o
    ]ZŽhÄ(  ã                   @   sl   d dl Z e  d¡Ze  d¡Zd dlZd dlmZmZm	Z	 d dl
mZ G dd„ dƒZe j dd	¡d
d„ ƒZdS )é    NÚnumpyZscipy)Úbarbell_graphÚcycle_graphÚ
path_graph)Úgraphs_equalc                   @   s¬   e Zd Zdd„ Zdd„ Zdd„ Zdd„ Zd	d
„ Zdd„ Zdd„ Z	dd„ Z
dd„ Zdd„ Zdd„ Zdd„ Zdd„ Zdd„ Zdd„ Zdd „ Zd!d"„ Zd#d$„ Zd%d&„ Zd'd(„ Zd)S )*ÚTestConvertScipyc                 C   s@   t ddƒ| _tdtjd| _|  t ¡ ¡| _|  t ¡ ¡| _	d S )Né
   é   ©Úcreate_using)
r   ÚG1r   ÚnxÚDiGraphÚG2Úcreate_weightedÚGraphÚG3ÚG4©Úself© r   úP/var/www/auris/lib/python3.10/site-packages/networkx/tests/test_convert_scipy.pyÚsetup_method   s   zTestConvertScipy.setup_methodc                 C   s$   G dd„ dƒ}t  tjtj|¡ d S )Nc                   @   s   e Zd ZdZdS )z+TestConvertScipy.test_exceptions.<locals>.GN)Ú__name__Ú
__module__Ú__qualname__Úformatr   r   r   r   ÚG   s    r   )ÚpytestÚraisesr   ÚNetworkXErrorÚto_networkx_graph)r   r   r   r   r   Útest_exceptions   s   z TestConvertScipy.test_exceptionsc                 C   sX   t dƒ}t| ¡ ƒ}dd„ |D ƒ}dd„ |D ƒ}dd„ |D ƒ}t|||ƒ}| |¡ |S )Né   c                 S   s   g | ]\}}|‘qS r   r   ©Ú.0ÚuÚvr   r   r   Ú
<listcomp>   ó    z4TestConvertScipy.create_weighted.<locals>.<listcomp>c                 S   s   g | ]\}}|‘qS r   r   r$   r   r   r   r(      r)   c                 S   s   g | ]}|d  ‘qS )r   r   )r%   Úsr   r   r   r(      r)   )r   ÚlistÚedgesÚzipÚadd_weighted_edges_from)r   r   ÚgÚeÚsourceÚdestÚweightÚexr   r   r   r      s   
z TestConvertScipy.create_weightedc                 C   s4  t j||d}t  ||¡sJ ‚t j||d}t  ||¡sJ ‚t  d|¡ |¡}t  ||¡s/J ‚| ¡ }t  d|¡ |¡}t  ||¡sDJ ‚| ¡ }t  d|¡ |¡}t  ||¡sYJ ‚| ¡ }	t  d|¡ |	¡}t  ||¡snJ ‚| 	¡ }
t  d|¡ |
¡}t  ||¡sƒJ ‚| 
¡ }t  d|¡ |¡}t  ||¡s˜J ‚d S )Nr
   r   )r   Úfrom_scipy_sparse_arrayÚis_isomorphicr!   Zempty_graphÚ	__class__ZtocsrZtocooZtocscÚtodenseÚtoarray)r   r   ÚAr   ZGGZGWZGIZACSRZACOOZACSCZADZAAr   r   r   Úidentity_conversion#   s*   z$TestConvertScipy.identity_conversionc                 C   s.   t j g d¢g d¢g¡}t tjtj|¡ dS )z(Conversion from non-square sparse array.)é   é   r	   )r#   é   é   N)ÚspÚsparseZ	lil_arrayr   r   r   r    r5   ©r   r:   r   r   r   Ú
test_shapeA   s   zTestConvertScipy.test_shapec                 C   ó$   t  | j¡}|  | j|t  ¡ ¡ dS )z0Conversion from graph to sparse matrix to graph.N)r   Úto_scipy_sparse_arrayr   r;   r   rB   r   r   r   Útest_identity_graph_matrixF   ó   z+TestConvertScipy.test_identity_graph_matrixc                 C   rD   )z4Conversion from digraph to sparse matrix to digraph.N)r   rE   r   r;   r   rB   r   r   r   Útest_identity_digraph_matrixK   rG   z-TestConvertScipy.test_identity_digraph_matrixc                 C   rD   )zBConversion from weighted graph to sparse matrix to weighted graph.N)r   rE   r   r;   r   rB   r   r   r   Ú#test_identity_weighted_graph_matrixP   rG   z4TestConvertScipy.test_identity_weighted_graph_matrixc                 C   rD   )zFConversion from weighted digraph to sparse matrix to weighted digraph.N)r   rE   r   r;   r   rB   r   r   r   Ú%test_identity_weighted_digraph_matrixU   rG   z6TestConvertScipy.test_identity_weighted_digraph_matrixc                 C   sœ   t dƒ}t dƒ}t| ¡ ƒ}tj||d}t |¡}t ||¡s"J ‚tjtj	tj|g d |dg }tjtj	tj||d g d¢}tjtj	tj||d dS )z>Conversion from graph to sparse matrix to graph with nodelist.r#   r	   ©Únodelistr   )éÿÿÿÿr   r<   r=   N)
r   r+   Únodesr   rE   r   r6   r   r   r    )r   ÚP4ZP3rL   r:   ZGAZlong_nlZnon_nlr   r   r   Útest_nodelistZ   s   

zTestConvertScipy.test_nodelistc                 C   sš   t  ¡ }| dd„ tdƒD ƒ¡ tdƒ}t  |¡}tj | 	¡ t j|d d 	¡ ¡ tj d| 	¡  t  |¡ 	¡ ¡ tj d| 	¡  t j|dd 	¡ ¡ d S )	Nc                 s   ó$    | ]}||d  dddœfV  qdS ©r<   ç      à?ç333333Ó?)r3   ÚotherNr   ©r%   Únr   r   r   Ú	<genexpr>n   ó   €" z7TestConvertScipy.test_weight_keyword.<locals>.<genexpr>r	   r#   ©r3   rS   rT   rU   ©
r   r   Úadd_edges_fromÚranger   rE   ÚnpÚtestingÚassert_equalr8   ©r   ÚWP4rO   r:   r   r   r   Útest_weight_keywordl   s   
ÿÿÿz$TestConvertScipy.test_weight_keywordc                 C   sn  t  ¡ }| dd„ tdƒD ƒ¡ tdƒ}t j|dd}tj | 	¡ t j|d d 	¡ ¡ t j|dd}tj | 	¡ t j|d d 	¡ ¡ t j|d	d}tj | 	¡ t j|d d 	¡ ¡ t j|d
d}tj | 	¡ t j|d d 	¡ ¡ t j|dd}tj | 	¡ t j|d d 	¡ ¡ t j|dd}tj | 	¡ t j|d d 	¡ ¡ t j|dd}tj | 	¡ t j|d d 	¡ ¡ d S )Nc                 s   rQ   rR   r   rV   r   r   r   rX   }   rY   z7TestConvertScipy.test_format_keyword.<locals>.<genexpr>r	   r#   Úcsr©r   rZ   ÚcscZcooZbsrZlilZdiaÚdokr[   ra   r   r   r   Útest_format_keyword{   s>   ÿÿÿÿÿÿÿz$TestConvertScipy.test_format_keywordc                 C   sh   t  tj¡$ t ¡ }| dd„ tdƒD ƒ¡ tdƒ}tj|dd W d   ƒ d S 1 s-w   Y  d S )Nc                 s   rQ   rR   r   rV   r   r   r   rX   ¥   s   € 
ÿz=TestConvertScipy.test_format_keyword_raise.<locals>.<genexpr>r	   r#   Z	any_otherre   )	r   r   r   r    r   r\   r]   r   rE   )r   rb   rO   r   r   r   Útest_format_keyword_raise¢   s   
ÿ"úz*TestConvertScipy.test_format_keyword_raisec                 C   s@   t  tj¡ t t ¡ ¡ W d   ƒ d S 1 sw   Y  d S )N)r   r   r   r    rE   r   r   r   r   r   Útest_null_raise«   s   "ÿz TestConvertScipy.test_null_raisec                 C   s<   t  ¡ }| d¡ t  |¡}tj | ¡ t dgg¡¡ d S )Nr<   r   )	r   r   Úadd_noderE   r^   r_   r`   r9   Úarray©r   r   ÚMr   r   r   Ú
test_empty¯   s   

 zTestConvertScipy.test_emptyc              	   C   sl   t  ¡ }| dd¡ | dd¡ | dd¡ t j|g d¢d}tj | ¡ t g d¢g d¢g d¢g¡¡ d S )	Nr<   r=   r	   )r	   r=   r<   rK   ©r   r   r<   )r<   r   r   ©r   r<   r   )	r   r   Úadd_edgerE   r^   r_   r`   r9   rl   rm   r   r   r   Útest_orderingµ   s    ÿzTestConvertScipy.test_orderingc              	   C   s€   t  dg¡}t  |¡}tj | ¡ t dgg¡¡ | ddg¡ t j|g d¢d}tj | ¡ t g d¢g d¢g d¢g¡¡ d S )	N©r<   r<   r<   ©r=   r	   ©r	   r#   ©r=   r	   r#   rK   rq   )r<   r   r<   )	r   r   rE   r^   r_   r`   r9   rl   r\   rm   r   r   r   Útest_selfloop_graph¿   ó   
 ÿz$TestConvertScipy.test_selfloop_graphc              	   C   s€   t  dg¡}t  |¡}tj | ¡ t dgg¡¡ | ddg¡ t j|g d¢d}tj | ¡ t g d¢g d¢g d	¢g¡¡ d S )
Nrt   r<   ru   rv   rw   rK   rq   rp   )r   r   r   )	r   r   rE   r^   r_   r`   r9   rl   r\   rm   r   r   r   Útest_selfloop_digraphÊ   ry   z&TestConvertScipy.test_selfloop_digraphc                 C   s"  t j ddgddgg¡}t ¡ }g d¢}| dd„ |D ƒ¡ |jdddd tj|dtjd}t||ƒs6J ‚tj|d	tjd}t||ƒsFJ ‚g d
¢}t 	¡ }| dd„ |D ƒ¡ tj|dtj	d}t||ƒshJ ‚t 	¡ }|j
t|ƒdd d|d d d d< tj|d	tj	d}t||ƒsJ ‚dS )z±Tests that the :func:`networkx.from_scipy_sparse_array` function
        interprets integer weights as the number of parallel edges when
        creating a multigraph.

        r<   r=   )©r   r   ©r   r<   ©r<   r   c                 S   ó   g | ]	\}}||d f‘qS ©r<   r   r$   r   r   r   r(   à   ó    zPTestConvertScipy.test_from_scipy_sparse_array_parallel_edges.<locals>.<listcomp>rZ   T)Zparallel_edgesr   F)r{   r|   r}   rt   rt   c                 S   r~   r   r   r$   r   r   r   r(   ï   r€   r   r3   N)r@   rA   Ú	csr_arrayr   r   r.   rr   r5   r   ZMultiDiGraphr\   Úset)r   r:   Úexpectedr,   Úactualr   r   r   Ú+test_from_scipy_sparse_array_parallel_edgesÕ   s6   ÿÿÿÿz<TestConvertScipy.test_from_scipy_sparse_array_parallel_edgesc                 C   sR   t j ddgddgg¡}tj|tjd}t ¡ }|jdddd t||ƒs'J ‚dS )z¢Tests that a symmetric matrix has edges added only once to an
        undirected multigraph when using
        :func:`networkx.from_scipy_sparse_array`.

        r   r<   r
   rZ   N)r@   rA   r   r   r5   Z
MultiGraphrr   r   )r   r:   r   rƒ   r   r   r   Útest_symmetricý   s
   zTestConvertScipy.test_symmetricN)r   r   r   r   r"   r   r;   rC   rF   rH   rI   rJ   rP   rc   rh   ri   rj   ro   rs   rx   rz   r…   r†   r   r   r   r   r      s*    
'	
(r   Úsparse_format)rd   rf   rg   c                 C   s–   t  ¡ }| ddddifddddifddddifddddifddddifddddifg¡ tj g d¢g d¢g d¢g¡ | ¡}t|t  |¡ƒsIJ ‚d	S )
z7Test all formats supported by _generate_weighted_edges.r   r<   r3   r	   r=   )r   r	   r=   )r	   r   r<   )r=   r<   r   N)	r   r   r\   r@   rA   Z	coo_arrayZasformatr   r5   )r‡   rƒ   r:   r   r   r   Ú$test_from_scipy_sparse_array_formats
  s   úÿ$
rˆ   )r   Zimportorskipr^   r@   Znetworkxr   Znetworkx.generators.classicr   r   r   Znetworkx.utilsr   r   ÚmarkZparametrizerˆ   r   r   r   r   Ú<module>   s    

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