a İa!Q@sddlZddlZddlZddlmZddlmZddl m Z m Z m Z m Z mZmZmZeddgZd d Zdd d Zd dZGdddZddZeddZeddZeddZdS)N) broadcast)_easy_facetgrid) _add_colorbar_get_nice_quiver_magnitude _is_numeric_process_cmap_cbar_kwargsget_axislabel_from_attrspltg2@gR@c Cst|j}dd|}||vr2td|||vrFtd||durb||vrbtd||rt||j} |dur| rdnd}| s|dkrtd||dus|d ur|dkrd nd } |dkrd nd } qd } d } n |d ur|d vrtd d } d } |s|durF|d krFd } |rJd } |s2d}n|dkrJtdnd } |sZ|dur|dkr|rd } |szd}n|dkrtd|dur|dvrtd|rt||} ||}nd} d}| | | | |t||t|||dS)Nz must be one of ({:s})z, xyhue continuousdiscretez7Cannot create a colorbar for a non numeric coordinate: TFquiver streamplotz&Cannot set add_guide when hue is None.rzKhue_style must be 'continuous' or None for .plot.quiver or .plot.streamplotr)rrz:hue_style must be either None, 'discrete' or 'continuous'.) add_colorbar add_legend add_quiverkey hue_label hue_stylexlabelylabelr) setZ variableskeysformatjoin ValueErrorrvaluesr )dsr rrr add_guidefuncnameZdvarsZ error_msgZhue_is_numericrrrrr%7lib/python3.9/site-packages/xarray/plot/dataset_plot.py_infer_meta_datasz           r'c Csddg}||||g}|r4||||d|rP||||dtt|t|} | d| dddd} |r| d| d<|r| d} |durt| |}| jt|j| j j | j d| d<| S)Nr rrsize)r rrsizes)datar)) appenddictzipr _parse_sizecopynpZreshapelocr!ravelshape) r"r rr markersize size_norm size_mappingZbroadcast_keysZ to_broadcastZ broadcastedr*r(r%r%r&_infer_scatter_datais(     r7c Cstj}|durdS|j}t|sNt|}tddt|ddd}nt t|}}t \}}|dur~|j }n2t |tr|j j |}nt ||j j sd}t|d|_|s|t|||}t||||} |jrd| |j<tt|| } t| S)Nrz7``size_norm`` must be None, tuple, or Normalize object.Tr)r Z matplotlibr!flattenrr0uniqueZarangelensort_MARKERSIZE_RANGEcolors Normalize isinstancetupler ZclipZscaledZasarraymaskanyr,r-pdZSeries) r*normZmpllevelsZnumbersZ min_widthZ max_widtherrZsclZwidthsr)r%r%r&r.s2       r.c@s eZdZdZddZddZdS)_Dataset_PlotMethodszp Enables use of xarray.plot functions as attributes on a Dataset. 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Use an explicit plot method, e.g. ds.plot.scatter(...))r )rJargskwargsr%r%r&__call__sz_Dataset_PlotMethods.__call__N)__name__ __module__ __qualname____doc__rLrOr%r%r%r&rHsrHcsXd}jd|_tdfdd td fdd }tt|j|S) Na Parameters ---------- ds : Dataset x, y : str Variable names for the *x* and *y* grid positions. u, v : str, optional Variable names for the *u* and *v* velocities (in *x* and *y* direction, respectively; quiver/streamplot plots only). hue: str, optional Variable by which to color scatter points or arrows. hue_style: {'continuous', 'discrete'}, optional How to use the ``hue`` variable: - ``'continuous'`` -- continuous color scale (default for numeric ``hue`` variables) - ``'discrete'`` -- a color for each unique value, using the default color cycle (default for non-numeric ``hue`` variables) markersize: str, optional Variable by which to vary the size of scattered points (scatter plot only). size_norm: matplotlib.colors.Normalize or tuple, optional Used to normalize the ``markersize`` variable. If a tuple is passed, the values will be passed to :py:class:`matplotlib:matplotlib.colors.Normalize` as arguments. Default: no normalization (``vmin=None``, ``vmax=None``, ``clip=False``). scale: scalar, optional Quiver only. Number of data units per arrow length unit. Use this to control the length of the arrows: larger values lead to smaller arrows. add_guide: bool, optional, default: True Add a guide that depends on ``hue_style``: - ``'continuous'`` -- build a colorbar - ``'discrete'`` -- build a legend row : str, optional If passed, make row faceted plots on this dimension name. col : str, optional If passed, make column faceted plots on this dimension name. col_wrap : int, optional Use together with ``col`` to wrap faceted plots. ax : matplotlib axes object, optional If ``None``, use the current axes. Not applicable when using facets. subplot_kws : dict, optional Dictionary of keyword arguments for Matplotlib subplots (see :py:meth:`matplotlib:matplotlib.figure.Figure.add_subplot`). Only applies to FacetGrid plotting. aspect : scalar, optional Aspect ratio of plot, so that ``aspect * size`` gives the *width* in inches. Only used if a ``size`` is provided. size : scalar, optional If provided, create a new figure for the plot with the given size: *height* (in inches) of each plot. See also: ``aspect``. norm : matplotlib.colors.Normalize, optional If ``norm`` has ``vmin`` or ``vmax`` specified, the corresponding kwarg must be ``None``. vmin, vmax : float, optional Values to anchor the colormap, otherwise they are inferred from the data and other keyword arguments. When a diverging dataset is inferred, setting one of these values will fix the other by symmetry around ``center``. Setting both values prevents use of a diverging colormap. If discrete levels are provided as an explicit list, both of these values are ignored. cmap : matplotlib colormap name or colormap, optional The mapping from data values to color space. Either a Matplotlib colormap name or object. If not provided, this will be either ``'viridis'`` (if the function infers a sequential dataset) or ``'RdBu_r'`` (if the function infers a diverging dataset). See :doc:`Choosing Colormaps in Matplotlib ` for more information. If *seaborn* is installed, ``cmap`` may also be a `seaborn color palette `_. Note: if ``cmap`` is a seaborn color palette, ``levels`` must also be specified. colors : str or array-like of color-like, optional A single color or a list of colors. The ``levels`` argument is required. center : float, optional The value at which to center the colormap. Passing this value implies use of a diverging colormap. Setting it to ``False`` prevents use of a diverging colormap. robust : bool, optional If ``True`` and ``vmin`` or ``vmax`` are absent, the colormap range is computed with 2nd and 98th percentiles instead of the extreme values. extend : {'neither', 'both', 'min', 'max'}, optional How to draw arrows extending the colorbar beyond its limits. If not provided, ``extend`` is inferred from ``vmin``, ``vmax`` and the data limits. levels : int or array-like, optional Split the colormap (``cmap``) into discrete color intervals. If an integer is provided, "nice" levels are chosen based on the data range: this can imply that the final number of levels is not exactly the expected one. Setting ``vmin`` and/or ``vmax`` with ``levels=N`` is equivalent to setting ``levels=np.linspace(vmin, vmax, N)``. **kwargs : optional Additional keyword arguments to wrapped Matplotlib function.  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Use 'add_guide' instead.r[rrr4Nr5r6rcrdrr)T)Zdrop)sr rrfr)c) r rmr7rDr:r!r2rwherer9r+scatter)r"r rrbrNr[rrr4r5r6r*rrfrBr%r%r&rsT             rc Ks|dus |dus |dus |dur(tdt||||||||\}}}}|j|j|j|jg}|d}|d} |r|||j| dst| d| d| d<|d|d d |j|i|| } | S) zaQuiver plot of Dataset variables. Wraps :py:func:`matplotlib:matplotlib.pyplot.quiver`. Nz)Must specify x, y, u, v for quiver plots.rr[rEr_r`rZpivotZmiddle) r rr!rmr+r r? setdefaultr) r"r rrbrcrdrNrMrr[hdlr%r%r&rs  &    rc Ks|dus |dus |dus |dur(tdt||jdkrH||jd}t||jdkrh||jd}|dur|durt||jt|g}|dur|durt||jt|g}t||||||||\}}}}|dur"|dur"|||}|||}|||}|||}|j|j|j|jg} |d} |d} | r|| j|d<| dst | d | d | d<|d |j | i|| } | j S) zjPlot streamlines of Dataset variables. Wraps :py:func:`matplotlib:matplotlib.pyplot.streamplot`. Nz-Must specify x, y, u, v for streamplot plots.rrrr[ZcolorrEr_r`r) r r;ZdimsrrZ transposer!rmr r?rlines) r"r rrbrcrdrNZxdimZydimrMrr[rr%r%r&r;s8 &        r)N)rZnumpyr0ZpandasrDZcore.alignmentrZ facetgridrZutilsrrrr r r r Zarrayr=r'r7r.rHrrrrr%r%r%r&s&  $ S '" <