o .wi}8@s ddlmZmZddlmZddlmZmZmZddl m Z m Z m Z m Z mZddlZddlZddlmZddlmZmZmZermddlZddlZddlmZeeje ejjej ffZ!ejjZ"e ej#j$e%fZ&ej'j(Z)nee*e*fZ!e*Z"e*Z&ddl+m,Z,e,d e d e d efd d Z)erddl-Z-ddgZ.ererdgndgZ.d2ddZ/e)e.      d3de eeee0e%efee0e%effde e"de e1de e2de e2de e%de e%d e!fddZ3de4d ee4e4ffddZ5dee2e2e2e2fd e%fd d!Z6d"e e"ej fd#e4d e ej e"ffd$d%Z7e)e.e  &  d4d'ede e"d(e1d)e e8e e4e%fd*e e&d e!f d+d,Z9e)e.      d3d-e eeeefee ee ee effd.e ede e"d/e ee%e%fde e%de e%d)e e8e e4e%fd e!fd0d1Z:dS)5) GeneratorSequence)product)ceilfloorsqrt)AnyListOptionalUnion no_type_checkN)Tensor)_LATEX_AVAILABLE_MATPLOTLIB_AVAILABLE_SCIENCEPLOT_AVAILABLE)contextmanagerargskwargsreturncos dVdS)z0No-ops decorator if matplotlib is not installed.N)rrrrX/home/ubuntu/sommelier/.venv/lib/python3.10/site-packages/torchmetrics/utilities/plot.py style_change*s rsciencezno-latexdefaultcCststddS)z+Raise error if matplotlib is not installed.z`Plot function expects `matplotlib` to be installed. Please install with `pip install matplotlib`N)rModuleNotFoundErrorrrrr_error_on_missing_matplotlib8s rvalaxhigher_is_better lower_bound upper_bound legend_namenamec s$t|dur tnd|f\}}|dttrVdkr1|j gdddnt D]\}} |rB|d|n|} |j|| ddd| d q5ntt rt  D]?\}\} } | dkr|j| ddd | d |d |d |tt| qa|j|| dd| d qanttr*ttdt rׇfdddD D]\} } |j| ddd | d qn>tdjdk} | rjndt D]$\}} | r|r|d|n|nd} |j| ddd | d q|d |d |tntd|\} }| rF|rF|j| |dddd d d|}|dur[|dur[d||}n d|d|d}|j|durp||n|d||dur~||n|d|d|d ||dur|nd|}d|d|d}g}|dur| ||dur| ||j!||d|dddd|dur|dur|s|"|d||d|j#|d|dddd|dur|r|"|d||d|j#|d|dddd||fS)aPlot a single metric value or multiple, including bounds of value if existing. Args: val: A single tensor with one or multiple values (multiclass/label/output format) or a list of such tensors. If a list is provided the values are interpreted as a time series of evolving values. ax: Axis from a figure. higher_is_better: Indicates if a label indicating where the optimal value it should be added to the figure lower_bound: lower value that the metric can take upper_bound: upper value that the metric can take legend_name: for class based metrics specify the legend prefix e.g. Class or Label to use when multiple values are provided name: Name of the metric to use for the y-axis label Returns: A tuple consisting of the figure and respective ax objects of the generated figure Raises: ModuleNotFoundError: If `matplotlib` is not installed NFo )marker markersize None)r&r' linestylelabel-TStep)r&r'r+rcs,i|]tfddtDqS)csg|]}|qSrr).0i)krrr vsz7plot_single_or_multi_val...)torchstackrange)r.n_stepsr)r0r vs,z,plot_single_or_multi_val..z&Got unknown format for argument `val`.z upper center)g?gffffff?)locbbox_to_anchorncolfancyboxshadowg?)bottomtopdashedr0) linestylescolorszOptimal valuecenter)shorizontalalignmentverticalalignment)$rpltsubplots get_xaxis set_visible isinstancer numelplotdetachcpu enumeratedictitems set_xlabel set_xticksr2arangelenrr3ndimT unsqueeze ValueErrorget_legend_handles_labelslegendget_ylimset_ylimgrid set_ylabelget_xlimappendhlinesset_xlimtext)rrrrr r!r"figr/vr+r0 multi_serieshandleslabelsylimfactorxlimy_linesrr5rplot_single_or_multi_val@s         $         rpncCsXt|}t||krt|t|fSt|t||kr$t|t|fSt|t|fS)z/Split `n` figures into `rows` x `cols` figures.)rintrr)rqnsqrrr_get_col_row_splits  rt patch_colorcCsN|\}}}}dd|||fD\}}}d|d|d|}|dkr%dSdS) zGet the text color for a given value and colormap. Following Wikipedia's recommendations: https://en.wikipedia.org/wiki/Relative_luminance. Args: patch_color: RGBA color tuple css0|]}|dkr |dn|dddVqdS)g?ܵ?gףp= )@g)\(?gzG?g333333@Nr)r.crrr s.z"_get_text_color..gz6?g,C?g]m{?g?z.1whiter)rurgbayrrr_get_text_colors r~axsnbcCs:t|tr|S|j}||dD]}|q|d|S)zSReduce `axs` to `nb` Axes. All further Axes are removed from the figure. N)rL_AX_TYPEflatremove)rrrrrrtrim_axss   rTconfmatadd_textrkcmapc Cszt|jdkr|jdd}}t|\}}n d|jdddf\}}}}|dur?|jdkr?t||kr?tdt|d||jdkrU|pJt|} tt t t |}n d} |p_t| }|durlt j||dd n||f\} } t| |} t |D]} |dks|dkr| | n| }| dur|jd | | d d |j|jdkr|| n||d } | ||dkr|jdd d | |dkr|jdd d |tt ||tt ||j|ddd|j|ddd|r8tt |t |D]8\}}|jdkr|| ||fn|||f}| | |}t|}|j ||t t!|dddd |dqq}| | fS)aPlot an confusion matrix. Inspired by: https://github.com/scikit-learn/scikit-learn/blob/main/sklearn/metrics/_plot/confusion_matrix.py. Works for both binary, multiclass and multilabel confusion matrices. Args: confmat: the confusion matrix. Either should be an [N,N] matrix in the binary and multiclass cases or an [N, 2, 2] matrix for multilabel classification ax: Axis from a figure. If not provided, a new figure and axis will be created add_text: if text should be added to each cell with the given value labels: labels to add the x- and y-axis cmap: matplotlib colormap to use for the confusion matrix https://matplotlib.org/stable/users/explain/colors/colormaps.html Returns: A tuple consisting of the figure and respective ax objects (or array of ax objects) of the generated figure Raises: ModuleNotFoundError: If `matplotlib` is not installed r9rr#NzYExpected number of elements in arg `labels` to match number of labels in confmat but got  and T)nrowsncolsconstrained_layoutzLabel )fontsize)rzPredicted classz True class-r%)rotationrrD)havarcolor)"rrXshapertrWr[nprVlistmapstrr4tolistrHrI get_figurer set_titleimshowrPrOrTrarU set_yticksset_xticklabelsset_yticklabelsrrnormitemr~rfround)rrrrkrr n_classesrowscols fig_labelrgrr/imiijjrrurvrrrplot_confusion_matrixsR  (  0 &(rcurvescore label_namescCs:t|dkrtdt||dd\}}t|dur"tnd|f\} }t|tret|tre|jdkre|jdkre|durHd|dnd} |j | | dd| d| durd| nt|t rot|t st|trt|tr|jdkr|jdkrt|} |durt|| krtd t|d | tt||D]G\} \} }|dur|d | n |durt| nt|| } | |durd || dnd 7} |j | | dd| d| qntdt|d t|d|dur||d||d|d||| |fS)aInspired by: https://github.com/scikit-learn/scikit-learn/blob/main/sklearn/metrics/_plot/roc_curve.py. Plots a curve object Args: curve: a tuple of (x, y, t) where x and y are the coordinates of the curve and t are the thresholds used to compute the curve score: optional area under the curve added as label to the plot ax: Axis from a figure label_names: Tuple containing the names of the x and y axis legend_name: Name of the curve to be used in the legend name: Custom name to describe the metric labels: Optional labels for the different curves that will be added to the plot Returns: A tuple consisting of the figure and respective ax objects (or array of ax objects) of the generated figure Raises: ModuleNotFoundError: If `matplotlib` is not installed ValueError: If `curve` does not have 3 elements, being in the wrong format rz*Expected 2 or 3 elements in curve but got Nr#zAUC=z0.3fr,)r* linewidthr+z\Expected number of elements in arg `labels` to match number of labels in roc curves but got r_z AUC=r8zQUnknown format for argument `x` and `y`. Expected either list or tensors but got .rT)rWr[rrHrIrLr rXrrNrOrPr]rrQziprtyperTrar`r)rrrrr!r"rkxr}rgr+rr/x_y_rrr plot_curve(sR !($2$$    r)rN)NNNNNN)NTNN);collections.abcrr itertoolsrmathrrrtypingrr r r r numpyrr2r torchmetrics.utilities.importsrrr matplotlibmatplotlib.axesmatplotlib.pyplotpyplotrHtupleFigureaxesAxesndarray_PLOT_OUT_TYPErrCColormapr _CMAP_TYPEstylecontextrobject contextlibr scienceplots_stylerrRboolfloatrprrrtr~rrrrrrrrs       & n *K*