a Df@sdZddlZddlmZddlZddlZddlmZm Z ddl m Z ddl m Z d d Zd d Zd dZddZeedZGddde ZdS)a@ Implements downsampling algorithms for large 1D datasets. The algorithms implemented in this module have been adapted from https://github.com/predict-idlab/plotly-resampler and are reproduced along with the original license: MIT License Copyright (c) 2022 Jonas Van Der Donckt, Jeroen Van Der Donckt, Emiel Deprost. Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. N)partial) NdOverlayOverlay)Area)ResampleOperation1DcCs2t||||||||||S)a-Vectorized triangular area argmax computation. Parameters ---------- prev_x : float The previous selected point is x value. prev_y : float The previous selected point its y value. avg_next_x : float The x mean of the next bucket avg_next_y : float The y mean of the next bucket x_bucket : np.ndarray All x values in the bucket y_bucket : np.ndarray All y values in the bucket Returns ------- int The index of the point with the largest triangular area. )npabsZargmax)Zprev_xZprev_yZ avg_next_xZ avg_next_yZx_bucketZy_bucketr k/nfs/NAS7/SABIOD/METHODE/ermites/ermites_venv/lib/python3.9/site-packages/holoviews/operation/downsample.py _argmax_area*s  r c Csd}t|dD]~}||||d||d}}} t||||||| ||| ||||||||}|||d<qt|||||d|d||d|d||d|d|d|d<dS)Nrrr)ranger mean) xyn_out sampled_xoffsetaiZo0Zo1Zo2r r r _lttb_innerFs4$   rcCs|jdd|d}tjd|jd|dtj}tj|tjd}d|d<|jdd|d<|jjdkrv|tj}|jjdkr|tj}t ||||||S)a7 Downsample the data using the LTTB algorithm (python implementation). Args: x (np.ndarray): The x-values of the data. y (np.ndarray): The y-values of the data. n_out (int): The number of output points. Returns: np.array: The indexes of the selected datapoints. rrr)startstopstep)dtyperM) shaper arangeastypeint64emptyrkindviewr)rrr block_sizerrr r r _lttbfs     r(c Cs&t|}td|tdt||S)a  Downsampling by selecting every n-th datapoint Args: x (np.ndarray): The x-values of the data. y (np.ndarray): The y-values of the data. n_out (int): The number of output points. Returns: np.array: The indexes of the selected datapoints. rr)lenr r!maxmathceil)rrrZ n_samplesr r r _nth_points r-)lttbnthc@s,eZdZdZejdddgdZdddZdS) downsample1dz Implements downsampling of a regularly sampled 1D dataset. Supports multiple algorithms: - `lttb`: Largest Triangle Three Buckets downsample algorithm - `nth`: Selects every n-th point. r.r/)defaultZobjectsNcstttfrZt|j|dttr:fddD}nfddD}|S|jjrrt |jjt |jj krSfddt dD\}}|j tjkr|tj}t|jj}|jjd krttrtd ||||jj }j|S) N)keycsg|]}|qSr map).0v_processr r z)downsample1d._process..csi|]\}}||qSr r3)r5kr6r7r r r:z)downsample1d._process..c3s|]}|VqdS)N)Zdimension_values)r5r)elementr r r:z(downsample1d._process..rr.z-LTTB algorithm is not implemented for hv.Area) isinstancerrrr8itemsclonepZx_rangeslicer)widthrrr Zbool_r"Zint8 _ALGORITHMS algorithmrNotImplementedErrorZiloc)selfr=r2elementsxsZysZ downsampleZsamplesr )r8r=r r8s(     zdownsample1d._process)N)__name__ __module__ __qualname____doc__paramZSelectorrFr8r r r r r0s r0)rNr+ functoolsrnumpyr rOcorerrZ element.chartrZresamplerr rr(r-rEr0r r r r s    "