Revision bc4ae43da0ba264e180a4f05f33f25a7f53724e2 authored by Susanne Zabel on 30 March 2021, 09:06:11 UTC, committed by Susanne Zabel on 30 March 2021, 09:06:11 UTC
1 parent b252134
PCA.cpython-37.pyc
B
7iG`1 � @ s| d dl mZ d dlZd dlmZ e�dd� d dlm Z d dlmZ d dl m
Z d dl m Z d a
dd � ZG d
d � d e �ZdS ) � )�arrayN)�configZjax_enable_x64T)�jacrev)�DimensionReductionMethodc C s� | t j| dd� } d| jd t �t �| �| � }t j�|�\}}t j| dd�}t j| dd� }t �|d d �|f �dt �d d �f }|dt � |fS )Nr )�axis� )
�np�mean�shape�dot� transpose�linalg�eigh�argsort�sort� N_COMPONENTS)�X�
covariance� eigenvalues� eigenvectors�sorting� r �6/share/home/zabel/projects_romanov/jax/src2/jax/PCA.py� pca_forward s &r c @ sf e Zd ZdZdd� Zdd� Zddd�Zd d
� Zd d � Zd
d� Z ddd�Z
ddd�Z dd� Z dd� Z
dS )�PCAan PCA: Class computing the PCA and corresponding Jacobian of a matrix.
Attributes:
matrix (DataMatrix): Instance of the DataMatrix class
n_compontents (int): Number of output dimensions
axis (int): 0 or 1 indicating if features are in columns (0) or rows (1)
compute_jacobian (Bool): indicates if jacobian should be computed or notc O s6 t j| f|� d | _d | _d | _d | _d | _d | _d S )N)r �__init__r r r �cov_eigenvectors�jacobian_eigenvalues�cov_eigenvalues)�self�args�kwargsr r r r $ s z PCA.__init__c C s� | j tj| j dd� | _ d| j jd t�t�| j �| j � | _tj�| j�\| _ | _
tj | j dd�}tj | j dd�d| j
� | _ t�| j
d d �|f �d| j
�d d �f | _
d S )Nr )r r )�matrixr r r
r r r r
r r r r r � n_components)r r r r r � pca_value- s ( z
PCA.pca_valueTc C s� | j r,| jatt�| j�\| _| _| �� n| �� t �
| j �| _ | j r�t � t j | j| j| j
d | j
d | j
d fdd�| j
d | j | j
d | j
d f�| _t � | j| j| j
d | j
d f�| _d S )Nr r �F)�order)Zcompute_jacobianr# r r r r" r �jacobianr$ r r r Zreshape�size)r �centerr r r �pca_grad5 s
2z PCA.pca_gradc C s< | j d krtd��n$t�| j| jd d �d| j�f �| _d S )Nz.eigenvalues and eigenvectors not computed yet.r )r � Exceptionr r r" r r# Ztransformed_data)r r r r �transform_dataI s
zPCA.transform_datac
C s� | j r^t�| jd| j| jd �d d �f | j t�| jd| j| jd �d d �f ��| _nZt�t�| jd| j| jd �d d �f | j�t�| jd| j| jd �d d �f ��| _d S )Nr r ) �diagonal_data_covr r r' r# r( �cov_datar r )r r r r �compute_cov_eigenvectorsO s Xz PCA.compute_cov_eigenvectorsc C s� | j rJt�| jd| j�d d �f | j t�| jd| j�d d �f ��| _nFt�t�| jd| j�d d �f | j�t�| jd| j�d d �f ��| _d S )Nr )r- r r r r# r. r r )r r r r �compute_cov_eigenvaluesU s D$zPCA.compute_cov_eigenvaluesNc C s� |d krt | j�}t�� }t�dd� td|�D �| jt�| j� d|� � tjdd� td|�D �t� | jt�| j� �d|� ddd� t�
d� d S ) Nc S s g | ]}|�qS r r )�.0�ir r r �
<listcomp>` s z?PCA.plot_variance_explained_by_eigenvectors.<locals>.<listcomp>r c S s g | ]}|�qS r r )r1 r2 r r r r3 a s z-boZred)�cz var_explained_by_eigenvalues.png) �lenr �plt�figureZbar�ranger �sumZplotZcumsum�savefig)r �n�figr r r �'plot_variance_explained_by_eigenvectors\ s
2>z+PCA.plot_variance_explained_by_eigenvectorsc
sn |d krt � j�}t�� }tjdd� td|d �D �� j� fdd�t|�D �ddddd d
� t�|d � d S ) Nc S s g | ]}|�qS r r )r1 r2 r r r r3 h s z4PCA.plot_uncertainty_eigenvalues.<locals>.<listcomp>r c s g | ]}t �� j�||f �qS r )r Zsqrtr )r1 r2 )r r r r3 j s �oZblackZ lightgray� r )�x�yZyerrZfmtZcolorZecolorZ
elinewidthZcapsizezeigenvalues_uncertainty.png)r5 r r6 r7 Zerrorbarr8 r: )r �outfiler; r< r )r r � plot_uncertainty_eigenvaluesd s
z PCA.plot_uncertainty_eigenvaluesc C s2 t �� }t j| jdd� t �� t �|d � d S )N�Blues)�cmapzcov_matrix_eigenvalues.png)r6 r7 �imshowr �colorbarr: )r rB r< r r r �plot_cov_eigenvaluesq s zPCA.plot_cov_eigenvaluesc C s2 t �� }t j| jdd� t �� t �|d � d S )NrD )rE zcov_matrix_eigenvectors.png)r6 r7 rF r rG r: )r rB r< r r r �plot_cov_eigenvectorsw s zPCA.plot_cov_eigenvectors)T)N)N)�__name__�
__module__� __qualname__�__doc__r r$ r* r, r/ r0 r= rC rH rI r r r r r s
r )Znumpyr ZjaxZ
jax.configr �updateZ jax.numpyr r Zmatplotlib.pyplotZpyplotr6 r r r r r r r r �<module> s
Computing file changes ...
