a Df@s.dZddlZddlZddlZddlmZddlmZddlm Z m Z m Z m Z m Z mZmZmZmZddlmZmZmZmZddlmZdd lmZmZmZmZmZmZm Z m!Z!m"Z"dd l#m$Z$m%Z%dd l&m'Z'm(Z(dd l)m*Z*m+Z+dd l,m-Z-ddl.m/Z/ddl0m1Z1eeegZ2ddZ3GdddeZ4GdddeZ5GdddeZ6GdddeZ7Gdddej8Z9GdddeZ:GdddeZ;Gd d!d!eZGd&d'd'eZ?Gd(d)d)eZ@Gd*d+d+eZAGd,d-d-eZBGd.d/d/eZCGd0d1d1eZDGd2d3d3ej8ZEdS)4zF Collection of either extremely generic or simple Operation examples. N)Version) _is_number) CollatorDataset DimensionElement GridMatrixHoloMap NdOverlay OperationOverlay)ArrayInterface DictInterfacePandasInterfacedefault_datatype)dask_array_module) datetime_types dt_to_intgroup_sanitizer is_cupy_array is_dask_array is_ibis_expr isdatetimeisfinitelabel_sanitizer) HistogramScatter)ContoursPolygons)RGBImage)categorical_aggregate2d)RangeXY) MaxNLocatorcCs|SN)xkr&r&h/nfs/NAS7/SABIOD/METHODE/ermites/ermites_venv/lib/python3.9/site-packages/holoviews/operation/element.pyidentity.r*c@sDeZdZdZejdddZejdddZej e ddZ d dd Z dS) operationa+ The most generic operation that wraps any callable into an Operation. The callable needs to accept an HoloViews component and a key (that may be ignored) and must return a new HoloViews component. This class may be useful for turning a HoloViews method into an operation to define as compositor operation. For instance, the following definition: operation.instance(op=lambda x, k: x.collapse(np.subtract)) Could be used to implement a collapse operation to subtracts the data between Rasters in an Overlay. Na The output element type which may be None to disable type checking. May be used to declare useful information to other code in HoloViews, e.g. required for tab-completion support of operations registered with compositors.defaultdocr zT The group assigned to the result after having applied the operator.z The operation used to generate a new HoloViews object returned by the operation. By default, the identity operation is applied.cCs@|j||}|jjdur0t||jjs0Jd|j|jjdS)Nz5Return value does not match the declared output type.group)pop output_type isinstanceZrelabelr1)selfviewkeyretvalr&r&r)_processRs  zoperation._process)N) __name__ __module__ __qualname____doc__param Parameterr4Stringr1Callabler*r3r:r&r&r&r)r,0s r,c@sDeZdZdZejeddZejgddZ ej iddZ d ddZ dS) factoryz Simple operation that constructs any element that accepts some other element as input. For instance, RGB and HSV elements can be created from overlays of Image elements. z The output type of the factor operation. By default, if three overlaid Images elements are supplied, the corresponding RGB element will be returned. r-z? The list of positional argument to pass to the factoryz= The dict of keyword arguments to pass to the factoryNcCs"|jj|g|jjRi|jjSr%)r2r4argskwargs)r6r7r8r&r&r)r:mszfactory._process)N) r;r<r=r>r?r@r r4ListrDDictrEr:r&r&r&r)rCZs rCc@s`eZdZejeddZejeddZejddddZ ej gddZ ej id dZ d d d Zd S)function0 The output type of the method operationclass_r/1 The object type the method is defined oncOs|Sr%r&)elrDrEr&r&r)yr+zfunction.z The function to apply.r-> The list of positional argument to pass to the method< The dict of keyword arguments to pass to the methodNcCs"|jj|g|jjRi|jjSr%)r2fnrDrEr6elementr8r&r&r)r:szfunction._process)N)r;r<r=r? ClassSelectortyper4 input_typerBrQrFrDrGrEr:r&r&r&r)rHqs rHc@s`eZdZdZejeddZejeddZej dddZ ej gddZ ej id dZd d d Zd S)methodz, Operation that wraps a method call rIrJrL__call__z The method namer-rOrPNcCs0t|jj|jj}||g|jjRi|jjSr%)getattrr2rV method_namerDrE)r6rSr8rQr&r&r)r:szmethod._process)N)r;r<r=r>r?rTrUr4rVrArZrFrDrGrEr:r&r&r&r)rWsrWc@s>eZdZdZejdddZejddZd ddZd d Z dS) apply_whena Applies a selection depending on the current zoom range. If the supplied predicate function returns a True it will apply the operation otherwise it will return the raw element after the selection. For example the following will apply datashading if the number of points in the current viewport exceed 1000 otherwise just returning the selected points element: apply_when(points, operation=datashade, predicate=lambda x: x > 1000) cCs|Sr%r&r'r&r&r)rNr+zapply_when.r.NFcCsb|}|dur |dur |||f}||}|s2|s:|r>|s>|S|jjrP|gS|jddSdSNr) predicate interfaceZgriddedcloneiloc)r6rSx_rangey_rangeinvertselected conditionr&r&r)_applys   zapply_when._applycKsld|vr|d}ntg}|jjfi||jsr?rBr,r_rhrXr&r&r&r)r[s    r[c@sPeZdZdZejeddZejdddZ ej ge ddZ dd d Z dd d ZdS)chainae Defining an Operation chain is an easy way to define a new Operation from a series of existing ones. The argument is a list of Operation (or Operation instances) that are called in sequence to generate the returned element. chain(operations=[gradient, threshold.instance(level=2)]) This operation can accept an Image instance and would first compute the gradient before thresholding the result at a level of 2.0. Instances are only required when arguments need to be passed to individual operations so the resulting object is a function over a single argument. z| The output type of the chain operation. Must be supplied if the chain is to be used as a channel operation.r-z The group assigned to the result after having applied the chain. Defaults to the group produced by the last operation in the chainzn A list of Operations (or Operation instances) that are applied on the input from left to right.)r.Z item_typer/NcCsF|}|jjD]}|j|||jjd}q |jjs2|S|j|jjdSdS)N) input_rangesr0)r2 operationsZprocess_elementrsr1ra)r6r7r8 processedr,r&r&r)r:s  zchain._processTcCs>d}|jdddD]$}t||r*|}q:|js|rq:q|S)z Returns the first found occurrence of an operation while performing a backward traversal of the chain pipeline. N)rtr5 link_inputs)r6r,Zskip_nonlinkedfoundr3r&r&r)finds  z chain.find)N)T)r;r<r=r>r?r@r!r4rAr1rFr rtr:ryr&r&r&r)rqs  rqc@s8eZdZdZeZejdddZej ddZ d dd Z dS) transforma} Generic Operation to transform an input Image or RGBA element into an output Image. The transformation is defined by the supplied callable that accepts the data of the input Image (typically a numpy array) and returns the transformed data of the output Image. This operator is extremely versatile; for instance, you could implement an alternative to the explicit threshold operator with: operator=lambda x: np.clip(x, 0, 0.5) Alternatively, you can implement a transform computing the 2D autocorrelation using the scipy library with: operator=lambda x: scipy.signal.correlate2d(x, x) TransformzO The group assigned to the result after applying the transform.r-z Function of one argument that transforms the data in the input Image to the data in the output Image. By default, acts as the identity function such that the output matches the input.r/NcCs.|jjs|jn |j|j}|j||jjdS)Nr0)r2operatordatarar1)r6imgr8rur&r&r)r:#s ztransform._process)N) r;r<r=r>r!r4r?rAr1rBr}r:r&r&r&r)rzs  rzc@sfeZdZdZeZejddZej ddZ ej dddZ ejd d dZ ed d Zd dZdddZdS) image_overlaya Operation to build a overlay of images to a specification from a subset of the required elements. This is useful for reordering the elements of an overlay, duplicating layers of an overlay or creating blank image elements in the appropriate positions. For instance, image_overlay may build a three layered input suitable for the RGB factory operation even if supplied with one or two of the required channels (creating blank channels for the missing elements). Note that if there is any ambiguity regarding the match, the strongest match will be used. In the case of a tie in match strength, the first layer in the input is used. One successful match is always required. a Specification of the output Overlay structure. For instance: Image.R * Image.G * Image.B Will ensure an overlay of this structure is created even if (for instance) only (Image.R * Image.B) is supplied. Elements in the input overlay that match are placed in the appropriate positions and unavailable specification elements are created with the specified fill group.r|rr]rz} The default range that will be set on the value_dimension of any automatically created blank image elements.r-r{z5 The group assigned to the resulting overlay.cCsttgd|d}t|tr.|ddkr6tdttd}d}dD]8}||t||}||vrH|||krxdS|d7}qH|S) z3Return the strength of the match (None if no match)rUr1label.rUr!zOnly Image currently supportedr1rrN) dictzipsplitr5r!NotImplementedErrorrrrY)clsrMspec spec_dictZ sanitizersstrengthr8 attr_valuer&r&r)_matchUs  zimage_overlay._matchc Csdgt|}dgt|}t|tr.|n|g}|D]R}tt|D]@}||||}|durhqHqH|||krxqHqH|||<|||<qHq8||fS)z Given a raster or input overlay, generate a list of matched elements (None if no match) and corresponding tuple of match strength values. Nr)lenr5r valuesranger) r6rasterZ overlay_specordering strengthselementsrMposrr&r&r)_match_overlayfs  zimage_overlay._match_overlayNc Cstdd|jjdD}|||\}}tdd|DrFtdg}|t|}t ||D]r\}} |durt t gd| d} t t |j j|jj| dd | d d d }|jj|jd _||qbt|S)Ncss|]}|VqdSr%)strip.0rMr&r&r) }r+z)image_overlay._process..*css|]}|duVqdSr%r&rr&r&r)rr+z7The image_overlay operation requires at least one matchrrr1r!rrrrr)tupler2rrrall ExceptionnpZargmaxrrr!onesr~shapefillget default_rangevdimsrappendprod) r6rr8specsrrZ completedZ strongestrMrrr&r&r)r:|s    zimage_overlay._process)N)r;r<r=r>r r4r?rArNumberrTuplerr1 classmethodrrr:r&r&r&r)r)s  rc@sZeZdZdZeZejdddZejdddZ ejdddZ ej d d dZ d Z dd dZd S) thresholdz Threshold a given Image whereby all values higher than a given level map to the specified high value and all values lower than that level map to the specified low value. g?z The value at which the threshold is applied. Values lower than the threshold map to the 'low' value and values above map to the 'high' value.r-g?zR The value given to elements greater than (or equal to) the threshold.gz7 The value given to elements below the threshold.Z Thresholdz5 The group assigned to the thresholded output.TNcCsht|tstd|j}t|j|jj}t|j|jj }t ||jj k||}|j ||jj dS)Nz2The threshold operation requires a Image as input.r0)r5r! TypeErrorr~rrrr2highlowwherelevelrar1)r6matrixr8arrrrZ thresholdedr&r&r)r:s zthreshold._process)N)r;r<r=r>r!r4r?rrrrrAr1 _per_elementr:r&r&r&r)rsrc@s0eZdZdZeZejdddZdZ d ddZ dS) gradientz Compute the gradient plot of the supplied Image. If the Image value dimension is cyclic, the smallest step is taken considered the cyclic range ZGradientz6 The group assigned to the output gradient matrix.r-TNc CsRt|jdkrtd|jd}t|j|dd}|j\}}|jrVd|jvrVt d|js`dn t |j}|dur||jd}tj |dddd|dd|df}tj |dddd|dd|df} |dur,||}| |} ||} | |} t t | |k| |}t t | | k| | } t t||| | |j|jjdS) NrzDInput matrix to gradient operation must have single value dimension.rFZflatzKCyclic range must be specified to compute the gradient of cyclic quantitiesZaxisboundsr1)rrrlrflipuddimension_valuesrZcyclicrrdiffrabsr!sqrtrr2r1) r6rr8Z matrix_dimr~rcZ cyclic_rangeZdxZdyZ dx_negativesZ dy_negativesr&r&r)r:s(  (( zgradient._process)N) r;r<r=r>r!r4r?rAr1rr:r&r&r&r)rs rc@s@eZdZdZeZejdddZej ddddZ d Z d d d Z d S)convolvez Apply a convolution to an overlay using the top layer as the kernel for convolving the bottom layer. Both Image elements in the input overlay should have a single value dimension. Z Convolutionz4 The group assigned to the convolved output.r-rrrrz A 2-dimensional slice of the kernel layer to use in the convolution in lbrt (left, bottom, right, top) format. By default, no slicing is applied.r.lengthr/TNcCs.t|dkrtd|d|d}}t|jdkr@tdt|jjd|jjd}t|jjd|jjd}|jjdkr|jn |||fj}t |j ddd }tj |} tj j ||j d } tj | | j} |j \} } tjtj| | d d d | d d d }|t|}t||j|jjdS)Nrz'Overlay must contain at least to items.rrz9Convolution requires inputs with single value dimensions.rFr)srvrr)rrrrslicer2 kernel_roir~rrrZfftfft2rZifft2realZrollfloatsumr!rr1)r6overlayr8targetkernelZxsliceZyslicer(r~Zfft1rZ convolved_rawZk_rowsZk_colsZrolledZ convolvedr&r&r)r:s     (zconvolve._process)N) r;r<r=r>r!r4r?rAr1 NumericTuplerrr:r&r&r&r)rs rc@s`eZdZdZeZejdee fddZ ej dddZ ej dd dZej dd dZd Zdd dZd S)contoursz Given a Image with a single channel, annotate it with contour lines for a given set of contour levels. 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Nrz< Specifies the range within which to compute the bins.rz An explicit set of bin edges or a method to find the optimal set of bin edges, e.g. 'auto', 'fd', 'scott' etc. For more documentation on these approaches see the np.histogram_bin_edges documentation.rFz2 Whether to compute the cumulative histogramr-zE Along which dimension of the Element to compute the histogram.zT Format string defining the label of the frequency dimension of the Histogram.zW Defines a dimension to group the Histogram returning an NdOverlay of Histograms.zD Whether to use base 10 logarithmic samples for the bin edges.z5 Whether the weighted frequencies are averaged.)TFintegralheighta^ Controls normalization behavior. If `True` or `'integral'`, then `density=True` is passed to np.histogram, and the distribution is normalized such that the integral is unity. If `False`, then the frequencies will be raw counts. 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Auto-ranges if set to None.c Cst|tstd|jtvr2|t|}|j j rB|j j n| d\}}|j j r`|j j n| d\}}|j dddd\}}|jfi|||f|||fi} t| |j jkrtj|j j} | t| |j jd} | jt| S| S)Nz$Cannot downsample non-Dataset types.rrTrrF)r5rrlr`column_interfacesrarcolumnsrr2rcrrdrselectr max_samplesrrandomZ RandomState random_seedchoicerbsort) r6rSr8ZxstartZxendZystartZyendrrZslicedZprngrIr&r&r)_process_layers  zdecimate._process_layercCs||jtSr%rrKrrRr&r&r)r:szdecimate._process)N)N)r;r<r=r>r?rZdynamicrwr@rFrHrTr#rrrirrcrdrrKr:r&r&r&r)rAs rAc@s`eZdZdZejgddddZdZeddZ ed d Z ed d Z dddZ dddZ d S)interpolate_curvezw Resamples a Curve using the defined interpolation method, e.g. to represent changes in y-values as steps. ) steps-pre steps-mid steps-postZlinearrOzC Controls the transition point of the step along the x-axis.)r r.r/Tcstdtd}tfdd|D}|ddd<|ddd|ddd<g}t||D]8\}}||ddd<|ddd|ddd<||q`|t|fS)Nrrc3s*|]"}tjdtd|jdVqdSrrdtypeNrrrrSrvr\r&r)rr+z3interpolate_curve.pts_to_prestep..rrrr1rrrrrr'rr;Z value_stepsZ val_arraysrVrr&r\r)pts_to_presteps z interpolate_curve.pts_to_prestepcstdt}tfdd|D}ddddddd|ddd<|ddd<dd|d<|d<g}t||D]8\}}||ddd<|ddd|ddd<||q|t|fS)Nrc3s&|]}tjdt|jdVqdS)rrRNrTrUr\r&r)rr+z3interpolate_curve.pts_to_midstep..rvrrrWrXr&r\r)pts_to_midstep s@ z interpolate_curve.pts_to_midstepcstdtd}tfdd|D}|ddd<|ddd|ddd<g}t||D]8\}}||ddd<|ddd|ddd<||q`|t|fS)Nrrc3s*|]"}tjdtd|jdVqdSrQrTrUr\r&r)r r+z4interpolate_curve.pts_to_poststep..rrrWrXr&r\r)pts_to_poststeps z!interpolate_curve.pts_to_poststepNc s|j|j|jd}|jj|vr"Sd}t|}|rFd}||}tfdd ddD}||jj||\}}|r||} |f|S)N)rNrOrPrrc3s|]}|VqdSr%)rr rSr&r)r8r+z3interpolate_curve._process_layer..r) rYrZr[r2 interpolationrrrrrra) r6rSr8ZINTERPOLATE_FUNCSr'rZdt_typeZdvalsrr&r\r)rK-s    " z interpolate_curve._process_layercCs||jtSr%rLrRr&r&r)r:>szinterpolate_curve._process)N)N)r;r<r=r>r?r?r]rrrYrZr[rKr:r&r&r&r)rMs     rMc@s*eZdZdZejejddZdddZ dS)collapsea* Given an overlay of Element types, collapse into single Element object using supplied function. Collapsing aggregates over the key dimensions of each object applying the supplied fn to each group. This is an example of an Operation that does not involve any Raster types. z[ The function that is used to collapse the curve y-values for each x-value.r-NcCs:t|trt|}ntddt|D}|j|jjdS)NcSsi|]\}}||qSr&r&)rirMr&r&r) Yr+z%collapse._process..)rH)r5r r rr^r2rQ)r6rr8Z collapse_mapr&r&r)r:Us  zcollapse._process)N) r;r<r=r>r?rBrmeanrQr:r&r&r&r)r^Gs r^c@sZeZdZdZejeddZejdddZeje ddZ ej gddZ dd Z d d d ZdS) gridmatrixaT The gridmatrix operation takes an Element or HoloMap of Elements as input and creates a GridMatrix object, which plots each dimension in the Element against each other dimension. This provides a very useful overview of high-dimensional data and is inspired by pandas and seaborn scatter_matrix implementations. zV The Element type used to display bivariate distributions of the data.r-Nz The Element type along the diagonal, may be a Histogram or any other plot type which can visualize a univariate distribution. 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