sphere and a torus), plot them in comparison with each other, and use statistical learning tools to classify the two types of landscapes. " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Section 1: Example Plots for Torus vs Sphere\n", + "---\n", + "\n", + "In this section, we plot persistence diagrams and persistence landscapes for a torus and a sphere to give an example of the data types and analysis results we will use in the larger-scale classification problem." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "# Import general utilities\n", + "import numpy as np\n", + "import matplotlib\n", + "import matplotlib.pyplot as plt\n", + "\n", + "# Import TDA utilities\n", + "from ripser import Rips\n", + "from tadasets import torus, sphere\n", + "import persim\n", + "\n", + "# Import Scikit-Learn tools\n", + "from sklearn.decomposition import PCA\n", + "from sklearn import svm\n", + "from sklearn import metrics\n", + "from sklearn.model_selection import train_test_split" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "# Instantiate datasets\n", + "data_torus = torus(n=100, c=2, a=1)\n", + "data_sphere = sphere(n=100, r=2)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Rips(maxdim=2, thresh=inf, coeff=2, do_cocycles=False, n_perm = None, verbose=True)\n" + ] + } + ], + "source": [ + "# Instantiate Vietoris-Rips solver\n", + "rips = Rips(maxdim = 2)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "# Compute persistence diagrams\n", + "dgms_torus = rips.fit_transform(data_torus)\n", + "dgms_sphere = rips.fit_transform(data_sphere)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Plot persistence diagrams\n", + "fig, axs = plt.subplots(1, 2, dpi=300)\n", + "fig.set_size_inches(10, 5)\n", + "\n", + "persim.landscapes.plot_diagrams(dgms_torus, title=\"Persistence Diagram of Torus\", ax=axs[0])\n", + "\n", + "persim.landscapes.plot_diagrams(dgms_sphere, title=\"Persistence Diagram of Sphere\", ax=axs[1])\n", + "\n", + "fig.tight_layout()" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Plot persistence landscapes\n", + "fig, axs = plt.subplots(1, 2, dpi=300)\n", + "fig.set_size_inches(10, 5)\n", + "\n", + "persim.landscapes.plot_landscape_simple(persim.PersLandscapeExact(dgms_torus, hom_deg=1),\n", + " title=\"Degree 1 Persistence Landscape of Torus\", ax=axs[0])\n", + "\n", + "persim.landscapes.plot_landscape_simple(persim.PersLandscapeExact(dgms_sphere, hom_deg=1),\n", + " title=\"Degree 1 Persistence Landscape of Sphere\", ax=axs[1])\n", + "\n", + "fig.tight_layout()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Section 2: PCA and Classification\n", + "---\n", + "\n", + "In this section, we implement principal component analysis and support vector classification to attempt to classify persistence landscapes generated from a torus and persistence landscapes generated from a sphere. This section is a basic implementation and can be optimized in many ways, a couple possible methods are described in the next section." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Torus: (100,)\n", + "Sphere: (100,)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/calder/.local/lib/python3.8/site-packages/numpy/core/_asarray.py:83: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray\n", + " return array(a, dtype, copy=False, order=order)\n" + ] + } + ], + "source": [ + "# Compute multiple persistence landscapes\n", + "\n", + "landscapes_torus = []\n", + "landscapes_sphere = []\n", + "\n", + "for i in range(100):\n", + " # Resample data\n", + " _data_torus = torus(n=100, c=2, a=1)\n", + " _data_sphere = sphere(n=100, r=2)\n", + " \n", + " # Compute persistence diagrams\n", + " dgm_torus = rips.fit_transform(_data_torus)\n", + " \n", + " # Instantiate persistence landscape transformer\n", + " torus_landscaper = persim.landscapes.PersistenceLandscaper(hom_deg=1, start=0, stop=2.0, num_steps=500, flatten=True)\n", + " \n", + " # Compute flattened persistence landscape\n", + " torus_flat = torus_landscaper.fit_transform(dgm_torus)\n", + " \n", + " landscapes_torus.append(torus_flat)\n", + " \n", + " # Compute persistence diagrams\n", + " dgm_sphere = rips.fit_transform(_data_sphere)\n", + " \n", + " # Instantiate persistence landscape transformer\n", + " sphere_landscaper = persim.landscapes.PersistenceLandscaper(hom_deg=1, start=0, stop=2.0, num_steps=500, flatten=True)\n", + " \n", + " # Compute flattened persistence landscape\n", + " sphere_flat = sphere_landscaper.fit_transform(dgm_sphere)\n", + " \n", + " landscapes_sphere.append(sphere_flat) \n", + "\n", + "print('Torus:', np.shape(landscapes_torus))\n", + "print('Sphere:', np.shape(landscapes_sphere))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "In order to make this data interpretable by a PCA solver, we need a (N, M) matrix. As seen in the above print statements, each entry in `landscapes_sphere` and `landscapes_torus` are not the same length! This is because there may be different amounts of $\\lambda_k$ functions for each resampling of the data. \n", + "\n", + "To fix this, we can use zero padding to embed the arrays above in a larger (100, `w`) matrix, where `w` is the maximal length of a flattened landscape." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Torus: (100, 9000)\n", + "Sphere: (100, 9000)\n" + ] + } + ], + "source": [ + "# Find maximal length\n", + "u = np.max([len(a) for a in landscapes_torus])\n", + "v = np.max([len(a) for a in landscapes_sphere])\n", + "\n", + "w = np.max([u,v])\n", + "\n", + "# Instantiate zero-padded arrays\n", + "ls_torus = np.zeros((100, w))\n", + "ls_sphere = np.zeros((100, w))\n", + "\n", + "# Populate arrays\n", + "for i in range(len(landscapes_torus)):\n", + " ls_torus[i, 0:len(landscapes_torus[i])] = landscapes_torus[i]\n", + " ls_sphere[i, 0:len(landscapes_sphere[i])] = landscapes_sphere[i]\n", + "\n", + "\n", + "print('Torus:', ls_torus.shape)\n", + "print('Sphere:', ls_sphere.shape)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now, we have a matrix that we can apply PCA to!" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "# Instantiate PCA solver\n", + "pca_torus = PCA(n_components=2)\n", + "\n", + "# Compute PCA\n", + "pca_torus.fit_transform(ls_torus)\n", + "\n", + "# Define components\n", + "comp_torus = pca_torus.components_\n", + "\n", + "# Instantiate PCA solver\n", + "pca_sphere = PCA(n_components=2)\n", + "\n", + "# Compute PCA\n", + "pca_sphere.fit_transform(ls_sphere)\n", + "\n", + "# Define components\n", + "comp_sphere = pca_sphere.components_" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can understand the results of PCA using the singular values computed in the PCA process. " + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Singular values for torus dataset: [10.63038465 8.84765173]\n", + "Singular values for sphere dataset: [12.04660805 10.06659192]\n" + ] + } + ], + "source": [ + "print('Singular values for torus dataset:', pca_torus.singular_values_)\n", + "print('Singular values for sphere dataset:', pca_sphere.singular_values_)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Plot projection of data onto the first two principal components\n", + "plt.figure()\n", + "plt.scatter(comp_sphere[0], comp_sphere[1], label='Sphere', alpha=0.4)\n", + "plt.scatter(comp_torus[0], comp_torus[1], label='Torus', alpha=0.4)\n", + "plt.xlabel('Principal Component 1')\n", + "plt.ylabel('Principal Component 2')\n", + "plt.legend()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We now want to use a support vector classifier to classify between landscapes computed on a torus and landscapes computed on a sphere. To do so, we need a list of points $L$ and a function $f: L \\to \\{0, 1\\}$ so that $f \\equiv 0$ for torus landscapes and $f \\equiv 1$ on sphere landscapes. " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Produce lists of points\n", + "pts_torus = [[comp_torus[0,i], comp_torus[1,i]] for i in range(len(comp_torus[0]))]\n", + "pts_sphere = [[comp_sphere[0,i], comp_sphere[1,i]] for i in range(len(comp_sphere[0]))]\n", + "\n", + "# Instantiate indicator functions\n", + "chi_torus = np.zeros(len(pts_torus))\n", + "chi_sphere = np.ones(len(pts_sphere))\n", + "\n", + "# Produce final list of points\n", + "pts = []\n", + "\n", + "for p in pts_torus:\n", + " pts.append(p)\n", + " \n", + "for p in pts_sphere:\n", + " pts.append(p)\n", + "\n", + "pts = np.array(pts)\n", + "\n", + "# Append indicator functions\n", + "chi = np.hstack((chi_torus, chi_sphere))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "To train the model, we use a simple 80-20 train/test split. We can improve this training schema by using cross-validation or other similar techniques." + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model accuracy: 0.59\n" + ] + } + ], + "source": [ + "# Split points and indicator arrays\n", + "P_train, P_test, c_train, c_test = train_test_split(pts, chi, train_size=.8)\n", + "\n", + "# Instantiate support vector classifier\n", + "clf = svm.SVC()\n", + "\n", + "# Fit model\n", + "clf.fit(P_train, c_train)\n", + "\n", + "# Evaluate model performance using accuracy between ground truth data and predicted data\n", + "print(f'Model accuracy: {metrics.accuracy_score(c_test, clf.predict(P_test)):.2f}')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The model currently is not particularly accurate, but better than guessing! Hopefully, this gives a baseline implementation that statistical learning experts can improve with more robust models." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Section 3: Improving Classification Accuracy\n", + "---\n", + "\n", + "In this section, we go over some methods that can be implemented to improve the accuracy of the classification presented above. \n", + "\n", + "First, we try deleting highly persistent classes to point the model at smaller-scale data, encouraging geometric properties to inform the model. \n", + "\n", + "Second, we try adding more principal components to the model to capture more degrees of freedom in the initial data.\n", + "\n", + "Spoiler alert: the first approach does not show a significant improvement in this use case, but may be useful for other datasets. The second approach shows a minor improvement, hinting that the first two principal components may not capture enough data for classification purposes.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Torus: (100, 9000)\n", + "Sphere: (100, 9000)\n" + ] + } + ], + "source": [ + "# Delete highly persistent landscapes\n", + "\n", + "# Instantiate trimmed arrays\n", + "ls_torus_trim = ls_torus\n", + "ls_sphere_trim = ls_sphere\n", + "\n", + "# Trim arrays\n", + "for i in range(len(landscapes_torus)):\n", + " ls_torus_trim[i, 0:1000] = np.zeros((1000,))\n", + " ls_sphere_trim[i, 0:1000] = np.zeros((1000,))\n", + "\n", + "\n", + "print('Torus:', ls_torus_trim.shape)\n", + "print('Sphere:', ls_sphere_trim.shape)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Instantiate PCA solver\n", + "pca_torus_trim = PCA(n_components=2)\n", + "\n", + "# Compute PCA\n", + "pca_torus_trim.fit_transform(ls_torus_trim)\n", + "\n", + "# Define components\n", + "comp_torus_trim = pca_torus_trim.components_\n", + "\n", + "# Instantiate PCA solver\n", + "pca_sphere_trim = PCA(n_components=2)\n", + "\n", + "# Compute PCA\n", + "pca_sphere_trim.fit_transform(ls_sphere_trim)\n", + "\n", + "# Define components\n", + "comp_sphere_trim = pca_sphere_trim.components_\n", + "\n", + "# Plot projection of data onto the first two principal components\n", + "plt.figure()\n", + "plt.scatter(comp_sphere_trim[0], comp_sphere_trim[1], label='Sphere', alpha=0.4)\n", + "plt.scatter(comp_torus_trim[0], comp_torus_trim[1], label='Torus', alpha=0.4)\n", + "plt.xlabel('Principal Component 1')\n", + "plt.ylabel('Principal Component 2')\n", + "plt.title('PCA Projection with Trimmed Diagrams')\n", + "plt.legend()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We now want to use a support vector classifier to classify between landscapes computed on a torus and landscapes computed on a sphere. To do so, we need a list of points $L$ and a function $f: L \\to \\{0, 1\\}$ so that $f \\equiv 0$ for torus landscapes and $f \\equiv 1$ on sphere landscapes. " + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [], + "source": [ + "# Produce lists of points\n", + "pts_torus = [[comp_torus[0,i], comp_torus[1,i]] for i in range(len(comp_torus[0]))]\n", + "pts_sphere = [[comp_sphere[0,i], comp_sphere[1,i]] for i in range(len(comp_sphere[0]))]\n", + "\n", + "# Instantiate indicator functions\n", + "chi_torus = np.zeros(len(pts_torus))\n", + "chi_sphere = np.ones(len(pts_sphere))\n", + "\n", + "# Produce final list of points\n", + "pts = []\n", + "\n", + "for p in pts_torus:\n", + " pts.append(p)\n", + " \n", + "for p in pts_sphere:\n", + " pts.append(p)\n", + "\n", + "pts = np.array(pts)\n", + "\n", + "# Append indicator functions\n", + "chi = np.hstack((chi_torus, chi_sphere))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "To train the model, we use a simple 80-20 train/test split. In practice, this can be improved by using cross-validation or other such techniques." + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model accuracy: 0.57\n" + ] + } + ], + "source": [ + "# Produce lists of points\n", + "pts_torus_trim = [[comp_torus_trim[0,i], comp_torus_trim[1,i]] for i in range(len(comp_torus_trim[0]))]\n", + "pts_sphere_trim = [[comp_sphere_trim[0,i], comp_sphere_trim[1,i]] for i in range(len(comp_sphere_trim[0]))]\n", + "\n", + "# Instantiate indicator functions\n", + "chi_torus_trim = np.zeros(len(pts_torus_trim))\n", + "chi_sphere_trim = np.ones(len(pts_sphere_trim))\n", + "\n", + "# Produce final list of points\n", + "pts_trim = []\n", + "\n", + "for p in pts_torus_trim:\n", + " pts_trim.append(p)\n", + " \n", + "for p in pts_sphere_trim:\n", + " pts_trim.append(p)\n", + "\n", + "pts_trim = np.array(pts_trim)\n", + "\n", + "# Append indicator functions\n", + "chi_trim = np.hstack((chi_torus_trim, chi_sphere_trim))\n", + "\n", + "# Split points and indicator arrays\n", + "P_train_trim, P_test_trim, c_train_trim, c_test_trim = train_test_split(pts_trim, chi_trim, train_size=.8)\n", + "\n", + "# Instantiate support vector classifier\n", + "clf_trim = svm.SVC()\n", + "\n", + "# Fit model\n", + "clf_trim.fit(P_train_trim, c_train_trim)\n", + "\n", + "# Evaluate model performance using accuracy between ground truth data and predicted data\n", + "print(f'Model accuracy: {metrics.accuracy_score(c_test_trim, clf_trim.predict(P_test_trim)):.2f}')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Section 3: Improving Classification Accuracy\n", + "\n", + "In this section, we go over some methods to improve the accuracy of the classification presented above. These methods include deleting highly persistent classes to identify significant differences in the data and using multicomponent PCA projections to capture more degrees of freedom in the initial data.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model accuracy: 0.63\n" + ] + } + ], + "source": [ + "# Try multicomponent PCA\n", + "\n", + "# Instantiate multicomponent PCA solver\n", + "pca_torus_mcomp = PCA(n_components=6)\n", + "\n", + "# Compute PCA\n", + "pca_torus_mcomp.fit_transform(ls_torus)\n", + "\n", + "# Define components\n", + "comp_torus_mcomp = pca_torus_mcomp.components_\n", + "\n", + "# Instantiate PCA solver\n", + "pca_sphere_mcomp = PCA(n_components=6)\n", + "\n", + "# Compute PCA\n", + "pca_sphere_mcomp.fit_transform(ls_sphere)\n", + "\n", + "# Define components\n", + "comp_sphere_mcomp = pca_sphere_mcomp.components_\n", + "\n", + "\n", + "# Produce lists of points\n", + "pts_torus_mcomp = [[comp_torus_mcomp[j,i] for j in range(6)] for i in range(len(comp_torus_mcomp[0]))]\n", + "pts_sphere_mcomp = [[comp_sphere_mcomp[j,i] for j in range(6)] for i in range(len(comp_sphere_mcomp[0]))]\n", + "\n", + "# Instantiate indicator functions\n", + "chi_torus_mcomp = np.zeros(len(pts_torus_mcomp))\n", + "chi_sphere_mcomp = np.ones(len(pts_sphere_mcomp))\n", + "\n", + "# Produce final list of points\n", + "pts_mcomp = []\n", + "\n", + "for p in pts_torus_mcomp:\n", + " pts_mcomp.append(p)\n", + " \n", + "for p in pts_sphere_mcomp:\n", + " pts_mcomp.append(p)\n", + "\n", + "pts_mcomp = np.array(pts_mcomp)\n", + "\n", + "# Append indicator functions\n", + "chi_mcomp = np.hstack((chi_torus_mcomp, chi_sphere_mcomp))\n", + "\n", + "# Split points and indicator arrays\n", + "P_train_mcomp, P_test_mcomp, c_train_mcomp, c_test_mcomp = train_test_split(pts_mcomp, chi_mcomp, train_size=.8)\n", + "\n", + "# Instantiate support vector classifier\n", + "clf_mcomp = svm.SVC()\n", + "\n", + "# Fit model\n", + "clf_mcomp.fit(P_train_mcomp, c_train_mcomp)\n", + "\n", + "# Evaluate model performance using accuracy between ground truth data and predicted data\n", + "print(f'Model accuracy: {metrics.accuracy_score(c_test_mcomp, clf_mcomp.predict(P_test_mcomp)):.2f}')\n" + ] + }, + { + "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": "3.8.5" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/docs/reference/index.rst b/docs/reference/index.rst index 924908c..944e3e8 100644 --- a/docs/reference/index.rst +++ b/docs/reference/index.rst @@ -27,7 +27,26 @@ Persistence Images persim.PersistenceImager persim.PersImage +Persistence Landscapes +======================== +.. autosummary:: + :toctree: stubs + :recursive: + :nosignatures: + + persim.PersLandscapeExact + persim.PersLandscapeApprox + persim.PersistenceLandscaper + +.. autosummary:: + :toctree: stubs + :recursive: + :nosignatures: + persim.average_approx + persim.snap_PL + persim.plot_landscape + persim.plot_landscape_simple Diagram Visualization @@ -40,8 +59,8 @@ Diagram Visualization persim.plot_diagrams persim.bottleneck_matching persim.wasserstein_matching - - + persim.plot_landscape + persim.plot_landscape_simple Persistence barcode measure diff --git a/persim/_version.py b/persim/_version.py index 3ced358..493f741 100644 --- a/persim/_version.py +++ b/persim/_version.py @@ -1 +1 @@ -__version__ = "0.2.1" +__version__ = "0.3.0" diff --git a/persim/landscapes/__init__.py b/persim/landscapes/__init__.py new file mode 100644 index 0000000..d664a77 --- /dev/null +++ b/persim/landscapes/__init__.py @@ -0,0 +1,5 @@ +from .exact import PersLandscapeExact +from .approximate import PersLandscapeApprox +from .transformer import PersistenceLandscaper +from .visuals import plot_landscape, plot_landscape_simple +from .tools import * diff --git a/persim/landscapes/approximate.py b/persim/landscapes/approximate.py new file mode 100644 index 0000000..b4687ea --- /dev/null +++ b/persim/landscapes/approximate.py @@ -0,0 +1,375 @@ +""" + Persistence Landscape Approximate class +""" + +import numpy as np +from operator import itemgetter +from .base import PersLandscape +from .auxiliary import union_vals, ndsnap_regular, _p_norm + +__all__ = ["PersLandscapeApprox"] + + +class PersLandscapeApprox(PersLandscape): + """ + Persistence Landscape Approximate class. + + This class implements an approximate version of Persistence Landscape, + given by sampling the landscape functions on a grid. This version is only + an approximation to the true landscape, but given a fine enough grid, this + should suffice for most applications. If an exact calculation with no + approximation is desired, consider `PersLandscapeExact`. Computations with this + class are much faster compared to `PersLandscapeExact` in general. + + The optional parameters `start`, `stop`, `num_steps` determine the approximating + grid that the values are sampled on. If both `dgms` and `values` are passed but `start` + and `stop` are not, `start` and `stop` will be determined by `dgms`. + + + Parameters + ---------- + start : float, optional + The start parameter of the approximating grid. + + stop : float, optional + The stop parameter of the approximating grid. + + num_steps : int, optional + The number of dimensions of the approximation, equivalently the + number of steps in the grid. + + dgms : list of (-,2) numpy.ndarrays, optional + Nested list of numpy arrays, e.g., [array( array([:]), array([:]) ),..., array([:])]. + Each entry in the list corresponds to a single homological degree. + Each array represents the birth-death pairs in that homological degree. This is + precisely the output format from ripser.py: ripser(data_user)['dgms']. + + hom_deg : int + Represents the homology degree of the persistence diagram. + + values : numpy.ndarray, optional + The approximated values of the landscapes, indexed by depth. + + compute : bool, optional + Flag determining whether landscape functions are computed upon instantiation. + + Examples + -------- + Define a persistence diagram and instantiate the landscape:: + + >>> from persim import PersLandscapeApprox + >>> import numpy as np + >>> pd = [ np.array([[0,3],[1,4]]), np.array([[1,4]]) ] + >>> pla = PersLandscapeApprox(dgms=pd, hom_deg=0); pla + + Approximate persistence landscape in homological degree 0 on grid from 0 to 4 with 500 steps + + The `start` and `stop` parameters will be determined to be as tight as possible from `dgms` if they are not passed. They can be passed directly if desired:: + + >>> wide_pl = PersLandscapeApprox(dgms=pd, hom_deg=0, start=-1, stop=3.1415, num_steps=1000); wide_pl + + Approximate persistence landscape in homological degree 0 on grid from -1 to 3.1415 with 1000 steps + + The approximating values are stored in the `values` attribute:: + + >>> wide_pl.values + + array([[0. , 0. , 0. , ..., 0.00829129, 0.00414565, + 0. ], + [0. , 0. , 0. , ..., 0. , 0. , + 0. ]]) + + Arithmetic methods are implemented for approximate landscapes, so they can be summed, subtracted, and admit scalar multiplication. + + .. note:: Landscapes must have the same grid parameters (`start`, `stop`, and `num_steps`) before any arithmetic is involved. See the `snap_PL` function for a method that will snap a list of landscapes onto a common grid. + + >>> pla - wide_pl + + ValueError: Start values of grids do not coincide + + >>> from persim import snap_PL + >>> [snapped_pla, snapped_wide_pl] = snap_PL([pla,wide_pl]) + >>> print(snapped_pla, snapped_wide_pl) + + Approximate persistence landscape in homological degree 0 on grid from -1 to 4 with 1000 steps Approximate persistence landscape in homological degree 0 on grid from -1 to 4 with 1000 steps + + >>> sum_pl = snapped_pla + snapped_wide_pl; sum_pl.values + array([[0. , 0. , 0. , ..., 0.01001001, 0.00500501, + 0. ], + [0. , 0. , 0. , ..., 0. , 0. , + 0. ]]) + + Approximate landscapes are sliced by depth and slicing returns the approximated values in those depths:: + + >>> sum_pl[0] + + array([0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ..., + 1.50150150e-02, 1.00100100e-02, 5.00500501e-03, 0.00000000e+00]) + + Norms are implemented for all `p` including the supremum norm:: + + >>> sum_pl.p_norm(p=5) + + 12.44665414332285 + + >>> sum_pl.sup_norm() + + 2.9958943943943943 + + """ + + def __init__( + self, + start: float = None, + stop: float = None, + num_steps: int = 500, + dgms: list = [], + hom_deg: int = 0, + values=np.array([]), + compute: bool = True, + ) -> None: + + super().__init__(dgms=dgms, hom_deg=hom_deg) + if not dgms and values.size == 0: + raise ValueError("dgms and values cannot both be emtpy") + if dgms: # diagrams are passed + self.dgms = dgms[self.hom_deg] + # remove infity values + self.dgms = self.dgms[~np.any(self.dgms == np.inf, axis=1)] + # calculate start and stop + if start is None: + start = min(self.dgms, key=itemgetter(0))[0] + if stop is None: + stop = max(self.dgms, key=itemgetter(1))[1] + elif values.size > 0: # values passed, diagrams weren't + self.dgms = dgms + if start is None: + raise ValueError("start parameter must be passed if values are passed") + if stop is None: + raise ValueError("stop parameter must be passed if values are passed") + if start > stop: + raise ValueError("start must be less than or equal to stop") + self.start = start + self.stop = stop + self.values = values + self.num_steps = num_steps + if compute: + self.compute_landscape() + + def __repr__(self) -> str: + return ( + "Approximate persistence landscape in homological " + f"degree {self.hom_deg} on grid from {self.start} to {self.stop}" + f" with {self.num_steps} steps" + ) + + def compute_landscape(self, verbose: bool = False) -> list: + """Computes the approximate landscape values + + Parameters + ---------- + verbose : bool, optional + If true, progress messages are printed during computation. + + """ + + verboseprint = print if verbose else lambda *a, **k: None + + if self.values.size: + verboseprint("values was stored, exiting") + return + + verboseprint("values was empty, computing values") + # make grid + grid_values, step = np.linspace( + self.start, self.stop, self.num_steps, retstep=True + ) + # grid_values = list(grid_values) + # grid = np.array([[x,y] for x in grid_values for y in grid_values]) + bd_pairs = self.dgms + + # snap birth-death pairs to grid + bd_pairs_grid = ndsnap_regular(bd_pairs, *(grid_values, grid_values)) + + # make grid dictionary + index = list(range(self.num_steps)) + dict_grid = dict(zip(grid_values, index)) + + # initialze W to a list of 2m + 1 empty lists + W = [[] for _ in range(self.num_steps)] + + # for each birth death pair + for ind_in_bd_pairs, bd in enumerate(bd_pairs_grid): + [b, d] = bd + ind_in_Wb = dict_grid[b] # index in W + ind_in_Wd = dict_grid[d] # index in W + mid_pt = ( + ind_in_Wb + (ind_in_Wd - ind_in_Wb) // 2 + ) # index half way between, rounded down + + # step through by x value + j = 0 + # j in (b, b+d/2] + for _ in range(ind_in_Wb, mid_pt): + j += 1 + # j*step: adding points from a line with slope 1 + W[ind_in_Wb + j].append(j * step) + + j = 0 + # j in (b+d/2, d) + for _ in range(mid_pt + 1, ind_in_Wd): + j += 1 + W[ind_in_Wd - j].append(j * step) + + # sort each list in W + for i in range(len(W)): + W[i] = sorted(W[i], reverse=True) + + # calculate k: max length of lists in W + K = max([len(_) for _ in W]) + + # initialize L to be a zeros matrix of size K x (2m+1) + L = np.array([np.zeros(self.num_steps) for _ in range(K)]) + + # input Values from W to L + for i in range(self.num_steps): + for k in range(len(W[i])): + L[k][i] = W[i][k] + + # check if L is empty + if not L.size: + L = np.array(["empty"]) + print("Bad choice of grid, values is empty") + + self.values = L + return + + def values_to_pairs(self): + """Converts function values to ordered pairs and returns them""" + self.compute_landscape() + grid_values = list(np.linspace(self.start, self.stop, self.num_steps)) + result = [] + for vals in self.values: + pairs = list(zip(grid_values, vals)) + result.append(pairs) + return np.array(result) + + def __add__(self, other): + """Computes the sum of two approximate persistence landscapes + + Parameters + ---------- + other : PersLandscapeApprox + The other summand. + """ + super().__add__(other) + if self.start != other.start: + raise ValueError("Start values of grids do not coincide") + if self.stop != other.stop: + raise ValueError("Stop values of grids do not coincide") + if self.num_steps != other.num_steps: + raise ValueError("Number of steps of grids do not coincide") + self_pad, other_pad = union_vals(self.values, other.values) + return PersLandscapeApprox( + start=self.start, + stop=self.stop, + num_steps=self.num_steps, + hom_deg=self.hom_deg, + values=self_pad + other_pad, + ) + + def __neg__(self): + """Negates an approximate persistence landscape""" + return PersLandscapeApprox( + start=self.start, + stop=self.stop, + num_steps=self.num_steps, + hom_deg=self.hom_deg, + values=np.array([-1 * depth_array for depth_array in self.values]), + ) + pass + + def __sub__(self, other): + """Computes the difference of two approximate persistence landscapes + + Parameters + ---------- + other : PersLandscapeApprox + The landscape to be subtracted. + """ + return self + -other + + def __mul__(self, other: float): + """Multiplies an approximate persistence landscape by a real scalar + + Parameters + ---------- + other : float + The real scalar to be multiplied. + """ + super().__mul__(other) + return PersLandscapeApprox( + start=self.start, + stop=self.stop, + num_steps=self.num_steps, + hom_deg=self.hom_deg, + values=np.array([other * depth_array for depth_array in self.values]), + ) + + def __rmul__(self, other: float): + """Multiplies an approximate persistence landscape by a real scalar + + Parameters + ---------- + other : float + The real scalar factor. + """ + return self.__mul__(other) + + def __truediv__(self, other: float): + """Divides an approximate persistence landscape by a non-zero real scalar + + Parameters + ---------- + other : float + The non-zero real scalar divisor. + """ + super().__truediv__(other) + return (1.0 / other) * self + + def __getitem__(self, key: slice) -> list: + """ + Returns a list of values corresponding in range specified by + depth + + Parameters + ---------- + key : slice object + + Returns + ------- + list + The values of the landscape function corresponding + to depths given by key + """ + self.compute_landscape() + return self.values[key] + + def p_norm(self, p: int = 2) -> float: + """ + Returns the L_{`p`} norm of an approximate persistence landscape + + Parameters + ---------- + p: float, default 2 + value p of the L_{`p`} norm + """ + super().p_norm(p=p) + return _p_norm(p=p, critical_pairs=self.values_to_pairs()) + + def sup_norm(self) -> float: + """ + Returns the supremum norm of an approximate persistence landscape + + """ + return np.max(np.abs(self.values)) diff --git a/persim/landscapes/auxiliary.py b/persim/landscapes/auxiliary.py new file mode 100644 index 0000000..29fc811 --- /dev/null +++ b/persim/landscapes/auxiliary.py @@ -0,0 +1,169 @@ +""" + Auxilary functions for working with persistence diagrams. +""" + +import itertools +import numpy as np + + +def union_vals(A, B): + """Helper function for summing grid landscapes. + + Extends one list to the length of the other by padding with zero lists. + """ + diff = A.shape[0] - B.shape[0] + if diff < 0: + # B has more entries, so pad A + A = np.pad(A, pad_width=((0, np.abs(diff)), (0, 0))) + return A, B + elif diff > 0: + # A has more entries, so pad B + B = np.pad(B, pad_width=((0, diff), (0, 0))) + return A, B + else: + return A, B + + +def union_crit_pairs(A, B): + """Helper function for summing landscapes. + + Computes the union of two sets of critical pairs. + """ + result_pairs = [] + A.compute_landscape() + B.compute_landscape() + # zip functions in landscapes A and B and pad with None + for a, b in list(itertools.zip_longest(A.critical_pairs, B.critical_pairs)): + # B had more functions + if a is None: + result_pairs.append(b) + # A had more functions + elif b is None: + result_pairs.append(a) + # A, B > pos_to_slope_interp > sum_slopes > slope_to_pos_interp + else: + result_pairs.append( + slope_to_pos_interp( + sum_slopes(pos_to_slope_interp(a), pos_to_slope_interp(b),) + ) + ) + return result_pairs + + +def pos_to_slope_interp(l: list) -> list: + """Convert positions of critical pairs to (x-value, slope) pairs. + + Intended for internal use. Inverse function of `slope_to_pos_interp`. + + Result + ------ + list + [(xi,mi)] for i in len(function in landscape) + """ + + output = [] + # for sequential pairs in landscape function + for [[x0, y0], [x1, y1]] in zip(l, l[1:]): + slope = (y1 - y0) / (x1 - x0) + output.append([x0, slope]) + output.append([l[-1][0], 0]) + return output + + +def slope_to_pos_interp(l: list) -> list: + """Convert positions of (x-value, slope) pairs to critical pairs. + + Intended + for internal use. Inverse function of `pos_to_slope_interp`. + + Result + ------ + list + [(xi, yi)]_i for i in len(function in landscape) + """ + output = [[l[0][0], 0]] + # for sequential pairs in [(xi,mi)]_i + for [[x0, m], [x1, _]] in zip(l, l[1:]): + # uncover y0 and y1 from slope formula + y0 = output[-1][1] + y1 = y0 + (x1 - x0) * m + output.append([x1, y1]) + return output + + +def sum_slopes(a: list, b: list) -> list: + """ + Sum two piecewise linear functions, each represented as a list + of pairs (xi,mi), where each xi is the x-value of critical pair and + mi is the slope. The input should be of the form of the output of the + `pos_to_slope_interp' function. + + Result + ------ + list + + """ + result = [] + am, bm = 0, 0 # initialize slopes + while len(a) > 0 or len(b) > 0: + if len(a) == 0 or (len(a) > 0 and len(b) > 0 and a[0][0] > b[0][0]): + # The next critical pair comes from list b. + bx, bm = b[0] + # pop b0 + b = b[1:] + result.append([bx, am + bm]) + elif len(b) == 0 or (len(a) > 0 and len(b) > 0 and a[0][0] < b[0][0]): + # The next critical pair comes from list a. + ax, am = a[0] + # pop a0 + a = a[1:] + result.append([ax, am + bm]) + else: + # The x-values of two critical pairs coincide. + ax, am = a[0] + bx, bm = b[0] + # pop a0 and b0 + a, b = a[1:], b[1:] + result.append([ax, am + bm]) + return result + + +def ndsnap_regular(points, *grid_axes): + """Snap points to the 2d grid determined by grid_axes""" + # https://stackoverflow.com/q/8457645/717525 + snapped = [] + for i, ax in enumerate(grid_axes): + diff = ax[:, np.newaxis] - points[:, i] + best = np.argmin(np.abs(diff), axis=0) + snapped.append(ax[best]) + return np.array(snapped).T + + +def _p_norm(p: float, critical_pairs: list = []): + """ + Compute `p` norm of interpolated piecewise linear function defined from list of + critical pairs. + """ + result = 0.0 + for l in critical_pairs: + for [[x0, y0], [x1, y1]] in zip(l, l[1:]): + if y0 == y1: + # horizontal line segment + result += (np.abs(y0) ** p) * (x1 - x0) + continue + # slope is well-defined + slope = (y1 - y0) / (x1 - x0) + b = y0 - slope * x0 + # segment crosses the x-axis + if (y0 < 0 and y1 > 0) or (y0 > 0 and y1 < 0): + z = -b / slope + ev_x1 = (slope * x1 + b) ** (p + 1) / (slope * (p + 1)) + ev_x0 = (slope * x0 + b) ** (p + 1) / (slope * (p + 1)) + ev_z = (slope * z + +b) ** (p + 1) / (slope * (p + 1)) + result += np.abs(ev_x1 + ev_x0 - 2 * ev_z) + # segment does not cross the x-axis + else: + ev_x1 = (slope * x1 + b) ** (p + 1) / (slope * (p + 1)) + ev_x0 = (slope * x0 + b) ** (p + 1) / (slope * (p + 1)) + result += np.abs(ev_x1 - ev_x0) + return (result) ** (1.0 / p) diff --git a/persim/landscapes/base.py b/persim/landscapes/base.py new file mode 100644 index 0000000..e318c15 --- /dev/null +++ b/persim/landscapes/base.py @@ -0,0 +1,76 @@ +""" + Base Persistence Landscape class. + + authors: Gabrielle Angeloro, Michael Catanzaro +""" +from abc import ABC, abstractmethod +import numpy as np + + +class PersLandscape(ABC): + """ + The base Persistence Landscape class. + + This is the base persistence landscape class. This class should not be + called directly; the subclasses `PersLandscapeApprox` or + `PersLandscapeExact` should instead be called. + + Parameters + ---------- + dgms: list[list] + A list of birth-death pairs. + + hom_deg: int + The homological degree. + """ + + def __init__(self, dgms: list = [], hom_deg: int = 0) -> None: + if not isinstance(hom_deg, int): + raise TypeError("hom_deg must be an integer") + if hom_deg < 0: + raise ValueError("hom_deg must be positive") + if not isinstance(dgms, (list, tuple, np.ndarray)): + raise TypeError("dgms must be a list, tuple, or numpy array") + self.hom_deg = hom_deg + + # We force landscapes to have arithmetic and norms, + # this is the whole reason for using them. + + @abstractmethod + def p_norm(self, p: int = 2) -> float: + if p < -1 or -1 < p < 0: + raise ValueError(f"p can't be negative, but {p} was passed") + self.compute_landscape() + if p == -1: + return self.sup_norm() + + @abstractmethod + def sup_norm(self) -> float: + pass + + @abstractmethod + def __add__(self, other): + if self.hom_deg != other.hom_deg: + raise ValueError( + "Persistence landscapes must be of same homological degree" + ) + + @abstractmethod + def __neg__(self): + pass + + @abstractmethod + def __sub__(self, other): + pass + + @abstractmethod + def __mul__(self, other): + if not isinstance(other, (int, float)): + raise TypeError( + "Can only multiply persistence landscapes" "by real numbers" + ) + + @abstractmethod + def __truediv__(self, other): + if other == 0.0: + raise ValueError("Cannot divide by zero") diff --git a/persim/landscapes/exact.py b/persim/landscapes/exact.py new file mode 100644 index 0000000..2c8a544 --- /dev/null +++ b/persim/landscapes/exact.py @@ -0,0 +1,415 @@ +""" + Persistence Landscape Exact class +""" + +import itertools +import numpy as np +from operator import itemgetter + +from .approximate import PersLandscapeApprox +from .auxiliary import union_crit_pairs, _p_norm +from .base import PersLandscape + +__all__ = ["PersLandscapeExact"] + + +class PersLandscapeExact(PersLandscape): + """Persistence Landscape Exact class. + + This class implements an exact version of Persistence Landscapes. The landscape + functions are stored as a list of critical pairs, and the actual function is the + linear interpolation of these critical pairs. All + computations done with these classes are exact. For much faster but + approximate methods that should suffice for most applications, consider + `PersLandscapeApprox`. + + Parameters + ---------- + dgms : list of (-,2) numpy.ndarrays, optional + A nested list of numpy arrays, e.g., [array( array([:]), array([:]) ),..., array([:])] + Each entry in the list corresponds to a single homological degree. + Each array represents the birth-death pairs in that homological degree. This is + the output format from ripser.py: ripser(data_user)['dgms']. Only + one of diagrams or critical pairs should be specified. + + hom_deg : int + Represents the homology degree of the persistence diagram. + + critical_pairs : list, optional + List of lists of critical pairs (points, values) for specifying a persistence landscape. + These do not necessarily have to arise from a persistence + diagram. Only one of diagrams or critical pairs should be specified. + + compute : bool, optional + Flag determining whether landscape functions are computed upon instantiation. + + + Examples + -------- + Define a persistence diagram and instantiate the landscape:: + + >>> from persim import PersLandscapeExact + >>> import numpy as np + >>> pd = [ np.array([[0,3],[1,4]]), np.array([[1,4]]) ] + >>> ple = PersLandscapeExact(dgms=pd, hom_deg=0) + >>> ple + + `PersLandscapeExact` instances store the critical pairs of the landscape as a list of lists in the `critical_pairs` attribute. The `i`-th entry corresponds to the critical values of the depth `i` landscape:: + + >>> ple.critical_pairs + + [[[0, 0], [1.5, 1.5], [2.0, 1.0], [2.5, 1.5], [4, 0]], + [[1, 0], [2.0, 1.0], [3, 0]]] + + Addition, subtraction, and scalar multiplication between landscapes is implemented:: + + >>> pd2 = [ np.array([[0.5,7],[3,5],[4.1,6.5]]), np.array([[1,4]])] + >>> pl2 = PersLandscapeExact(dgms=pd2,hom_deg=0) + >>> pl_sum = ple + pl2 + >>> pl_sum.critical_pairs + + [[[0, 0], [0.5, 0.5], [1.5, 2.5], [2.0, 2.5], + [2.5, 3.5], [3.75, 3.5],[4, 3.0], [7.0, 0.0]], + [[1, 0], [2.0, 1.0], [3, 0.0], [4.0, 1.0], + [4.55, 0.45], [5.3, 1.2], [6.5, 0.0]], + [[4.1, 0], [4.55, 0.45], [5.0, 0]]] + + >>> diff_pl = ple - pl2 + >>> diff_pl.critical_pairs + + [[[0, 0], [0.5, 0.5], [1.5, 0.5], [2.0, -0.5], + [2.5, -0.5], [3.75, -3.0], [4, -3.0], [7.0, 0.0]], + [[1, 0], [2.0, 1.0], [3, 0.0], [4.0, -1.0], + [4.55, -0.45], [5.3, -1.2], [6.5, 0.0]], + [[4.1, 0], [4.55, -0.45], [5.0, 0]]] + + >>> (5*ple).critical_pairs + + [[(0, 0), (1.5, 7.5), (2.0, 5.0), (2.5, 7.5), (4, 0)], + [(1, 0), (2.0, 5.0), (3, 0)]] + + Landscapes are sliced by depth and slicing returns the critical pairs in the range specified:: + + >>> ple[0] + + [[0, 0], [1.5, 1.5], [2.0, 1.0], [2.5, 1.5], [4, 0]] + + >>> pl2[1:] + + [[[3.0, 0], [4.0, 1.0], [4.55, 0.4500000000000002], + [5.3, 1.2000000000000002], [6.5, 0]], + [[4.1, 0], [4.55, 0.4500000000000002], [5.0, 0]]] + + `p` norms are implemented for all `p` as well as the supremum norms:: + + >>> ple.p_norm(p=3) + + 1.7170713638299977 + + >>> pl2.sup_norm() + + 3.25 + + + + Methods + ------- + compute_landscape : computes the set of critical pairs and stores them in + the attribute `critical_pairs` + + compute_landscape_by_depth : compute the set of critical pairs in a certain + range. + + p_norm : returns p-norm of a landscape + + sup_norm : returns sup norm of a landscape + + """ + + def __init__( + self, + dgms: list = [], + hom_deg: int = 0, + critical_pairs: list = [], + compute: bool = True, + ) -> None: + super().__init__(dgms=dgms, hom_deg=hom_deg) + self.critical_pairs = critical_pairs + if dgms: + self.dgms = dgms[self.hom_deg] + else: # critical pairs are passed. Is this the best check for this? + self.dgms = dgms + if not dgms and not critical_pairs: + raise ValueError("dgms and critical_pairs cannot both be empty") + self.max_depth = len(self.critical_pairs) + if compute: + self.compute_landscape() + + def __repr__(self): + return f"Exact persistence landscape in homological degree {self.hom_deg}" + + def __neg__(self): + """ + Computes the negation of a persistence landscape object + + """ + self.compute_landscape() + return PersLandscapeExact( + hom_deg=self.hom_deg, + critical_pairs=[ + [[a, -b] for a, b in depth_list] for depth_list in self.critical_pairs + ], + ) + + def __add__(self, other): + """ + Computes the sum of two persistence landscape objects + + """ + + if self.hom_deg != other.hom_deg: + raise ValueError("homological degrees must match") + return PersLandscapeExact( + critical_pairs=union_crit_pairs(self, other), hom_deg=self.hom_deg + ) + + def __sub__(self, other): + """ + Computes the difference of two persistence landscape objects + + """ + return self + -other + + def __mul__(self, other: float): + """ + Computes the product of a persistence landscape object and a float + + Parameters + ------- + other: float + the real scalar the persistence landscape will be multiplied by + + """ + self.compute_landscape() + return PersLandscapeExact( + hom_deg=self.hom_deg, + critical_pairs=[ + [(a, other * b) for a, b in depth_list] + for depth_list in self.critical_pairs + ], + ) + + def __rmul__(self, other: float): + """ + Computes the product of a persistence landscape object and a float + + Parameters + ------- + other: float + the real scalar the persistence landscape will be multiplied by + + """ + return self.__mul__(other) + + def __truediv__(self, other: float): + """ + Computes the quotient of a persistence landscape object and a float + + Parameters + ------- + other: float + the real divisor of the persistence landscape object + + """ + + if other == 0.0: + raise ValueError("Cannot divide by zero") + return self * (1.0 / other) + + def __getitem__(self, key: slice) -> list: + """ + Returns a list of critical pairs corresponding in range specified by + depth + + Parameters + ---------- + key : slice object + + Returns + ------- + list + The critical pairs of the landscape function corresponding + to depths given by key + + Note + ---- + If the slice is beyond `self.max_depth` an IndexError is raised. + """ + self.compute_landscape() + return self.critical_pairs[key] + + def compute_landscape(self, verbose: bool = False) -> list: + """ + Stores the persistence landscape in `self.critical_pairs` as a list + + Parameters + ---------- + verbose: bool, optional + If true, progress messages are printed during computation + + """ + + verboseprint = print if verbose else lambda *a, **k: None + + # check if landscapes were already computed + if self.critical_pairs: + verboseprint( + "self.critical_pairs was not empty and stored value was returned" + ) + return self.critical_pairs + + A = self.dgms + # change A into a list + A = list(A) + # change inner nparrays into lists + for i in range(len(A)): + A[i] = list(A[i]) + if A[-1][1] == np.inf: + A.pop(-1) + + landscape_idx = 0 + L = [] + + # Sort A: read from right to left inside () + A = sorted(A, key=lambda x: [x[0], -x[1]]) + + while A: + verboseprint(f"computing landscape index {landscape_idx+1}...") + + # add a 0 element to begin count of lamda_k + # size_landscapes = np.append(size_landscapes, [0]) + + # pop first term + b, d = A.pop(0) + verboseprint(f"(b,d) is ({b},{d})") + + # outer brackets for start of L_k + L.append([[-np.inf, 0], [b, 0], [(b + d) / 2, (d - b) / 2]]) + + # check for duplicates of (b,d) + duplicate = 0 + + for j, itemj in enumerate(A): + if itemj == [b, d]: + duplicate += 1 + A.pop(j) + else: + break + + while L[landscape_idx][-1] != [np.inf, 0]: + + # if d is > = all remaining pairs, then end lambda + # includes edge case with (b,d) pairs with the same death time + if all(d >= _[1] for _ in A): + # add to end of L_k + L[landscape_idx].extend([[d, 0], [np.inf, 0]]) + # for duplicates, add another copy of the last computed lambda + for _ in range(duplicate): + L.append(L[-1]) + landscape_idx += 1 + + else: + # set (b', d') to be the first term so that d' > d + for i, item in enumerate(A): + if item[1] > d: + b_prime, d_prime = A.pop(i) + verboseprint(f"(bp,dp) is ({b_prime},{d_prime})") + break + + # Case I + if b_prime > d: + L[landscape_idx].extend([[d, 0]]) + + # Case II + if b_prime >= d: + L[landscape_idx].extend([[b_prime, 0]]) + + # Case III + else: + L[landscape_idx].extend( + [[(b_prime + d) / 2, (d - b_prime) / 2]] + ) + # push (b', d) into A in order + # find the first b_i in A so that b'<= b_i + + # push (b', d) to end of list if b' not <= any bi + ind = len(A) + for i in range(len(A)): + if b_prime <= A[i][0]: + ind = i # index to push (b', d) if b' != b_i + break + # if b' not < = any bi, put at the end of list + if ind == len(A): + pass + # if b' = b_i + elif b_prime == A[ind][0]: + # pick out (bk,dk) such that b' = bk + A_i = [item for item in A if item[0] == b_prime] + + # move index to the right one for every d_i such that d < d_i + for j in range(len(A_i)): + if d < A_i[j][1]: + ind += 1 + + # d > dk for all k + + A.insert(ind, [b_prime, d]) + + L[landscape_idx].extend( + [[(b_prime + d_prime) / 2, (d_prime - b_prime) / 2]] + ) + # size_landscapes[landscape_idx] += 1 + + b, d = b_prime, d_prime # Set (b',d')= (b, d) + + landscape_idx += 1 + + verboseprint("self.critical_pairs was empty and algorthim was executed") + self.max_depth = len(L) + self.critical_pairs = [item[1:-1] for item in L] + + def compute_landscape_by_depth(self, depth: int) -> list: + """ + Returns the function of depth from `self.critical_pairs` as a list + + Parameters + ---------- + depth: int + the depth of the desired landscape function + """ + + if self.critical_pairs: + return self.critical_pairs[depth] + else: + return self.compute_landscape()[depth] + + def p_norm(self, p: int = 2) -> float: + """ + Returns the L_{`p`} norm of an exact persistence landscape + + Parameters + ---------- + p: float, default 2 + value p of the L_{`p`} norm + """ + super().p_norm(p=p) + return _p_norm(p=p, critical_pairs=self.critical_pairs) + + def sup_norm(self) -> float: + """ + Returns the supremum norm of an exact persistence landscape + """ + + self.compute_landscape() + cvals = list(itertools.chain.from_iterable(self.critical_pairs)) + return max(np.abs(cvals), key=itemgetter(1))[1] diff --git a/persim/landscapes/tools.py b/persim/landscapes/tools.py new file mode 100644 index 0000000..d13eb39 --- /dev/null +++ b/persim/landscapes/tools.py @@ -0,0 +1,203 @@ +""" + Tools for working with exact and approximate persistence landscapes. +""" + +import numpy as np +from operator import itemgetter, attrgetter + +from .approximate import PersLandscapeApprox +from .exact import PersLandscapeExact + +__all__ = [ + "death_vector", + "vectorize", + "snap_pl", + "lc_approx", + "average_approx", +] + + +def death_vector(dgms: list, hom_deg: int = 0): + """Returns the death vector in degree 0 for the persistence diagram + + For Vietoris-Rips or Cech complexes, or any similar filtration, all bars in + homological degree 0 start at filtration value 0. Therefore, the discerning + information is the death values. The death vector is the vector of death times, + sorted from largest to smallest. + + Parameters + ---------- + dgms : list of persistence diagrams + + hom_deg : int specifying the homological degree + + """ + if hom_deg != 0: + raise NotImplementedError( + "The death vector is not defined for " + "homological degrees greater than zero." + ) + return sorted(dgms[hom_deg][:, 1], reverse=True) + + +def snap_pl( + pls: list, start: float = None, stop: float = None, num_steps: int = None +) -> list: + """Snap a list of PersLandscapeApprox tpes to a common grid + + Given a list `l` of PersLandscapeApprox types, convert them to a list + where each entry has the same start, stop, and num_steps. This puts each + entry of `l` on the same grid, so they can be added, averaged, etc. + This assumes they're all of the same homological degree. + + If the user + does not specify the grid parameters, they are computed as tightly as + possible from the input list `l`. + """ + if start is None: + start = min(pls, key=attrgetter("start")).start + if stop is None: + stop = max(pls, key=attrgetter("stop")).stop + if num_steps is None: + num_steps = max(pls, key=attrgetter("num_steps")).num_steps + grid = np.linspace(start, stop, num_steps) + k = [] + for pl in pls: + snapped_landscape = [] + for funct in pl: + # snap each function and store + snapped_landscape.append( + np.array( + np.interp(grid, np.linspace(pl.start, pl.stop, pl.num_steps), funct) + ) + ) + # store snapped persistence landscape + k.append( + PersLandscapeApprox( + start=start, + stop=stop, + num_steps=num_steps, + values=np.array(snapped_landscape), + hom_deg=pl.hom_deg, + ) + ) + return k + + +def lc_approx( + landscapes: list, + coeffs: list, + start: float = None, + stop: float = None, + num_steps: int = None, +) -> PersLandscapeApprox: + """Compute the linear combination of a list of PersLandscapeApprox objects. + + This uses vectorized arithmetic from numpy, so it should be faster and + more memory efficient than a standard for-loop. + + Parameters + ------- + landscapes: list + a list of PersLandscapeApprox objects + + coeffs: list + a list of the coefficients defining the linear combination + + start: float + starting value for the common grid for PersLandscapeApprox objects + in `landscapes` + + stop: float + last value in the common grid for PersLandscapeApprox objects + in `landscapes` + + num_steps: int + number of steps on the common grid for PersLandscapeApprox objects + in `landscapes` + + Returns + ------- + PersLandscapeApprox: + The specified linear combination of PersLandscapeApprox objects + in `landscapes` + + """ + pl = snap_pl(landscapes, start=start, stop=stop, num_steps=num_steps) + return np.sum(np.array(coeffs) * np.array(pl)) + + +def average_approx( + landscapes: list, start: float = None, stop: float = None, num_steps: int = None +) -> PersLandscapeApprox: + """Compute the average of a list of PersLandscapeApprox objects. + + Parameters + ------- + landscapes: list + a list of PersLandscapeApprox objects + + start: float, optional + starting value for the common grid for PersLandscapeApprox objects + in `landscapes` + + stop: float, optional + last value in the common grid for PersLandscapeApprox objects + in `landscapes` + + num_steps: int + number of steps on the common grid for PersLandscapeApprox objects + in `landscapes` + + Returns + ------- + PersLandscapeApprox: + The specified average of PersLandscapeApprox objects in `landscapes` + """ + return lc_approx( + landscapes=landscapes, + coeffs=[1.0 / len(landscapes) for _ in landscapes], + start=start, + stop=stop, + num_steps=num_steps, + ) + + +def vectorize( + l: PersLandscapeExact, start: float = None, stop: float = None, num_steps: int = 500 +) -> PersLandscapeApprox: + """Converts a `PersLandscapeExact` type to a `PersLandscapeApprox` type. + + Parameters + ---------- + start: float, default None + start value of grid + if start is not inputed, start is assigned to minimum birth value + + stop: float, default None + stop value of grid + if stop is not inputed, stop is assigned to maximum death value + + num_dims: int, default 500 + number of points starting from `start` and ending at `stop` + + """ + + l.compute_landscape() + if start is None: + start = min(l.critical_pairs[0], key=itemgetter(0))[0] + if stop is None: + stop = max(l.critical_pairs[0], key=itemgetter(0))[0] + grid = np.linspace(start, stop, num_steps) + result = [] + # creates sequential pairs of points for each lambda in critical_pairs + for depth in l.critical_pairs: + xs, ys = zip(*depth) + result.append(np.interp(grid, xs, ys)) + return PersLandscapeApprox( + start=start, + stop=stop, + num_steps=num_steps, + hom_deg=l.hom_deg, + values=np.array(result), + ) diff --git a/persim/landscapes/transformer.py b/persim/landscapes/transformer.py new file mode 100644 index 0000000..60bc495 --- /dev/null +++ b/persim/landscapes/transformer.py @@ -0,0 +1,133 @@ +""" + Implementation of scikit-learn transformers for persistence + landscapes. +""" +from operator import itemgetter +from sklearn.base import BaseEstimator, TransformerMixin + +from .approximate import PersLandscapeApprox + + +__all__ = ["PersistenceLandscaper"] + + +class PersistenceLandscaper(BaseEstimator, TransformerMixin): + """A scikit-learn transformer for converting persistence diagrams into persistence landscapes. + + Parameters + ---------- + hom_deg : int + Homological degree of persistence landscape. + + start : float, optional + Starting value of approximating grid. + + stop : float, optional + Stopping value of approximating grid. + + num_steps : int, optional + Number of steps of approximating grid. + + flatten : bool, optional + Determines if the resulting values are flattened. + + + Examples + -------- + First instantiate the PersistenceLandscaper:: + + >>> from persim import PersistenceLandscaper + >>> pl = PersistenceLandscaper(hom_deg=0, num_steps=10, flatten=True) + >>> print(pl) + + PersistenceLandscaper(hom_deg=1,num_steps=10) + + The `fit()` method is first called on a list of (-,2) numpy.ndarrays to determine the `start` and `stop` parameters of the approximating grid:: + + >>> ex_dgms = [np.array([[0,3],[1,4]]),np.array([[1,4]])] + >>> pl.fit(ex_dgms) + + PersistenceLandscaper(hom_deg=0, start=0, stop=4, num_steps=10) + + The `transform()` method will then compute the values of the landscape functions on the approximated grid. The `flatten` flag determines if the output should be a flattened numpy array:: + + >>> ex_pl = pl.transform(ex_dgms) + >>> ex_pl + + array([0. , 0.44444444, 0.88888889, 1.33333333, 1.33333333, + 1.33333333, 1.33333333, 0.88888889, 0.44444444, 0. , + 0. , 0. , 0. , 0.44444444, 0.88888889, + 0.88888889, 0.44444444, 0. , 0. , 0. ]) + """ + + def __init__( + self, + hom_deg: int = 0, + start: float = None, + stop: float = None, + num_steps: int = 500, + flatten: bool = False, + ): + self.hom_deg = hom_deg + self.start = start + self.stop = stop + self.num_steps = num_steps + self.flatten = flatten + + def __repr__(self): + if self.start is None or self.stop is None: + return f"PersistenceLandscaper(hom_deg={self.hom_deg}, num_steps={self.num_steps})" + else: + return f"PersistenceLandscaper(hom_deg={self.hom_deg}, start={self.start}, stop={self.stop}, num_steps={self.num_steps})" + + def fit(self, dgms): + """Find optimal `start` and `stop` parameters for approximating grid. + + Parameters + ---------- + + dgms : list of (-,2) numpy.ndarrays + List of persistence diagrams + """ + # TODO: remove infinities + _dgm = dgms[self.hom_deg] + if self.start is None: + self.start = min(_dgm, key=itemgetter(0))[0] + if self.stop is None: + self.stop = max(_dgm, key=itemgetter(1))[1] + return self + + def transform(self, dgms): + """Construct persistence landscape values. + + Parameters + ---------- + + dgms : list of (-,2) numpy.ndarrays + List of persistence diagrams + + flatten : bool, optional + Flag determining whether output values are flattened + + Returns + ------- + + numpy.ndarray + Persistence Landscape values sampled on approximating grid. + """ + result = PersLandscapeApprox( + dgms=dgms, + start=self.start, + stop=self.stop, + num_steps=self.num_steps, + hom_deg=self.hom_deg, + ) + if self.flatten: + return (result.values).flatten() + else: + return result.values + + def fit_transform(self, dgms): + self.fit(dgms=dgms) + vals = self.transform(dgms=dgms) + return vals diff --git a/persim/landscapes/visuals.py b/persim/landscapes/visuals.py new file mode 100644 index 0000000..972afb3 --- /dev/null +++ b/persim/landscapes/visuals.py @@ -0,0 +1,323 @@ +""" + Visualization methods for plotting persistence landscapes. +""" + +import itertools +from operator import itemgetter +import matplotlib as mpl +from matplotlib import cm +import matplotlib.pyplot as plt +import numpy as np + +from .base import PersLandscape +from .exact import PersLandscapeExact +from .approximate import PersLandscapeApprox + +mpl.rcParams["text.usetex"] = True + +__all__ = ["plot_landscape", "plot_landscape_simple"] + + +def plot_landscape( + landscape: PersLandscape, + num_steps: int = 3000, + colormap="default", + title=None, + labels=None, + ax=None, +): + """ + Plot landscape functions + """ + if isinstance(landscape, PersLandscapeApprox): + return plot_landscape_approx( + landscape=landscape, + num_steps=num_steps, + colormap=colormap, + title=title, + labels=labels, + ax=ax, + ) + if isinstance(landscape, PersLandscapeExact): + return plot_landscape_exact( + landscape=landscape, + num_steps=num_steps, + colormap=colormap, + title=title, + labels=labels, + ax=ax, + ) + + +def plot_landscape_simple( + landscape: PersLandscape, + alpha=1, + padding=0.1, + num_steps=1000, + title=None, + ax=None, +): + """ + plot landscape functions. + """ + if isinstance(landscape, PersLandscapeExact): + return plot_landscape_exact_simple( + landscape=landscape, alpha=alpha, title=title, ax=ax + ) + + if isinstance(landscape, PersLandscapeApprox): + return plot_landscape_approx_simple( + landscape=landscape, + alpha=alpha, + padding=padding, + num_steps=num_steps, + title=title, + ax=ax, + ) + + +def plot_landscape_exact( + landscape: PersLandscapeExact, + num_steps: int = 3000, + colormap="default", + alpha=0.8, + labels=None, + padding: float = 0.1, + depth_padding: float = 0.7, + title=None, + ax=None, +): + """ + A plot of the exact persistence landscape. + + Warning: This function is quite slow, especially for large landscapes. + + Parameters + ---------- + num_steps: int, default 3000 + number of sampled points that are plotted + + color, defualt cm.viridis + color scheme for shading of landscape functions + + alpha, default 0.8 + transparency of shading + + padding: float, default 0.1 + amount of empty grid shown to left and right of landscape functions + + depth_padding: float, default = 0.7 + amount of space between sequential landscape functions + + """ + fig = plt.figure() + plt.style.use(colormap) + ax = fig.gca(projection="3d") + landscape.compute_landscape() + # itemgetter index selects which entry to take max/min wrt. + # the hanging [0] or [1] takes that entry. + crit_pairs = list(itertools.chain.from_iterable(landscape.critical_pairs)) + min_crit_pt = min(crit_pairs, key=itemgetter(0))[0] # smallest birth time + max_crit_pt = max(crit_pairs, key=itemgetter(0))[0] # largest death time + max_crit_val = max(crit_pairs, key=itemgetter(1))[1] # largest peak of landscape + min_crit_val = min(crit_pairs, key=itemgetter(1))[1] # smallest peak of landscape + norm = mpl.colors.Normalize(vmin=min_crit_val, vmax=max_crit_val) + scalarMap = mpl.cm.ScalarMappable(norm=norm) + # x-axis for grid + domain = np.linspace( + min_crit_pt - padding * 0.1, max_crit_pt + padding * 0.1, num=num_steps + ) + # for each landscape function + for depth, l in enumerate(landscape): + # sequential pairs in landscape + xs, zs = zip(*l) + image = np.interp(domain, xs, zs) + for x, z in zip(domain, image): + if z == 0.0: + # plot a single point here? + continue # moves to the next iterable in for loop + if z > 0.0: + ztuple = [0, z] + elif z < 0.0: + ztuple = [z, 0] + # for coloring https://matplotlib.org/3.1.0/tutorials/colors/colormapnorms.html + ax.plot( + [x, x], # plotting a line to get shaded function + [depth_padding * depth, depth_padding * depth], + ztuple, + linewidth=0.5, + alpha=alpha, + # c=colormap(norm(z))) + c=scalarMap.to_rgba(z), + ) + ax.plot([x], [depth_padding * depth], [z], "k.", markersize=0.1) + ax.set_ylabel("depth") + if title: + plt.title(title) + ax.view_init(10, 90) + plt.show() + + +def plot_landscape_exact_simple( + landscape: PersLandscapeExact, alpha=1, title=None, ax=None +): + """ + A simple plot of the persistence landscape. This is a faster plotting utility than the standard plotting, but is recommended for smaller landscapes for ease of visualization. + + + Parameters + ---------- + alpha, default 1 + transparency of shading + + """ + ax = ax or plt.gca() + landscape.compute_landscape() + crit_pairs = list(itertools.chain.from_iterable(landscape.critical_pairs)) + min_crit_pt = min(crit_pairs, key=itemgetter(0))[0] # smallest birth time + max_crit_pt = max(crit_pairs, key=itemgetter(0))[0] # largest death time + max_crit_val = max(crit_pairs, key=itemgetter(1))[1] # largest peak of landscape + min_crit_val = min(crit_pairs, key=itemgetter(1))[1] # smallest peak of landscape + # for each landscape function + for depth, l in enumerate(landscape): + ls = np.array(l) + ax.plot(ls[:, 0], ls[:, 1], label=f"$\lambda_{{{depth}}}$", alpha=alpha) + ax.legend() + if title: + ax.set_title(title) + + +def plot_landscape_approx( + landscape: PersLandscapeApprox, + num_steps: int = 3000, + colormap="default", + labels=None, + alpha=0.8, + padding: float = 0.1, + depth_padding: float = 0.7, + title=None, + ax=None, +): + """ + A plot of the approximate persistence landscape. + + Warning: This function is quite slow, especially for large landscapes. + + Parameters + ---------- + num_steps: int, default 3000 + number of sampled points that are plotted + + color, defualt cm.viridis + color scheme for shading of landscape functions + + alpha, default 0.8 + transparency of shading + + padding: float, default 0.1 + amount of empty grid shown to left and right of landscape functions + + depth_padding: float, default = 0.7 + amount of space between sequential landscape functions + + """ + fig = plt.figure() + ax = fig.gca(projection="3d") + plt.style.use(colormap) + landscape.compute_landscape() + # TODO: RE the following line: is this better than np.concatenate? + # There is probably an even better way without creating an intermediary. + _vals = list(itertools.chain.from_iterable(landscape.values)) + min_val = min(_vals) + max_val = max(_vals) + norm = mpl.colors.Normalize(vmin=min_val, vmax=max_val) + scalarMap = mpl.cm.ScalarMappable(norm=norm) + # x-axis for grid + domain = np.linspace( + landscape.start - padding * 0.1, landscape.stop + padding * 0.1, num=num_steps + ) + # for each landscape function + for depth, l in enumerate(landscape): + # sequential pairs in landscape + # xs, zs = zip(*l) + image = np.interp( + domain, + np.linspace( + start=landscape.start, stop=landscape.stop, num=landscape.num_steps + ), + l, + ) + for x, z in zip(domain, image): + if z == 0.0: + # plot a single point here? + continue # moves to the next iterable in for loop + if z > 0.0: + ztuple = [0, z] + elif z < 0.0: + ztuple = [z, 0] + # for coloring https://matplotlib.org/3.1.0/tutorials/colors/colormapnorms.html + ax.plot( + [x, x], # plotting a line to get shaded function + [depth_padding * depth, depth_padding * depth], + ztuple, + linewidth=0.5, + alpha=alpha, + # c=colormap(norm(z))) + c=scalarMap.to_rgba(z), + ) + ax.plot([x], [depth_padding * depth], [z], "k.", markersize=0.1) + + # ax.set_xlabel('X') + ax.set_ylabel("depth") + if title: + plt.title(title) + ax.view_init(10, 90) + plt.show() + + +def plot_landscape_approx_simple( + landscape: PersLandscapeApprox, + alpha=1, + padding=0.1, + num_steps=1000, + title=None, + ax=None, +): + """ + A simple plot of the persistence landscape. This is a faster plotting utility than the standard plotting, but is recommended for smaller landscapes for ease of visualization. + + Parameters + ---------- + alpha, default 1 + transparency of shading + + padding: float, default 0.1 + amount of empty grid shown to left and right of landscape functions + + num_steps: int, default 1000 + number of sampled points that are plotted + + """ + ax = ax or plt.gca() + + landscape.compute_landscape() + + # TODO: RE the following line: is this better than np.concatenate? + # There is probably an even better way without creating an intermediary. + _vals = list(itertools.chain.from_iterable(landscape.values)) + min_val = min(_vals) + max_val = max(_vals) + + # for each landscape function + for depth, l in enumerate(landscape): + + # instantiate depth-specific domain + domain = np.linspace( + landscape.start - padding * 0.1, landscape.stop + padding * 0.1, num=len(l) + ) + + ax.plot(domain, l, label=f"$\lambda_{{{depth}}}$", alpha=alpha) + + ax.legend() + if title: + ax.set_title(title) diff --git a/setup.py b/setup.py index 1804c1a..7ed01c0 100644 --- a/setup.py +++ b/setup.py @@ -21,8 +21,8 @@ description='Distances and representations of persistence diagrams', long_description=long_description, long_description_content_type="text/markdown", - author='Nathaniel Saul, Chris Tralie, Francis Motta', - author_email='nat@riverasaul.com, chris.tralie@gmail.com, francis.c.motta@gmail.com', + author='Nathaniel Saul, Chris Tralie, Francis Motta, Michael Catanzaro, Gabrielle Angeloro, Calder Sheagren', + author_email='nat@riverasaul.com, chris.tralie@gmail.com, francis.c.motta@gmail.com, catanzaromj@gmail.com, gabrielleangeloro@gmail.com, caldersheagren@gmail.com', url='https://persim.scikit-tda.org', license='MIT', packages=['persim'], diff --git a/test/test_landscapes.py b/test/test_landscapes.py new file mode 100644 index 0000000..6765646 --- /dev/null +++ b/test/test_landscapes.py @@ -0,0 +1,534 @@ +import pytest +import numpy as np + +from persim.landscapes import PersLandscapeExact +from persim.landscapes import PersLandscapeApprox +from persim.landscapes import PersistenceLandscaper +from persim.landscapes import vectorize, snap_pl, lc_approx, average_approx +from persim.landscapes import death_vector + + +class TestPersLandscapeExact: + def test_exact_empty(self): + with pytest.raises(ValueError): + PersLandscapeExact() + + def test_exact_hom_deg(self): + P = PersLandscapeExact(dgms=[np.array([[1.0, 5.0]])], hom_deg=0,) + assert P.hom_deg == 0 + with pytest.raises(ValueError): + PersLandscapeExact(hom_deg=-1) + + def test_exact_critical_pairs(self): + assert not PersLandscapeExact( + dgms=[np.array([[0, 3]])], compute=False + ).critical_pairs + # example from Peter & Pavel's paper + P = PersLandscapeExact( + dgms=[ + np.array([[1.0, 5.0], [2.0, 8.0], [3.0, 4.0], [5.0, 9.0], [6.0, 7.0]]) + ], + hom_deg=0, + ) + P.compute_landscape() + + # duplicate bars + Q = PersLandscapeExact(dgms=[np.array([[1, 5], [1, 5], [3, 6]])], hom_deg=0) + Q.compute_landscape() + + np.testing.assert_array_equal( + P.critical_pairs, + [ + [ + [1.0, 0], + [3.0, 2.0], + [3.5, 1.5], + [5.0, 3.0], + [6.5, 1.5], + [7.0, 2.0], + [9.0, 0], + ], + [[2.0, 0], [3.5, 1.5], [5.0, 0], [6.5, 1.5], [8.0, 0]], + [[3.0, 0], [3.5, 0.5], [4.0, 0], [6.0, 0], [6.5, 0.5], [7.0, 0]], + ], + ) + + np.testing.assert_array_equal( + Q.critical_pairs, + [ + [[1, 0], [3.0, 2.0], [4.0, 1.0], [4.5, 1.5], [6, 0]], + [[1, 0], [3.0, 2.0], [4.0, 1.0], [4.5, 1.5], [6, 0]], + [[3, 0], [4.0, 1.0], [5, 0]], + ], + ) + + def test_exact_add(self): + with pytest.raises(ValueError): + PersLandscapeExact( + critical_pairs=[[[0, 0], [1, 1]]], hom_deg=0 + ) + PersLandscapeExact(critical_pairs=[[[0, 0], [1, 1]]], hom_deg=1) + Q = PersLandscapeExact( + critical_pairs=[[[0, 0], [1, 1], [2, 2]]] + ) + PersLandscapeExact(critical_pairs=[[[0, 0], [0.5, 1], [1.5, 3]]]) + np.testing.assert_array_equal( + Q.critical_pairs, [[[0, 0], [0.5, 1.5], [1, 3], [1.5, 4.5], [2, 5]]] + ) + + def test_exact_neg(self): + P = PersLandscapeExact( + critical_pairs=[[[0, 0], [1, 1], [2, 1], [3, 1], [4, 0]]] + ) + assert (-P).critical_pairs == [[[0, 0], [1, -1], [2, -1], [3, -1], [4, 0]]] + Q = PersLandscapeExact(critical_pairs=[[[0, 0], [5, 0]]]) + assert (-Q).critical_pairs == Q.critical_pairs + + def test_exact_mul(self): + P = PersLandscapeExact( + critical_pairs=[[[0, 0], [1, 2], [2, 0], [3, -1], [4, 0]]] + ) + np.testing.assert_array_equal( + (4 * P).critical_pairs, [[[0, 0], [1, 8], [2, 0], [3, -4], [4, 0]]] + ) + np.testing.assert_array_equal( + (P * (-1)).critical_pairs, [[[0, 0], [1, -2], [2, 0], [3, 1], [4, 0]]] + ) + + def test_exact_div(self): + P = PersLandscapeExact( + critical_pairs=[[[0, 0], [1, 2], [2, 0], [3, -1], [4, 0]]] + ) + np.testing.assert_array_equal( + (P / 2).critical_pairs, [[[0, 0], [1, 1], [2, 0], [3, -0.5], [4, 0]]] + ) + with pytest.raises(ValueError): + P / 0 + + def test_exact_get_item(self): + P = PersLandscapeExact(dgms=[np.array([[1, 5], [1, 5], [3, 6]])]) + np.testing.assert_array_equal( + P[1], [[1, 0], [3, 2], [4, 1], [4.5, 1.5], [6, 0]] + ) + with pytest.raises(IndexError): + P[3] + + def test_exact_norm(self): + P = PersLandscapeExact( + critical_pairs=[[[0, 0], [1, 1], [2, 1], [3, 1], [4, 0]]], hom_deg=0 + ) + negP = PersLandscapeExact( + critical_pairs=[[[0, 0], [1, -1], [2, -1], [3, -1], [4, 0]]], hom_deg=0 + ) + assert P.sup_norm() == 1 + assert P.p_norm(p=2) == pytest.approx(np.sqrt(2 + (2.0 / 3.0))) + assert P.p_norm(p=5) == pytest.approx((2 + (1.0 / 3.0)) ** (1.0 / 5.0)) + assert P.p_norm(p=113) == pytest.approx((2 + (1.0 / 57.0)) ** (1.0 / 113.0)) + assert negP.sup_norm() == 1 + assert negP.p_norm(p=2) == pytest.approx(np.sqrt(2 + (2.0 / 3.0))) + assert negP.p_norm(p=5) == pytest.approx((2 + (1.0 / 3.0)) ** (1.0 / 5.0)) + assert negP.p_norm(p=113) == pytest.approx((2 + (1.0 / 57.0)) ** (1.0 / 113.0)) + + +class TestPersLandscapeApprox: + def test_approx_empty(self): + with pytest.raises(ValueError): + PersLandscapeApprox() + + def test_approx_compute_flag(self): + assert ( + PersLandscapeApprox(dgms=[np.array([[0, 4]])], compute=False).values.size + == 0 + ) + + def test_approx_hom_deg(self): + with pytest.raises(IndexError): + PersLandscapeApprox(dgms=[np.array([[2, 6], [4, 10]])], hom_deg=2) + with pytest.raises(ValueError): + PersLandscapeApprox(hom_deg=-1) + assert ( + PersLandscapeApprox( + dgms=[np.array([[2, 6], [4, 10]]), np.array([[1, 5], [4, 6]])], + hom_deg=1, + ).hom_deg + == 1 + ) + + def test_approx_grid_params(self): + with pytest.raises(ValueError): + PersLandscapeApprox(values=np.array([[2, 6], [4, 10]]), start=1) + with pytest.raises(ValueError): + PersLandscapeApprox(values=np.array([[2, 6], [4, 10]]), stop=11) + with pytest.raises(ValueError): + PersLandscapeApprox(values=np.array([[2, 6], [4, 10]]), start=3, stop=2) + P = PersLandscapeApprox(dgms=[np.array([[0, 3], [1, 4]])], num_steps=100) + assert P.start == 0 + assert P.stop == 4 + assert P.num_steps == 100 + Q = PersLandscapeApprox(values=np.array([[2, 6], [4, 10]]), start=0, stop=5) + assert Q.start == 0 + assert Q.stop == 5 + + def test_approx_compute_landscape(self): + diagrams1 = [np.array([[2, 6], [4, 10]])] + P1 = PersLandscapeApprox( + start=0, stop=10, num_steps=11, dgms=diagrams1, hom_deg=0 + ) + P2 = PersLandscapeApprox( + start=0, stop=10, num_steps=6, dgms=diagrams1, hom_deg=0 + ) + P3 = PersLandscapeApprox( + start=0, stop=10, num_steps=21, dgms=diagrams1, hom_deg=0 + ) + + # duplicate bars + diagrams2 = [np.array([[2, 6], [2, 6], [4, 10]])] + Q2 = PersLandscapeApprox( + start=0, stop=10, num_steps=11, dgms=diagrams2, hom_deg=0 + ) + + # edge case: bars start same value + diagrams3 = [np.array([[3, 5], [3, 7]])] + Q3 = PersLandscapeApprox( + start=0, stop=10, num_steps=11, dgms=diagrams3, hom_deg=0 + ) + + # edge case: bars end same value + diagrams4 = [np.array([[2, 6], [4, 6]])] + Q4 = PersLandscapeApprox( + start=0, stop=10, num_steps=11, dgms=diagrams4, hom_deg=0 + ) + np.testing.assert_array_equal( + P1.values, + np.array( + [ + [0.0, 0.0, 0.0, 1.0, 2.0, 1.0, 2.0, 3.0, 2.0, 1.0, 0.0], + [0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0], + ] + ), + ) + + np.testing.assert_array_equal( + P2.values, np.array([[0.0, 0.0, 2.0, 2.0, 2.0, 0.0]]) + ) + + np.testing.assert_array_equal( + P3.values, + np.array( + [ + [ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.5, + 1.0, + 1.5, + 2.0, + 1.5, + 1.0, + 1.5, + 2.0, + 2.5, + 3.0, + 2.5, + 2.0, + 1.5, + 1.0, + 0.5, + 0.0, + ], + [ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.5, + 1.0, + 0.5, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + ], + ] + ), + ) + + np.testing.assert_array_equal( + Q2.values, + np.array( + [ + [0.0, 0.0, 0.0, 1.0, 2.0, 1.0, 2.0, 3.0, 2.0, 1.0, 0.0], + [0.0, 0.0, 0.0, 1.0, 2.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0], + ] + ), + ) + + np.testing.assert_array_equal( + Q3.values, + np.array( + [ + [0.0, 0.0, 0.0, 0.0, 1.0, 2.0, 1.0, 0.0, 0.0, 0.0, 0.0], + [0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + ] + ), + ) + + np.testing.assert_array_equal( + Q4.values, + np.array( + [ + [0.0, 0.0, 0.0, 1.0, 2.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0], + ] + ), + ) + + def test_approx_values_to_pairs(self): + diagrams1 = [np.array([[2, 6], [4, 10]])] + P1 = PersLandscapeApprox( + start=0, stop=10, num_steps=11, dgms=diagrams1, hom_deg=0 + ) + np.testing.assert_array_equal( + P1.values_to_pairs(), + np.array( + [ + [ + [0, 0], + [1, 0], + [2, 0], + [3, 1], + [4, 2], + [5, 1], + [6, 2], + [7, 3], + [8, 2], + [9, 1], + [10, 0], + ], + [ + [0, 0], + [1, 0], + [2, 0], + [3, 0], + [4, 0], + [5, 1], + [6, 0], + [7, 0], + [8, 0], + [9, 0], + [10, 0], + ], + ] + ), + ) + + def test_approx_add(self): + with pytest.raises(ValueError): + PersLandscapeApprox( + dgms=[np.array([[0, 1]])], start=0, stop=2 + ) + PersLandscapeApprox(dgms=[np.array([[0, 1]])], start=1, stop=2) + with pytest.raises(ValueError): + PersLandscapeApprox( + dgms=[np.array([[0, 1]])], start=0, stop=2 + ) + PersLandscapeApprox(dgms=[np.array([[0, 1]])], start=0, stop=3) + with pytest.raises(ValueError): + PersLandscapeApprox( + dgms=[np.array([[0, 1]])], start=0, stop=2, num_steps=100 + ) + PersLandscapeApprox( + dgms=[np.array([[0, 1]])], start=1, stop=2, num_steps=200 + ) + with pytest.raises(ValueError): + PersLandscapeApprox( + dgms=[np.array([[0, 1], [1, 2]])], hom_deg=0 + ) + PersLandscapeApprox( + dgms=[np.array([[0, 1], [1, 2]]), np.array([[1, 3]])], hom_deg=1 + ) + + Q = PersLandscapeApprox( + start=0, stop=5, num_steps=6, dgms=[np.array([[1, 4]])] + ) + PersLandscapeApprox(start=0, stop=5, num_steps=6, dgms=[np.array([[2, 5]])]) + np.testing.assert_array_equal(Q.values, np.array([[0, 0, 1, 2, 1, 0]])) + + def test_approx_neg(self): + P = PersLandscapeApprox( + start=0, stop=5, num_steps=6, dgms=[np.array([[0, 5], [1, 3]])] + ) + np.testing.assert_array_equal( + (-P).values, np.array([[0, -1, -2, -2, -1, 0], [0, 0, -1, 0, 0, 0]]) + ) + + def test_approx_sub(self): + P = PersLandscapeApprox( + start=0, + stop=5, + num_steps=6, + values=np.array([[0, 1, 2, 2, 1, 0], [0, 0, 1, 0, 0, 0]]), + ) + Q = PersLandscapeApprox( + start=0, stop=5, num_steps=6, values=np.array([[0, 1, 1, 1, 1, 0]]) + ) + np.testing.assert_array_equal( + (P - Q).values, np.array([[0, 0, 1, 1, 0, 0], [0, 0, 1, 0, 0, 0]]) + ) + + def test_approx_mul(self): + P = PersLandscapeApprox( + start=0, + stop=5, + num_steps=6, + values=np.array([[0, 1, 2, 2, 1, 0], [0, 0, 1, 0, 0, 0]]), + ) + np.testing.assert_array_equal( + (3 * P).values, np.array([[0, 3, 6, 6, 3, 0], [0, 0, 3, 0, 0, 0]]) + ) + + def test_approx_div(self): + P = PersLandscapeApprox( + start=0, + stop=5, + num_steps=6, + values=np.array([[0, 1, 2, 2, 1, 0], [0, 0, 1, 0, 0, 0]]), + ) + with pytest.raises(ValueError): + P / 0 + np.testing.assert_array_equal( + (P / 2).values, np.array([[0, 0.5, 1, 1, 0.5, 0], [0, 0, 0.5, 0, 0, 0]]) + ) + + def test_approx_get_item(self): + P = PersLandscapeApprox( + start=0, + stop=5, + num_steps=6, + values=np.array([[0, 1, 2, 2, 1, 0], [0, 0, 1, 0, 0, 0]]), + ) + with pytest.raises(IndexError): + P[3] + np.testing.assert_array_equal(P[1], np.array([0, 0, 1, 0, 0, 0])) + + def test_approx_norm(self): + P = PersLandscapeApprox( + start=0, stop=5, num_steps=6, values=np.array([[0, 1, 1, 1, 1, 0]]), + ) + assert P.p_norm(p=2) == pytest.approx(np.sqrt(3 + (2.0 / 3.0))) + assert P.sup_norm() == 1.0 + Q = PersLandscapeApprox( + start=0, + stop=5, + num_steps=6, + values=np.array([[0, 1, 2, 2, 1, 0], [0, 0, 1, 1, 0, 0]]), + ) + assert Q.p_norm(p=3) == pytest.approx((16 + 3.0 / 2.0) ** (1.0 / 3.0)) + assert Q.sup_norm() == 2.0 + + +class TestAuxiliary: + def test_vectorize(self): + P = PersLandscapeExact(dgms=[np.array([[0, 5], [1, 4]])]) + Q = vectorize(P, start=0, stop=5, num_steps=6) + assert Q.hom_deg == P.hom_deg + assert Q.start == 0 + assert Q.stop == 5 + np.testing.assert_array_equal( + Q.values, np.array([[0, 1, 2, 2, 1, 0], [0, 0, 1, 1, 0, 0]]) + ) + R = vectorize(P) + assert R.start == 0 + assert R.stop == 5 + + def test_snap_PL(self): + P = PersLandscapeApprox( + start=0, stop=5, num_steps=6, values=np.array([[0, 1, 1, 1, 1, 0]]), + ) + [P_snapped] = snap_pl([P], start=0, stop=10, num_steps=11) + assert P_snapped.hom_deg == P.hom_deg + assert P_snapped.start == 0 + assert P_snapped.stop == 10 + assert P_snapped.num_steps == 11 + np.testing.assert_array_equal( + P_snapped.values, np.array([[0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0]]) + ) + Q = PersLandscapeApprox( + start=1, stop=6, num_steps=6, values=np.array([[0, 1, 2, 2, 1, 0]]) + ) + [P_snap, Q_snap] = snap_pl([P, Q], start=0, stop=10, num_steps=11) + assert P_snap.start == 0 + assert Q_snap.stop == 10 + assert P_snap.num_steps == Q_snap.num_steps + np.testing.assert_array_equal( + Q_snap.values, np.array([[0, 0, 1, 2, 2, 1, 0, 0, 0, 0, 0]]) + ) + + def test_lc_approx(self): + P = PersLandscapeApprox( + start=0, + stop=10, + num_steps=11, + values=np.array([[0, 1, 1, 1, 1, 0, 0, 1, 1, 0, 0]]), + ) + Q = PersLandscapeApprox( + start=0, + stop=10, + num_steps=11, + values=np.array([[0, 1, 2, 2, 1, 0, 1, 2, 3, 2, 0]]), + ) + lc = lc_approx([P, Q], [2, -1]) + np.testing.assert_array_equal( + lc.values, np.array([[0, 1, 0, 0, 1, 0, -1, 0, -1, -2, 0]]) + ) + + def test_average_approx(self): + P = PersLandscapeApprox( + start=0, stop=5, num_steps=6, values=np.array([[0, 1, 2, 3, 2, 1]]) + ) + Q = PersLandscapeApprox( + start=0, stop=5, num_steps=6, values=np.array([[0, -1, -2, -1, 0, 1]]) + ) + np.testing.assert_array_equal( + average_approx([P, Q]).values, np.array([[0, 0, 0, 1, 1, 1]]) + ) + + def test_death_vector(self): + dgms = [np.array([[0, 4], [0, 1], [0, 10]])] + np.testing.assert_array_equal(death_vector(dgms), [10, 4, 1]) + + +class TestTransformer: + def test_persistenceimager(self): + pl = PersistenceLandscaper(hom_deg=0, num_steps=5, flatten=True) + assert pl.hom_deg == 0 + assert not pl.start + assert not pl.stop + assert pl.num_steps == 5 + assert pl.flatten + dgms = [np.array([[0, 3], [1, 4]]), np.array([[1, 4]])] + pl.fit(dgms) + assert pl.start == 0 + assert pl.stop == 4.0 + np.testing.assert_array_equal( + pl.transform(dgms), + np.array([0.0, 1.0, 1.0, 1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0,]), + ) + pl2 = PersistenceLandscaper(hom_deg=1, num_steps=4) + assert pl2.hom_deg == 1 + pl2.fit(dgms) + assert pl2.start == 1.0 + assert pl2.stop == 4.0 + np.testing.assert_array_equal(pl2.transform(dgms), [[0.0, 1.0, 1.0, 0.0]]) + pl3 = PersistenceLandscaper(hom_deg=0, num_steps=5, flatten=True) + np.testing.assert_array_equal( + pl3.fit_transform(dgms), + np.array([0.0, 1.0, 1.0, 1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0,]), + )