OwlCyberSecurity - MANAGER
Edit File: test_mlab.cpython-38.pyc
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s "z5TestGaussianKDECustom.test_silverman_multidim_datasetc C s8 t �dddddg�}t�|d�}d}t|�� |d� d S ) zOUse a single dimension list as the dataset and test silverman's output.r� r r rM r% r g/�����?rf N�r r7 r+ r� r �covariance_factor�r rK Zmygaussr� r r r � test_silverman_singledim_datasetF s z6TestGaussianKDECustom.test_silverman_singledim_datasetc C sL t �dddgdddgddd gg�}t�t jj�� t�|d � W 5 Q R X d S ) zMUse a multi-dimensional array as the dataset and test scott's output r r0 r1 rM r% rj rf r rg r Nr r r r r �test_scott_multidim_datasetN s "z1TestGaussianKDECustom.test_scott_multidim_datasetc C s8 t �dddddg�}t�|d�}d}t|�� |d� d S ) zMUse a single-dimensional array as the dataset and test scott's outputr� r r rM r% r g�� e1�?rf Nr r r r r � test_scott_singledim_datasetU s z2TestGaussianKDECustom.test_scott_singledim_datasetc C s( t �t�� tjg dd� W 5 Q R X dS )zKUse an empty array as the dataset and test the scalar's cov factor r% r Nr r| r r r �test_scalar_empty_dataset] s z/TestGaussianKDECustom.test_scalar_empty_datasetc sH t j�d� d� � fdd�td�D �}tj|dd�}|�� dksDt�dS ) z5Use a dataset and test a scalar's cov factor r rn c s g | ]}t j�� ��qS r �r ry r� �rS r �r r r rW h s zHTestGaussianKDECustom.test_scalar_covariance_dataset.<locals>.<listcomp>r% g �?r N�r ry rz r r+ r� r r; )r � multidim_datar� r r r � test_scalar_covariance_datasetc s z4TestGaussianKDECustom.test_scalar_covariance_datasetc sP t j�d� d� � fdd�td�D �}dd� }tj||d�}|�� d ksLt�d S ) zWUse a multi-dimensional array as the dataset and test the callable's cov factorr rn c s g | ]}t j�� ��qS r r r r r r rW r s zJTestGaussianKDECustom.test_callable_covariance_dataset.<locals>.<listcomp>r% c S s dS )N皙�����?r )r r r r � callable_funt s zLTestGaussianKDECustom.test_callable_covariance_dataset.<locals>.callable_funr r# Nr )r r! r$ r� r r r � test_callable_covariance_datasetm s z6TestGaussianKDECustom.test_callable_covariance_datasetc C sB t j�d� d}t j�|�}tj|dd�}d}t|�� |d� dS )zXUse a single-dimensional array as the dataset and test the callable's cov factorr rn r r g}�B8 �?rf N)r ry rz r� r+ r� r r )r r r! r� r� r r r � test_callable_singledim_datasety s z5TestGaussianKDECustom.test_callable_singledim_datasetc C sD t j�d� d}t j�|�}t�t�� tj|dd� W 5 Q R X dS )z@Test the error message that should be called when bw is invalid.r rn Zinvalidr N) r ry rz r� r( r) r* r+ r� )r r �datar r r �test_wrong_bw_method� s z*TestGaussianKDECustom.test_wrong_bw_methodN)rT rU rV r r r r r r r r" r% r& r( r r r r r 4 s r c @ s4 e Zd Zdd� Zdd� Zdd� Zdd� Zd d � Zd S ) �TestGaussianKDEEvaluatec C sR t �ddd�}t�|�}t �ddd�}dddddg}|�|�}t j�||d� d S ) zr Test the evaluate method when the dim's of dataset and points have different dimensions. r1 r! r0 � �X�]��?�A�G$�?g�;�]��?rf N�r r r+ r� r r� r� )r rK r� rL r� r r r r �test_evaluate_diff_dim� s � z.TestGaussianKDEEvaluate.test_evaluate_diff_dimc C sZ t j�d� d}t j�|�}t�|�}dgdgdgg}t�t�� |� |� W 5 Q R X dS )z� Invert the dimensions; i.e., for a dataset of dimension 1 [3,2,4], the points should have a dimension of 3 [[3],[2],[4]]. r rn r r0 r1 N) r ry rz r� r+ r� r( r) r* r )r r r! r� rL r r r �test_evaluate_inv_dim� s z-TestGaussianKDEEvaluate.test_evaluate_inv_dimc C sH t �ddd�}t �dg�}t�|�}dg}|�|�}t j�||d� dS )z-Tests if evaluated against a one by one arrayr1 r! r0 r+ rf N)r r r7 r+ r� r r� r� �r rK rL r� r� r r r r �test_evaluate_dim_and_num� s z1TestGaussianKDEEvaluate.test_evaluate_dim_and_numc C sX t �ddd�}t �ddd�t �ddd�g}t�|�}t�t�� |�|� W 5 Q R X d S )Nr1 r! r0 )r r r+ r� r( r) r* r )r rK rL r� r r r � test_evaluate_point_dim_not_one� s z7TestGaussianKDEEvaluate.test_evaluate_point_dim_not_onec C sN t �ddd�}t �ddd�}t�|�}dddg}|�|�}t j�||d� d S )Nr1 r! r0 r r+ r, rf r- r0 r r r �"test_evaluate_equal_dim_and_num_lt� s z:TestGaussianKDEEvaluate.test_evaluate_equal_dim_and_num_ltN)rT rU rV r. r/ r1 r2 r3 r r r r r) � s r) c C s� t �dddddddg�} d}t �t j�| �| �d || j }tj| | jd| tjtjdd d dd� \}}t � |d g|dd� |dd � d d d � �}t ||d d � d S ) Nr r r0 r1 � �?rL �r rV r� r� r r� r� rK rM r5 r� r� ) r r7 rq �fft�sizer+ r� r� r� �appendr ��uZdtZSu�Pr� ZSu_1sider r r �test_psd_onesided_norm� s $ � 0r< c C s� t �dddddddg�} d}t �t j�| �| �d || j }tj| | jd d| tjtjddddd� \}}t � |d g|dd � |d d� ddd � �}t t � |�t � |�� dS ) z&Test the case len(x) < NFFT for psd().r r r0 r1 r4 NrL r5 rM r5 ) r r7 rq r6 r7 r+ r� r� r� r8 r r� r9 r r r �test_psd_oversampling� s $ � 0r= )$r] r� Z numpy.testingr r r r Znumpy.ma.testutilsZmaZ testutilsZmatestZnumpyr rq r( Zmatplotlib.mlabr+ Z matplotlib.cbook.deprecationr �objectr r� r_ re rW rX ru rv r� rR r� r� r r) r< r= r r r r �<module> s� { ����� { ^ ���� � F-Y6