OwlCyberSecurity - MANAGER
Edit File: streamplot.cpython-38.pyc
U ��]�V � @ s� d Z ddlZddlZddlmZ ddlmZ ddl m Z ddl m Z ddlmZ dgZd d d�ZG d d � d e�ZG d d � d e�ZG dd� de�ZG dd� de�ZG dd� de�ZG dd� de�Zdd� Zdd� Z dd� Z d d � Z d d � Z dS )!z, Streamline plotting for 2D vector fields. � N� streamplot� �-|>皙�����?� @�bothc 5 C sh t ||�}t|�}t||�}|dkr,tjj}| dkr:| j} |dkrL| j�� }|dkr^t j d }i }t | d| d�}|dkr�d| }t |��|dkr�|d }t |tj�}|r�|j|jkr�t d ��g }tj�|�}n||d < ||d < t |tj��r|j|jk�rt d ��g |d < n||d < ||d < ||d < ||d < |j|jk�sJ|j|jk�rRt d��tj�|�}tj�|�}t|||| ||�}g }|dk�r�t|j�D ]J\} } || | f dk�r�|�| | �\} } || | �} | dk �r�|�| � �q�n�tj|td��� }!|!D ]d\}"}#|j|" k�r"|j|j k�rJn n$|j |# k�rH|j |j k�s�n t d� |"|#����q�|!dd�df |j8 < |!dd�df |j 8 < |!D ]8\}"}#|� |"|#�\} } || | �} | dk �r�|�| � �q�|�r| dk�r�t �!|�"� |�#� �} |dk�rt$�%t j d �}n t$�%|�}g }$g }%|D �]�} t�&| d �}&t�&| d �}'|j't�&| �� \}(})|(|j7 }(|)|j 7 })t�(|(|)g��)ddd�}*|$�*t�+|*dd� |*dd� g�� t�,t�-t�.|(�t�.|)���}+t�/|+|+d d �},|(|, |)|, f}-t�0|(|,|,d � �t�0|)|,|,d � �f}.t |tj��rVt1||&|'�dd� }/|d �*|/� |/|, |d < |�r�t1||&|'�dd� }0|�|0� || |0|, ��|d < t2j3|-|.fd| i|��}1| �4|1� |%�|1� �q&t5j6|$fd| i|��}2|j|j|j g|2j7j8dd�< |j |j |j g|2j7j9dd�< |�r<|2�:tj�+|�� |2�;|� |2�<| � | �=|2� | �>� t j?�@|%�}3tA|2|3�}4|4S )a� Draw streamlines of a vector flow. Parameters ---------- x, y : 1D arrays An evenly spaced grid. u, v : 2D arrays *x* and *y*-velocities. The number of rows and columns must match the length of *y* and *x*, respectively. density : float or (float, float) Controls the closeness of streamlines. When ``density = 1``, the domain is divided into a 30x30 grid. *density* linearly scales this grid. Each cell in the grid can have, at most, one traversing streamline. For different densities in each direction, use a tuple (density_x, density_y). linewidth : float or 2D array The width of the stream lines. With a 2D array the line width can be varied across the grid. The array must have the same shape as *u* and *v*. color : matplotlib color code, or 2D array The streamline color. If given an array, its values are converted to colors using *cmap* and *norm*. The array must have the same shape as *u* and *v*. cmap : `~matplotlib.colors.Colormap` Colormap used to plot streamlines and arrows. This is only used if *color* is an array. norm : `~matplotlib.colors.Normalize` Normalize object used to scale luminance data to 0, 1. If ``None``, stretch (min, max) to (0, 1). This is only used if *color* is an array. arrowsize : float Scaling factor for the arrow size. arrowstyle : str Arrow style specification. See `~matplotlib.patches.FancyArrowPatch`. minlength : float Minimum length of streamline in axes coordinates. start_points : Nx2 array Coordinates of starting points for the streamlines in data coordinates (the same coordinates as the *x* and *y* arrays). zorder : int The zorder of the stream lines and arrows. Artists with lower zorder values are drawn first. maxlength : float Maximum length of streamline in axes coordinates. integration_direction : {'forward', 'backward', 'both'} Integrate the streamline in forward, backward or both directions. default is ``'both'``. Returns ------- stream_container : StreamplotSet Container object with attributes - ``lines``: `.LineCollection` of streamlines - ``arrows``: `.PatchCollection` containing `.FancyArrowPatch` objects representing the arrows half-way along stream lines. This container will probably change in the future to allow changes to the colormap, alpha, etc. for both lines and arrows, but these changes should be backward compatible. Nzlines.linewidth� )� arrowstyleZmutation_scale)r �forward�backwardzTIntegration direction '%s' not recognised. Expected 'both', 'forward' or 'backward'.r g @z7If 'color' is given, must have the shape of 'Grid(x,y)'�colorz;If 'linewidth' is given, must have the shape of 'Grid(x,y)'� linewidth�zorderz('u' and 'v' must be of shape 'Grid(x,y)'r )Zdtypez2Starting point ({}, {}) outside of data boundariesr z image.cmap���� � transform)B�Grid� StreamMask� DomainMap�mlinesZLine2Dr Z transDataZ _get_linesZget_next_color� matplotlibZrcParams�dict� ValueError� isinstance�np�ndarray�shape�maZmasked_invalid�get_integrator�_gen_starting_points� mask2grid�appendZ asanyarray�float�copy�x_origin�width�y_origin�height�format� data2grid�mcolorsZ Normalize�min�max�cmZget_cmapZarray� grid2dataZ transposeZreshape�extendZhstackZcumsum�hypot�diffZ searchsortedZmean� interpgrid�patchesZFancyArrowPatchZ add_patch� mcollectionsZLineCollectionZ sticky_edges�x�yZ set_arrayZset_cmapZset_normZadd_collectionZautoscale_view� collectionsZPatchCollection� StreamplotSet)5Zaxesr5 r6 �u�v�densityr r ZcmapZnormZ arrowsizer � minlengthr r Z start_points� maxlength�integration_direction�grid�mask�dmapZline_kwZarrow_kwZerrstrZuse_multicolor_linesZ line_colors� integrateZ trajectories�xm�ym�xg�yg�tZsp2ZxsZysZ streamlines�arrowsZtgxZtgyZtxZtyZpoints�s�nZ arrow_tailZ arrow_headZ line_widthsZ color_values�pZlcZacZstream_container� rL �7/usr/lib/python3/dist-packages/matplotlib/streamplot.pyr s C � �� � & � � � $ , ��� ��� c @ s e Zd Zdd� ZdS )r8 c K s || _ || _d S �N)�linesrH )�selfrO rH �kwargsrL rL rM �__init__� s zStreamplotSet.__init__N)�__name__� __module__� __qualname__rR rL rL rL rM r8 � s r8 c @ sX e Zd ZdZdd� Zdd� Zdd� Zdd � Zd d � Zd d � Z dd� Z dd� Z dd� Z dS )r a Map representing different coordinate systems. Coordinate definitions: * axes-coordinates goes from 0 to 1 in the domain. * data-coordinates are specified by the input x-y coordinates. * grid-coordinates goes from 0 to N and 0 to M for an N x M grid, where N and M match the shape of the input data. * mask-coordinates goes from 0 to N and 0 to M for an N x M mask, where N and M are user-specified to control the density of streamlines. This class also has methods for adding trajectories to the StreamMask. Before adding a trajectory, run `start_trajectory` to keep track of regions crossed by a given trajectory. Later, if you decide the trajectory is bad (e.g., if the trajectory is very short) just call `undo_trajectory`. c C sd || _ || _|jd |j | _|jd |j | _d| j | _d| j | _d|j | _ d|j | _ d S )Nr � �?) r? r@ �nx� x_grid2mask�ny� y_grid2mask� x_mask2grid� y_mask2grid�dx� x_data2grid�dy� y_data2grid)rP r? r@ rL rL rM rR s zDomainMap.__init__c C s$ t || j d �t || j d �fS )z;Return nearest space in mask-coords from given grid-coords.� �?)�intrX rZ �rP �xi�yirL rL rM � grid2mask s �zDomainMap.grid2maskc C s || j || j fS rN )r[ r\ �rP rC rD rL rL rM r s zDomainMap.mask2gridc C s || j || j fS rN �r^ r` )rP ZxdZydrL rL rM r) s zDomainMap.data2gridc C s || j || j fS rN rh )rP rE rF rL rL rM r. s zDomainMap.grid2datac C s" | � ||�\}}| j�||� d S rN )rf r@ �_start_trajectory�rP rE rF rC rD rL rL rM �start_trajectory# s zDomainMap.start_trajectoryc C s | � ||�\}}||f| j_d S rN )rf r@ � _current_xyrj rL rL rM �reset_start_point' s zDomainMap.reset_start_pointc C s4 | j �||�st�| �||�\}}| j�||� d S rN )r? � within_grid�InvalidIndexErrorrf r@ �_update_trajectoryrj rL rL rM �update_trajectory+ s zDomainMap.update_trajectoryc C s | j �� d S rN )r@ �_undo_trajectory�rP rL rL rM �undo_trajectory1 s zDomainMap.undo_trajectoryN) rS rT rU �__doc__rR rf r r) r. rk rm rq rt rL rL rL rM r � s r c @ s, e Zd ZdZdd� Zedd� �Zdd� ZdS ) r z Grid of data.c C sV |j dkr n<|j dkr@|dd d �f }t�||�s:td��|}ntd��|j dkrTn>|j dkr�|d d �df }t�||j�s�td��|}ntd��t|�| _t|�| _|d |d | _|d |d | _ |d | _ |d | _ |d |d | _ |d |d | _ t�t�|�| j | jd ��s*td ��t�t�|�| j | jd ��sRtd ��d S ) Nr r r z The rows of 'x' must be equalz$'x' can have at maximum 2 dimensionsz The columns of 'y' must be equalz$'y' can have at maximum 2 dimensionsr z!'x' values must be equally spacedz!'y' values must be equally spaced)�ndimr Zallcloser �T�lenrW rY r] r_ r$ r& r% r' r1 )rP r5 r6 Zx_rowZy_colrL rL rM rR 7 s8 z Grid.__init__c C s | j | jfS rN )rY rW rs rL rL rM r ^ s z Grid.shapec C s, |dko*|| j d ko*|dko*|| jd kS )z.Return True if point is a valid index of grid.r r )rW rY rc rL rL rM rn b s zGrid.within_gridN)rS rT rU ru rR �propertyr rn rL rL rL rM r 5 s ' r c @ s8 e Zd ZdZdd� Zdd� Zdd� Zdd � Zd d � Zd S ) r aI Mask to keep track of discrete regions crossed by streamlines. The resolution of this grid determines the approximate spacing between trajectories. Streamlines are only allowed to pass through zeroed cells: When a streamline enters a cell, that cell is set to 1, and no new streamlines are allowed to enter. c C s� z"dt �|d� �t�\| _| _W n tk r> td��Y nX | jdk sT| jdk r\td��t �| j| jf�| _| jj | _ d | _ d S )N� r z,'density' must be a scalar or be of length 2r z'density' must be positive) r Z broadcast_to�astyperb rW rY r Zzeros�_maskr rl )rP r; rL rL rM rR r s " zStreamMask.__init__c G s | j j|� S rN )r| � __getitem__)rP �argsrL rL rM r} ~ s zStreamMask.__getitem__c C s g | _ | �||� dS )z%Start recording streamline trajectoryN)�_trajrp rg rL rL rM ri � s z StreamMask._start_trajectoryc C s | j D ]}| j�|d� qdS )z#Remove current trajectory from maskr N)r r| � __setitem__)rP rG rL rL rM rr � s zStreamMask._undo_trajectoryc C sP | j ||fkrL| ||f dkrH| j�||f� d| j||f< ||f| _ nt�dS )z�Update current trajectory position in mask. If the new position has already been filled, raise `InvalidIndexError`. r r N)rl r r! r| ro rg rL rL rM rp � s z StreamMask._update_trajectoryN) rS rT rU ru rR r} ri rr rp rL rL rL rM r i s r c @ s e Zd ZdS )ro N�rS rT rU rL rL rL rM ro � s ro c @ s e Zd ZdS )�TerminateTrajectoryNr� rL rL rL rM r� � s r� c sv �� ���\����jj }��jj }tj�|d |d �����fdd���fdd�� � �����fdd�}|S )Nr c sJ t � | |�}|dkrt� �d| }t �| |�}t �| |�}|| || fS )Nr rV )r2 r� )rd re Zds_dtZdt_dsZuiZvi)�speedr9 r: rL rM � forward_time� s z$get_integrator.<locals>.forward_timec s � | |�\}}| | fS rN rL )rd re ZdxiZdyi)r� rL rM � backward_time� s z%get_integrator.<locals>.backward_timec s dg g }}}z�� | |� W n tk r6 Y dS X �dkr�t| |�� ��\}}}||7 }||ddd� 7 }||ddd� 7 }�dkr��| |� t| |����\}}}t|�dkr�|dd� }|dd� }||7 }||7 }||7 }|�kr�||fS ��� dS dS )a� Return x, y grid-coordinates of trajectory based on starting point. Integrate both forward and backward in time from starting point in grid coordinates. Integration is terminated when a trajectory reaches a domain boundary or when it crosses into an already occupied cell in the StreamMask. The resulting trajectory is None if it is shorter than `minlength`. g N)r r r )r r r r )rk ro �_integrate_rk12rm rx rt )�x0�y0�stotalZx_trajZy_trajrI �xt�yt)r� rA r� r> r= r< rL rM rB � s. z!get_integrator.<locals>.integrate)r) r? rW rY r r Zsqrt) r9 r: rA r< r= r> Zu_axZv_axrB rL ) r� rA r� r> r= r< r� r9 r: rM r � s 'r c C s� d}t d|jj d|jj d�}|}d}| } |} g } g } |j�| | ��r�| �| � | �| � z0|| | �\} }|| || | || �\}}W nN tk r� t| | ||�\}} } ||7 }Y �q�Y n t k r� Y �q�Y nX || }|| }|d | | }|d || }|jj \}}t � || | || | �}||k �r�| |7 } | |7 } z|� | | � W n tk �rz Y �q�Y nX || |k�r��q�||7 }|dk�r�|}q8t |d| || d �}q8|| | fS )aA 2nd-order Runge-Kutta algorithm with adaptive step size. This method is also referred to as the improved Euler's method, or Heun's method. This method is favored over higher-order methods because: 1. To get decent looking trajectories and to sample every mask cell on the trajectory we need a small timestep, so a lower order solver doesn't hurt us unless the data is *very* high resolution. In fact, for cases where the user inputs data smaller or of similar grid size to the mask grid, the higher order corrections are negligible because of the very fast linear interpolation used in `interpgrid`. 2. For high resolution input data (i.e. beyond the mask resolution), we must reduce the timestep. Therefore, an adaptive timestep is more suited to the problem as this would be very hard to judge automatically otherwise. This integrator is about 1.5 - 2x as fast as both the RK4 and RK45 solvers in most setups on my machine. I would recommend removing the other two to keep things simple. g�~j�t�h?rV r r ra g333333�?)r+ r@ rW rY r? rn r! � IndexError� _euler_stepr� r r r0 rq ro )r� r� rA �fr= ZmaxerrorZmaxds�dsr� rd re �xf_traj�yf_trajZk1xZk1yZk2xZk2yZdx1Zdy1Zdx2Zdy2rW rY �errorrL rL rM r� � sT � r� c C s� |j j\}}| d }|d }|||�\}} |dkr:tj} n$|dk rN|| } n|d | | } | dkrntj} n$| dk r�|| } n|d | | } t| | �} | �||| � |�|| | � | | |fS )zBSimple Euler integration step that extends streamline to boundary.r r r )r? r r �infr+ r! ) r� r� rA r� rY rW rd re ZcxZcyZdsxZdsyr� rL rL rM r� > s$ r� c C s@ t �| �\}}t|t j�r\|�t�}|�t�}t �|d d|d �}t �|d d|d �}nDt|�}t|�}||d kr~|}n|d }||d kr�|}n|d }| ||f } | ||f } | ||f } | ||f } || } || }| d| | | }| d| | | }|d| || }t|t j��s<t j�|��r<t �|S )z0Fast 2D, linear interpolation on an integer gridr r ) r r r r r{ rb Zclipr Z is_maskedr� )�ard re ZNyZNxr5 r6 ZxnZynZa00Za01Za10Za11r� r� Za0Za1ZairL rL rM r2 Y s6 r2 c c s� | \}}d}d}|d }|d }d\}}d} t || �D ]�} ||fV | dkrl|d7 }||kr�|d8 }d} q8| dkr�|d7 }||kr�|d8 }d} q8| dkr�|d8 }||kr�|d7 }d} q8| dkr8|d8 }||kr8|d7 }d} q8dS ) a Yield starting points for streamlines. Trying points on the boundary first gives higher quality streamlines. This algorithm starts with a point on the mask corner and spirals inward. This algorithm is inefficient, but fast compared to rest of streamplot. r r )r r �rightZup�leftZdownN)�range) r rY rW ZxfirstZyfirstZxlastZylastr5 r6 � direction�irL rL rM r � s: r ) r NNNNr r r NNNr r ) ru Znumpyr r Z matplotlib.cmr- Zmatplotlib.colorsZcolorsr* Zmatplotlib.collectionsr7 r4 Zmatplotlib.linesrO r Zmatplotlib.patchesr3 �__all__r �objectr8 r r r � Exceptionro r� r r� r� r2 r rL rL rL rM �<module> s@ � Z ?40AY(