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)r ra r r r �test_finite_range� s z TestHistogram.test_finite_rangec C s< t jdddd�}ttd�� t j|ddgd� W d Q R X d S ) Ng g �?r )r_ zmax must be larger thang�������?g{�G�z�?)r> )r r r r' r )r ra r r r �test_invalid_range� s z TestHistogram.test_invalid_rangec C s� t �dddddddg�}t j|dd d �\}}|d k}|d d � | }|d d � | }x2t|||�D ]"\}}} t||k� t|| k � qbW d S )NiQ i� i� i& i� i i� ih )r# i� )r& r> r rC r" )r r( r �zipr ) r �arrr) r* �maskZ left_edgesZ right_edgesrN �left�rightr r r �test_bin_edge_cases s z!TestHistogram.test_bin_edge_casesc C sB t �dddddddddg �}t j|ddd �\}}t|d d � d S ) Ng g �?g @g @g @g @� )g �r/ )r& r> rC r" )r r( r r )r rg r) r* r r r � test_last_bin_inclusive_range s z+TestHistogram.test_last_bin_inclusive_rangec C sN t jdddd�}t �ddgddgg�}ttd�� t j||d � W d Q R X d S ) Ng g �?r )r_ r g �?g333333�?z must be 1d)r& )r r r( r r' r )r ra r& r r r �test_bin_array_dims s z!TestHistogram.test_bin_array_dimsc C sJ t �dg�}t jdddgdd�}tt�� t j||d�\}}W d Q R X d S )Nr# r" r$ Zuint64)rH )r& )r r( r r' r )r rg r& r) r* r r r � test_unsigned_monotonicity_check s z.TestHistogram.test_unsigned_monotonicity_checkc C s� t ttdd� td�D �tj g � t ttdd� td�D �tjg � t�dd� td�D �dg � t�dd� td�D �dg � d S ) Nc S s g | ]}t �d ��qS )g�������?)r r( )�.0�ir r r � <listcomp># s z9TestHistogram.test_object_array_of_0d.<locals>.<listcomp>r c S s g | ]}t �d ��qS )g�������?)r r( )rp rq r r r rr % s c S s g | ]}t �d ��qS )g �?)r r( )rp rq r r r rr ( s g �?c S s g | ]}t �d ��qS )g �?)r r( )rp rq r r r rr ) s g �?)r r' r r> r r; )r r r r �test_object_array_of_0d s z%TestHistogram.test_object_array_of_0dc C s� t �ddt jg�}t �t jt jg�}t� }|�t� |�� ttt|dd� ttt|dd� t|ddd�\}}t |� � d� t|ddd�\}}t |� � d� t|ddgd�\}}t |� � d� t|ddgd�\}}t |� � d� W d Q R X d S )Nr r" �auto)r& )r r" )r& r> r# ) r r( rc r �filterrQ r r' r r r )r Zone_nanZall_nanr5 r+ r r r r �test_some_nan_values+ s z"TestHistogram.test_some_nan_valuesc C s� t �dd�}t �ddddddddd g �}t �ddd d g�}|| }|| }t �d �}t||d �\}}t|�|�|�|�d �\} } t||d �\} } t|| � t| | � t|| �t�| � t| �t�| � t|j|j� t| j|� d S ) Nz 2000-01-01�Dr r" r# r$ r/ r � � ztimedelta64[D])r& )r Z datetime64r( rH r �astyper rK ) r �begin�offsetsr& �datesZ date_bins�tdZd_countZd_edgeZt_countZt_edgeZi_countZi_edger r r � test_datetimeD s zTestHistogram.test_datetimec C s| dt �|�j d }t jd| d d| d g|d�}t|dd�\}}t|d| d dd| d g� t|ddg� d S )NrB r" r# r% )rH )r& r )r rH �itemsizer( r r )r rH �exponentrg r) r, r r r �do_signed_overflow_bounds] s $"z'TestHistogram.do_signed_overflow_boundsc C s@ | � tj� | � tj� | � tj� | � tj� | � tj� d S )N)r� r �byte�shortZintc�int_Zlonglong)r r r r �test_signed_overflow_boundsd s z)TestHistogram.test_signed_overflow_boundsc C st t �|�j}t �dg|�}t �d| dg|�}|�|�d dkrDd S t j|d|d�\}}t|dg� t|j|� d S )Ng �?g @r r" )r& r> )r �finfo�epsr( rz r r rH )r � float_small� float_larger� rg r> �count�x_locr r r �do_precision_lower_boundk s z&TestHistogram.do_precision_lower_boundc C st t �|�j}t �dg|�}t �dd| g|�}|�|�d dkrDd S t j|d|d�\}}t|dg� t|j|� d S )Ng �?g rC r" )r& r> )r r� r� r( rz r r rH )r r� r� r� rg r> r� r� r r r �do_precision_upper_bound| s z&TestHistogram.do_precision_upper_boundc C s | � ||� | �||� d S )N)r� r� )r r� r� r r r � do_precision� s zTestHistogram.do_precisionc C sd | � tjtj� | � tjtj� | � tjtj� | � tjtj� | � tjtj� | � tjtj� d S )N)r� r ZhalfZsingle�doubleZ longdouble)r r r r �test_precision� s z TestHistogram.test_precisionc C s� t ddddgddg�\}}tddddgddg�}t||� t�dddddddd d g �}t |d d d �\}}t|d d d �}t||� t |ddd �\}}t|ddd �}t||� d S )Nr" r# r$ r% g g �?g @g @g @g @rl )g �r/ )r& r> rt )r r" )r r r r r( )r r) r, r* rg r r r �test_histogram_bin_edges� s z&TestHistogram.test_histogram_bin_edgesN)#�__name__� __module__� __qualname__r r r! r- r8 r= rE rG rM rP rR rY r\ r] r^ rb rd re rk rm rn ro rs rv r r� r� r� r� r� r� r� r r r r r s@ r c @ s� e Zd ZdZdd� Zdd� Zdd� Zdd � Zd d � Zd d � Z dd� Z dd� Z dd� Z e j�ddddddddg�d d � �Zd d � Zd S )!�TestHistogramOptimBinNumsz] Provide test coverage when using provided estimators for optimal number of bins c C s\ ddddddddg}xB|D ]:}t g |d �\}}t|t�d g�� t|t�d d g�� qW d S ) N�fd�scott�rice�sturges�doane�sqrtrt �stone)r& r r" )r r r r( )r �estimator_list� estimatorr r r r r r^ � s z$TestHistogramOptimBinNums.test_emptyc C s� ddddddddd�dddddd dd d�d d d d d dd dd�d�}x�|� � D ]�\}}t�dd|d d �}t�dd|d d �}t�||f�}x>|� � D ]2\}}t�||�\} } tt| �|d�||�d� q�W qLW dS )z� Straightforward testing with a mixture of linspace data (for consistency). All test values have been precomputed and the values shouldn't change r% rB ry r# )r� r� r� r� r� r� rt r� � r � � r0 � �# � �G rx )�2 i� i� i����rC r/ r" r$ z*For the {0} estimator with datasize of {1})�err_msgN)�itemsr r rS r r r3 �format) r � basic_test�testlen�expectedResults�x1�x2rN r� �numbinsr r r r r r! � s z%TestHistogramOptimBinNums.test_simplec C s� dddddddd�dddddddd�dddddddd�d�}x^|� � D ]R\}}t�|�}x>|� � D ]2\}}t�||�\}}tt|�|d�||�d� qbW qFW dS ) z� Smaller datasets have the potential to cause issues with the data adaptive methods, especially the FD method. All bin numbers have been precalculated. r" )r� r� r� r� r� r� r� r# r$ )r" r# r$ z*For the {0} estimator with datasize of {1})r� N)r� r r4 r r r3 r� ) r Z small_datr� r� Ztestdatr� Zexpbinsr r r r r � test_small� s z$TestHistogramOptimBinNums.test_smallc C s2 ddddg}x |D ]}t ttdddg|� qW dS ) zS Check a Value Error is thrown when an unknown string is passed in ZmadZfreemanZ histogramsZIQRr" r# r$ N)r r' r )r Z check_listr� r r r �test_incorrect_methods� s z0TestHistogramOptimBinNums.test_incorrect_methodsc C sb t �d�}ddddddddd�}x<|�� D ]0\}}t �||�\}}tt|�|d�|�d� q*W dS )z� Check that methods handle no variance in data Primarily for Scott and FD as the SD and IQR are both 0 in this case r r" )r� r� r� r� r� r� rt r� z {0} estimator, No Variance test)r� N)r rJ r� r r r3 r� )r Z novar_datasetZnovar_resultdictr� r� r r r r r �test_novariance� s z)TestHistogramOptimBinNums.test_novariancec C s� t �d�}d|dd�< d|dd�< t|d�}t|t �ddd�� t|d �}t|t �ddg�� t|d �}t|t �ddd�� dS ) zu Check when IQR is 0, but variance exists, we return the sturges value and not the fd value. i� r Nr$ r ���rt r� r� r� )r rJ r r r r( )r Z lim_var_dataZ edges_autoZedges_fdZ edges_sturgesr r r �test_limited_variance� s z/TestHistogramOptimBinNums.test_limited_variancec C sl t �ddd�}t �t �ddd�|f�}dddd d �}x2|�� D ]&\}}t �||�\}}tt|�|� q>W d S ) a� Check the FD, Scott and Doane with outliers. The FD estimates a smaller binwidth since it's less affected by outliers. Since the range is so (artificially) large, this means more bins, most of which will be empty, but the data of interest usually is unaffected. The Scott estimator is more affected and returns fewer bins, despite most of the variance being in one area of the data. The Doane estimator lies somewhere between the other two. i����r r� i����i����r/ � rF r: )r� r� r� r� N)r r �hstackr� r r r3 )r ZxcenterZoutlier_datasetZoutlier_resultdictr� r� r r r r r � test_outlier s z&TestHistogramOptimBinNums.test_outlierc sN dd� � � fdd�t d�D �}ttj|dd�d �}t|d d d d gd d� dS )zQVerify that Scott's rule and Stone's rule converges for normally distributed datac S sR t j�| �}|jdd|d�}tt �|d�d �tt �|d�d � }}||| S )Nr r# )�loc�scale�sizer� r� )r r Z RandomState�normalr3 r )�seedr� �rngrN r r r r r � nbins_ratio% s *zBTestHistogramOptimBinNums.test_scott_vs_stone.<locals>.nbins_ratioc s6 g | ].� �� fd d�t jdddd��� �t�D ��qS )c s g | ]}� �|��qS r r )rp r� )r� r� r r rr + s zLTestHistogramOptimBinNums.test_scott_vs_stone.<locals>.<listcomp>.<listcomp>r r r% )�start�stopr_ )r Z geomspace�roundrz rK )rp )r� )r� r rr + s zATestHistogramOptimBinNums.test_scott_vs_stone.<locals>.<listcomp>r r )r g �?g333333�?g ףp= �?g{�G�z�?g� ��Q��?r# )r@ N)r> �absr Zmeanr )r �ll�avgr )r� r �test_scott_vs_stone" s z-TestHistogramOptimBinNums.test_scott_vs_stonec C s� ddddddd�ddddddd�d d d d d dd�d �}x�|� � D ]�\}}t�d d|d d �}t�dd|d d �}t�dd|�}t�|||f�}xR|� � D ]F\}} tj||dd�\} } d�|�} | d�|�7 } tt| �| | d� q�W q@W dS ) z� Straightforward testing with a mixture of linspace data (for consistency). Adding in a 3rd mixture that will then be completely ignored. 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)r& r" N)r r( r r rH )r rN rO r� r� r) r* r r r �test_edge_dtype� s z TestHistogramdd.test_edge_dtypec C s` d}t �dgt j�}t �ddgt j�}|| }|| }t||f||fd�\}}t|d d� d S )Nl r rC r" )r& )r r )r r( Zint64r r )r �bigrN r� rO r� r) r* r r r �test_large_integers s z#TestHistogramdd.test_large_integersc C s� t �dddg�}t �dddg�}t �ddgddgg�}t �dgdgd dgd dgd �}t �dgdgd dgd dgd �}t||f||fd �\}}t||� t||f||fd d �\}}t|d � d S ) Nr r# rB r: r$ r0 r" ry )r& T)r& r9 g �?)r r( r r )r r� r� Zrelative_areasrN rO r) r* r r r �test_density_non_uniform_2d s ** z+TestHistogramdd.test_density_non_uniform_2dc C sb t �d�}t �dddddg�}t||dd�\}}t|f|fdd�\}}t||� t||d � d S )Nr r r" r$ r: T)r9 )r r4 r( r r r )r r r& r) r* �hist_dd�edges_ddr r r �test_density_non_uniform_1d. s z+TestHistogramdd.test_density_non_uniform_1dc C sb t �d�}t �dddddg�}t||dd�\}}t|f|fdd�\}}t||� t||d � d S ) Nr r r" r$ r: T)r9 )r. )r r4 r( r r r )r r r& r) r* r� r� r r r �test_density_via_normed7 s z'TestHistogramdd.test_density_via_normedc C sP t �d�}t �dddddg�}ttd�� t|f|fddd�\}}W d Q R X d S ) Nr r r" r$ r: zCannot specify bothT)r9 r. )r r4 r( r r` r )r r r& r� r� r r r � test_density_normed_redundancy@ s z.TestHistogramdd.test_density_normed_redundancyN)r� r� r� r! r� r� rY r� r^ r� r� r� rd r� r� r� r� r� r� r� r r r r r� e s" % r� )�numpyr Znumpy.lib.histogramsr r r Z numpy.testingr r r r r r r r r r r� r r� r� r r r r �<module> s 0 =
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