192 results about "Regular grid" patented technology

The invention relates to the technical field of marine surveying and mapping and submarine topography modeling, and discloses a submarine topography and landform construction method based on multi-source water depth data fusion, which comprises a multi-source data acquisition module, a data preprocessing module, a feature extraction module, a fusion algorithm matching module, a three-dimensional modeling module and an uncertainty evaluation module. A historical submarine topographic map is converted into grid data, namely, submarine topography is discretized into digital representation of regular grid units, water depths of other sources are converted into the grid data, the precision of the water depths of different sources is evaluated by adopting a superposition comparison method, and an error distribution model is established to reasonably correct and fuse the water depth data of various sources. The innovation of the method lies in that topographic feature parameters including the gradient, the curvature matrix and the bionic optimization algorithm are introduced, the defect that a single algorithm is preset in a traditional method is overcome, and the precision of coral reef and fault zone complex areas is improved.

The invention discloses a dynamic DEM spatial interpolation method which comprises the following steps: performing depression filling, flow direction analysis and confluence cumulant calculation on DEM data, and extracting a natural sub-basin unit by adopting a minimum catchment area threshold method; constructing a topographic feature matrix, performing refined second-level classification on the first-level drainage basin through an improved self-organizing mapping network, generating a hydrological response unit through boundary processing, and establishing a hydrological attribute library; fusing multi-source data, supplementing attribute interpolation such as underlying surface and rainfall, and constructing an interpolation auxiliary parameter system; a drainage basin is divided into regular grids as neurons, a dynamic neural network containing dynamic states and static attributes is constructed, and nonlinear mapping of DEM correction parameters is achieved through optimization of a dynamic activation function and a loss function. The method overcomes the defects that a traditional interpolation algorithm does not consider hydrological boundary constraints, a neural network model topological structure is fixed and the like, and the DEM interpolation precision and the hydrological simulation effect of the complex terrain area are improved.

The invention relates to the technical field of ocean engineering digital twinning and three-dimensional visualization, and provides a method and system for generating dredging terrain twinning based on a right-angle triangular mesh, and the method comprises the steps: obtaining regular grid elevation unified to an engineering plane coordinate system or preprocessed sampling height data, determining a covered space range, reading the space range and density parameters, and calculating the total row number and the total column number of the grids based on the space range and the density parameters; generating regularly arranged vertexes in the covered space, and constructing a topological structure of an isosceles right triangle grid; dividing the global grid into a plurality of Chunk blocks according to a fixed size by taking a vertex as a unit, establishing a triangular index mapping relationship between global rows and columns and the Chunk blocks, filling three vertexes of an isosceles right triangle and elevation / height data in each Chunk block in parallel, and generating local VBO, IBO and AABB; and performing batch rendering and coloring according to a height color table on all Chunk blocks to realize visualization of the terrain.

The invention provides a point cloud downsampling method applied to unmanned aerial vehicle obstacle avoidance, and aims to solve the problems of low mapping efficiency and geometric detail loss caused by large point cloud data volume and non-uniform density in environmental perception. The method comprises the following steps: preprocessing an original point cloud through a regular grid to balance density, and extracting an effective flight area of the unmanned aerial vehicle by adopting bidirectional cloth simulation filtering and combining with a flight height; multi-level geometric features including elevation gradient, curvature and roughness are calculated, and point cloud priority scores are fused and generated based on principal component analysis; voxel grids are divided according to the size of the unmanned aerial vehicle, the sampling rate of each voxel is adaptively set in combination with the priority, farthest point sampling is executed in the feature space to select representative points, and finally a simplified point cloud model is output. The method can be integrated to a mapping module of a multi-aircraft cooperative obstacle avoidance and planning system, is suitable for unmanned aerial vehicle path planning tasks in a complex three-dimensional environment, and has the characteristics of light weight, accuracy, high efficiency and the like.

The invention belongs to the technical field of physical ocean and remote sensing application, and particularly relates to a sub-mesoscale signal extraction method based on Ku / Ka dual-frequency SAR (Synthetic Aperture Radar) height measurement, which comprises the following steps of: acquiring a Ku / Ka dual-frequency sea surface height observation original data set and IMU (Inertial Measurement Unit) attitude and trajectory data; registering the average sea surface and tide height to a space-time sampling position of Ku / Ka synchronous observation and deducting from the original height to obtain an initial sea surface height anomaly sequence of the two channels, and processing the initial sea surface height anomaly data of the two channels to obtain a fused height anomaly sequence; performing attitude coupling mode extraction on the fused height anomaly sequence to obtain a height anomaly sequence after platform error elimination; meanwhile, smoothing processing is carried out to obtain a smoothed sequence; and interpolating the smoothed sequence into a two-dimensional regular grid, performing small-scale secondary smoothing denoising on grid data, interpolating a mesoscale background field at the same time into the same grid, and deducting the mesoscale background field to obtain a sea surface height anomaly data system with sub-mesoscale as a main part.

The invention discloses a salinization remote sensing inversion method fusing crop information and data preprocessing. A land utilization data set is subjected to splicing, cutting and other processing to obtain a high-confidence-coefficient cultivated land range; point distribution sampling is carried out according to a regular grid method, and soil conductivity is measured; preprocessing the remote sensing image; dividing crop growth stages and constructing a multi-temporal spectral feature set; constructing an NDVI time sequence data set and extracting phenological characteristics; extracting planting structure information based on the multi-temporal spectrum and phenological characteristics; a planting structure is converted into crop type data through one-hot coding, and the crop type data is fused with multi-temporal spectrum and phenological characteristics to construct a crop information data set; the method comprises the following steps: constructing a salinity inversion model through data preprocessing and combining with ground actually measured salinity data, and verifying the salinity inversion model; evaluating the cross-year generalization ability of the model; and finally, the inversion result is visualized to generate a salinization map. According to the invention, the system integrates the multi-dimensional information of crops and optimizes the data preprocessing process, and significantly improves the salinization monitoring precision and the cross-space-time adaptability.

The invention discloses a steep cliff three-dimensional modeling method and system based on structural plane constraint, and relates to the technical field of three-dimensional geographic information system.The steep cliff three-dimensional modeling method comprises the steps that steep cliff area geological data including steep cliff multi-view images and steep cliff surface dense point cloud data are collected, and a geological prior knowledge base is constructed; an image recognition technology is used for processing a steep cliff multi-view image, point cloud geometric analysis is combined, and the structural plane spatial orientation including a rock stratum interface and a joint plane is recognized. According to the method, geological priori knowledge is fused, the geometric distortion problem of a traditional digital elevation model in a cliff area is effectively solved, the spatial orientation of a rock stratum interface and a joint surface is extracted by using an image recognition technology, and the spatial orientation is used as a hard constraint condition to construct a control triangulation network framework; the problems of forced smoothing errors of a regular grid DEM and a suspended surface of a triangular irregular network are avoided, and the rock stratum structure, the crack distribution and the dangerous rock body form of the cliff can be precisely restored through the self-adaptive triangulation algorithm.

The invention discloses an infrared bidirectional thermal effect simulation method based on radiation and GPU acceleration, and belongs to the field of thermal radiation simulation and parallel computing. Dispersing the complex geometry into patch units, constructing an inter-patch radiation energy balance equation based on a radiance theory, and iteratively solving the final temperature of the patches through a radiance method; a three-level parallel strategy of a task level, a data level and an instruction level is designed, data intensive tasks such as shape factor calculation and radiance iteration are migrated to a GPU to be executed, data storage is optimized in combination with a structure array (SoA) layout and a sparse matrix compression technology, and efficient data sharing of a CPU end and a GPU end is achieved through a CUDA zero copy technology. According to the method, the dependence of a traditional method on regular grids is broken through, the calculation efficiency and precision of million-level surface patch heat radiation transmission in a complex scene are remarkably improved, and an efficient tool is provided for heat radiation indirect transmission calculation and a global illumination model in the field of three-dimensional scene infrared simulation.

The invention relates to the technical field of photogrammetry, in particular to an earthwork measuring and calculating system based on an unmanned aerial vehicle surveying and mapping technology, which comprises a BIM (Building Information Modeling) route partitioning module, a point cloud quality evaluation module, a digital earth surface model generation module and an earth volume measuring and calculating module. According to the method, by analyzing geometric parameters such as gradient and curvature of a designed curved surface, intelligently partitioning and optimizing an unmanned aerial vehicle surveying and mapping route, and executing independent density clustering on point cloud data streams according to route partitions, dynamic evaluation and marking of spatial data quality are realized, and vegetation point clouds are removed in combination with image color information; the method comprises the following steps: correcting data by using an abnormal mark of quality evaluation, generating an accurate digital earth surface model, finally carrying out elevation deviation comparison on the accurate digital earth surface model and a designed curved surface, finely calculating the earth volume through a regular grid, and carrying out statistical analysis by using a root mean square error, thereby improving the accuracy and reliability of a measurement result.

The embodiment of the specification discloses a self-adaptive variable grid forward modeling method for middle-deep dry hot rock mass. p , a transverse wave velocity V s and a medium density p model, pre-setting forward modeling parameters; performing self-adaptive variable grid processing on the velocity model, determining a mapping relationship between coordinate systems, and determining a wave equation under variable grid based on the mapping relationship; performing self-adaptive variable grid processing on the velocity model, determining a mapping relationship between coordinate systems, obtaining the underground medium longitudinal wave velocity, transverse wave velocity and density after variable grid, determining a wave equation under variable grid based on the mapping relationship, and generating final regular grid horizontal direction longitudinal wave field, horizontal direction transverse wave field, vertical direction longitudinal wave field and vertical direction transverse wave field information by using the mapping relationship reversely according to the wave field information in each direction at a specific moment after the variable grid, so that the memory occupation is small and the calculation speed is faster.

The invention relates to the technical field of wafer testing, in particular to a wafer testing result visualization method and system. Through spatial discretization processing, continuous physical coordinates of test points are mapped to a fixed N * N regular grid, and mass and disordered coordinate points are classified into limited and ordered grid units through the conversion, so that the complexity of data positioning is reduced from O (n) to O (1). When rendering is carried out, a system can directly access grid data at any position through simple coordinate transformation without traversing all test points based on a data structure established on the basis of the regular grid. More importantly, the rendering mode is dynamically selected and drawn, so that the rendering calculation amount of the system does not depend on the total amount of test points any more, but depends on the number of grids in the current viewport. And the processing object is fundamentally optimized from a'test point 'to a'viewport inner grid', so that the data processing and rendering efficiency is greatly improved.

The embodiment of the invention provides a rail transit 3D data defect detection method and system based on spatial indexing, and the method comprises the steps: collecting rail 3D original data, carrying out the preprocessing, and unifying the data into a unified rail coordinate system; dividing the preprocessed track 3D data into a plurality of regular grid units as space units according to spatial positions, extracting multi-dimensional features of data in each space unit, establishing a composite index for each space unit, and storing the composite index in a space-time database; after the acquired 3D data of the current track are subjected to identical processing, spatial position areas corresponding to the 3D data of the current track and historical data are quickly matched through a composite index, and a difference value of multi-dimensional features is calculated; dynamically adjusting the defect judgment threshold of each dimension according to the statistical distribution of the difference values, judging the defect type and severity of the region meeting the threshold, and generating a detection report. The problems that traditional 3D data processing is low in efficiency and long in comparison time consumption are solved.

The invention provides a geological disaster risk assessment data processing method and system, and relates to the technical field of geological disasters, and the method comprises the steps: obtaining original observation data of an assessment region, and generating a plurality of error measurement indexes according to the original observation data; mapping the original observation data and the error measurement index to a regular grid to obtain a grid field, and constructing a geographic analysis block; constructing disaster-causing state variables based on the geographic analysis blocks, executing spatial adjacency consistency check, and if adjacent geographic analysis blocks are located in the same influence area and the KL divergence of the corresponding disaster-causing state variables is smaller than a probability target value, merging the adjacent geographic analysis blocks into a comprehensive risk block; elevation deviation caused by terrain shielding of a digital elevation model, spatial interpolation uncertainty caused by sparse rainfall stations and distortion caused by atmosphere and decoherence interference on InSAR deformation are converted into quantifiable error measurement indexes, and the accuracy of risk assessment is improved.

A rock burst risk dynamic assessment method based on a Bayesian method comprises the steps that a stope working face is divided into M * M regular grids, and each grid serves as an independent assessment unit; collecting geological and mining data, selecting a plurality of influence factors based on historical data and expert knowledge, and quantifying the plurality of influence factors by adopting a static evaluation model; determining weights of a plurality of influence factors by using an analytic hierarchy process, and calculating an initial risk score of each evaluation unit by using a comprehensive index method; normalizing the initial dangerousness score into prior distribution by adopting an S-type function, and constructing an initial dangerousness prior probability field; a power law attenuation model is introduced to calculate influence weights among the evaluation units, and an influence weight matrix is constructed; real-time monitoring data are obtained through a micro-seismic monitoring system, the risk probability of each evaluation unit is updated in real time based on the Bayesian theorem, and dynamic evaluation and evaluation result output are achieved. According to the method, the accuracy and the real-time performance of rock burst risk assessment can be effectively improved.

The application discloses a cliff three-dimensional modeling method and system based on structure surface constraint, relates to the technical field of three-dimensional geographic information systems, collects cliff regional geological data including cliff multi-view images and cliff surface dense point cloud data, and constructs a geological prior knowledge base; image recognition technology is used to process the cliff multi-view images, combined with point cloud geometry analysis, to identify the spatial orientation of structure surfaces including rock layer interfaces and joint surfaces. The application effectively solves the geometric distortion problem of traditional digital elevation models in cliff regions by fusing geological prior knowledge, uses image recognition technology to extract the spatial orientation of rock layer interfaces and joint surfaces, and uses the spatial orientation as a hard constraint condition to construct a control triangular net framework, thereby avoiding the forced smoothing error of a regular grid DEM and the overhanging surface problem of an irregular triangular net, and through an adaptive triangular division algorithm, the rock layer structure, crack distribution and dangerous rock body shape of the cliff can be accurately restored.

The application discloses a three-dimensional space field prediction method and device based on a large model and data compression, equipment and a medium, and relates to the field of space field prediction. The method comprises the following steps: simulating to generate a dynamic three-dimensional space field data set of each irregular grid under different boundary conditions, mapping the irregular grid to a regular grid, and compressing the dynamic three-dimensional space field data by using a down-sampling method; constructing a training set according to the three-dimensional space field compressed data and the boundary conditions and the three-dimensional space field compressed data at a next historical moment, thereby training a large model pre-training network, the network combines a 3D convolutional neural network and an auto-encoder structure, and a three-dimensional space field prediction large model is obtained; and the model is applied to predict the three-dimensional space field distribution at a future moment. The application can accurately and efficiently predict a three-dimensional space field.

The invention relates to a space laser radar forest structure data correction method and system, and belongs to the technical field of space laser remote sensing and forest resource monitoring. Aiming at four kinds of errors of geometric positioning offset, slow distortion, terrain broadening effect and canopy structure influence of GEDI data, UAV control points are arranged by adopting a hierarchical arrangement strategy, a homonymy point relation is established through waveform registration, and weights are calculated; performing overall geometric correction based on the regular grid control points; carrying out local distortion correction based on the encryption control point; establishing a physical compensation model to compensate the terrain broadening effect; based on the canopy structure parameters and GEDI signal quality indexes, establishing a statistical regression model to correct a canopy height residual error; and finally, obtaining a high-precision canopy height convergence result through spatial smoothing processing, and outputting corrected data. The method achieves step-by-step precision improvement from the whole domain to the local domain and from the geometry to the height, and is low in cost, high in precision and wide in application range.

The invention discloses a neutral atmosphere refractive index calculation method and system suitable for different heights, and belongs to the technical field of communication and navigation. During modeling, monthly average reanalysis data is used as input to calculate the three-dimensional refractive index field of the neutral atmosphere, and horizontal, vertical and time domain change characteristics of the refractive index are represented by adopting a regular grid, a third-order index and a trigonometric function; when in use, the refractive index of any target point at any time within a global near-surface space range of 85 km can be calculated through space-time interpolation and elevation normalization only by giving the longitude, latitude, geodetic height and simplified Julian day of the target point. According to the method, the empirical modeling of the global neutral atmosphere refractive index field is realized by utilizing reanalysis data for the first time, the refractive index calculation precision at different height positions is improved through third-order index elevation normalization, and the method has important application value in the communication and navigation fields such as electromagnetic wave signal propagation path simulation and neutral atmosphere delay calculation correction.

The application provides a three-dimensional terrain generation method, device and system and a storage medium, and belongs to the field of image processing.The method comprises the following steps: constructing an encoder, a generator, a discriminator and a discriminator; encoding each original terrain map through the encoder to obtain an original latent space domain sample; and training each original terrain map and each original latent space domain sample through the encoder and the generator to obtain an original mapping terrain map and a mapping latent space domain sample.The application solves the problems of difficulty in predicting the generated terrain lacking user control, the need for a large number of operations and the appearance of regular grid-like artifacts in the generated terrain, does not require human participation, saves manpower and resources, can accurately capture a real structured conditional distribution and solves the problem of optimization cycle consistency obstacles.

The invention discloses a wind field quality control method based on a single moment image structure, which comprises the following steps of: converting original wind direction and wind speed data into U and V wind components, and interpolating the U and V wind components and wind direction site observation data into regular grid data; adopting a curvelet decomposition method to decompose the grid-processed wind field data into two parts, namely a main term and a remainder term taking random change as a main term; for U and V wind speed and wind direction data, calculating a spatial gradient of a target grid point by using the main item data after curvelet analysis, and judging that the grid point with the gradient greater than a preset gradient threshold value is abnormal; performing progressive quality control for multiple times to identify discontinuous abnormal values in the main item; after main term curvelet analysis is completed, curvelet decomposition is carried out to obtain remainder term data, an abnormal threshold value is set, and a wind field area is divided into a weak rotating wind area and a strong rotating wind area; the quality control method is suitable for high-intensity weather system influence.

The application discloses a fluid simulation method and system based on adaptive grid optimization, and belongs to the technical field of computational fluid dynamics, and comprises the following contents: receiving fluid state data at a current moment, state data at a historical moment and global physical parameters, performing scale alignment and normalization processing on the data and encapsulating the data as structured input; performing initial blocking on the whole calculation domain, converting original regular grid expression into a candidate unit set with hierarchical relationship; calculating physical indexes of each candidate unit based on fluid physical properties, judging whether each candidate unit needs to be refined, reserved or discarded; performing word tokenization and position coding on a multi-scale unit sequence, inputting the sequence into a neural solver to establish a long-range dependence relationship across regions, and outputting state word tokens at a next moment; and mapping the state word tokens back to an original regular grid space to generate a flow field simulation result. By using the method, accurate identification of a key region of a flow field and efficient modeling of multi-scale flow characteristics are realized.

The application provides a variable-grid three-dimensional longitudinal wave equation forward numerical simulation method, and the numerical simulation method comprises the following steps: S1, establishing an irregular grid division strategy; S2, under the irregular grid division strategy, constructing a regular grid function relationship in a Cartesian coordinate system; and S3, performing forward numerical simulation according to the regular grid function relationship. The method reduces the number of grid units and ensures the forward simulation precision, and realizes an efficient and high-precision variable-grid forward simulation method.

The present application relates to the technical field of marine engineering digital twin and three-dimensional visualization technology field, provide a kind of based on right triangle grid's dredging topography twin's generation method and system, comprising: obtaining regular grid elevation or sampling height data after pre-processing that have been unified to engineering plane coordinate system, determine the space range covered read space range and density parameter, based on space range and total row number and total column number of calculated grid;In the space covered, generate regularly arranged vertex, construct the topological structure of isosceles right triangle grid;With vertex as unit, several Chunk blocks are divided into global grid with fixed size, establish the triangular index mapping relationship of global row and Chunk block, the three vertices of isosceles right triangle and elevation or height data are filled in each Chunk block in parallel, generate local VBO, IBO and AABB;Batch rendering and coloring according to height color table are executed to all Chunk blocks, and the visualization of topography is realized.

The invention discloses a multi-source-driven CO2 concentration high-temporal-spatial-resolution prediction method based on a dynamic diffusion model, and the method integrates the satellite observation of OCO-2, GOSAT and the like, ERA5 meteorological data, vegetation index NDVI, population activity and other characteristics on the basis of DCRNN, and achieves high-precision prediction through physical prior and a dynamic graph structure. The method comprises the following steps: unifying multi-source data to a regular grid; an adjacent matrix is dynamically generated based on the geographic position and the wind field to serve as the input of the improved DCRNN, and the diffusion relation of COs in the wind direction is described; multi-source node features are input into the improved DCRNN, and physical constraints such as mass conservation and convection consistency are introduced to improve the reliability of a result; a graph-to-grid decoding and super-resolution technology is adopted to reconstruct prediction to a higher resolution level by level, and pixel-level uncertainty can be output. According to the method, multi-source observation and meteorological driving information are fully utilized, the satellite observation blank is effectively supplemented, the fineness and continuity of a COconcentration product are improved, and the method is suitable for carbon emission accounting, carbon source and sink evaluation and environmental decision support.

The invention provides a channel gain map reconstruction method based on a k-nearest neighbor refined neural network, relates to the technical field of wireless communication, and has the technical key points that the invention provides a two-stage CGM reconstruction framework under a sparse regular grid sampling condition, and in the stage 2, local learning is carried out during query to refine prediction, so that explicit decoupling and robust extrapolation are realized. K nearest neighbors are selected from a total sample by adopting a global k nearest neighbor thought which is not constrained by a clustering boundary, spatial continuity is preferentially utilized, and k nearest neighbors in a cluster which can be used as a contrast are selected only in the same cluster. The whole process does not depend on LoS / NLoS labels or high-cost environment prior, the CGM can be reconstructed only by regular grid sampling measurement, and high-precision benefits are kept under different sampling interval values d and k. On the premise of not increasing expensive measurement and label cost, the MSE of CGM reconstruction is obviously reduced.

The invention discloses a three-dimensional grid automatic filling method and device for unmanned aerial vehicle point cloud hole repairing, and the method comprises the steps: obtaining a point cloud data set, and dividing a point cloud coverage area into regular grid arrays with equal sizes according to a preset spatial resolution; mapping each laser point in the point cloud data set to a corresponding grid unit according to a plane coordinate of the laser point; traversing and counting the number of point clouds in each grid unit, marking the grid units of which the number of point clouds is smaller than a number threshold value as hole units, and combining adjacent hole units to form a hole area; for each cavity area, grid units of a preset number of adjacent layers are expanded outwards to form a continuous neighborhood, neighborhood features of the neighborhood are counted, and the neighborhood features represent the entity condition of a target area corresponding to a neighborhood grid; and selecting at least one filling strategy based on the area of each cavity area and the corresponding neighborhood features, and filling the grid attribute values of the cavity areas.

This invention relates to a method and system for optimizing coating trajectory to ensure uniformity of spacecraft coating thickness. The method includes: acquiring a model of the surface to be coated, generating a regular grid initial coating curve and setting constraint parameters; mapping the curve to a complex surface using a pseudo-projection algorithm, and generating a fully covered, non-intersecting initial trajectory after trajectory correction; based on an experimentally calibrated coating deposition model, constructing a multi-objective optimization function that minimizes coating thickness deviation while considering trajectory smoothness and operation time, using trajectory waypoint coordinates, coating gun attitude quaternions, and coating segment duration as optimization variables, and applying constraints such as coating distance, velocity, and attitude; using an interior-point solver for iterative optimization, limiting variable iteration deviations to ensure model accuracy; and outputting an directly executable optimized trajectory. This invention can automatically adapt to the coating requirements of complex surfaces, significantly improve coating thickness uniformity, control deviations within the allowable range of aerospace processes, and effectively improve operational accuracy and efficiency.

The invention discloses a scanning magnet beam calibration method and related equipment, and relates to the technical field of radiotherapy, and the method comprises the steps: selecting a plurality of feature points in a target radiation field range, and enabling the feature points to jointly form a regular grid covering the radiation field; the regular grid comprises at least one grid unit; for each feature point, obtaining a current value pair of the feature point which enables the deviation between the actual position and the theoretical position of the beam to be within a preset range; and for any target point in the radiation field, according to the current value pairs of the feature points, the control current of the target point is calculated through a bilinear interpolation algorithm, and high-precision and high-uniformity beam calibration of the whole field of the scanning magnet is rapidly achieved by combining a small amount of precise measurement with intelligent interpolation calculation.

In various examples, optimized cluster templates (e.g., template triblock data, template CLASes or some portion thereof such as template range data, etc.) are precomputed for various patterns of triangle clusters (e.g., regular grids and / or irregular meshes of various edge resolutions) and corresponding compression levels. For example, optimized range assignments may be computed by iteratively generating candidate range assignments using different strategies, evaluating each range assignment using a designated metric (e.g., a cost that estimates, models, approximates, or otherwise quantifies the anticipated time cost of traversal), and tracking the best (e.g., optimized) range assignment (or top N) for each optimized triblock layout. As such, a range assignment may be iteratively optimized for each supported pattern of triangles and corresponding compression level, and may be used to generate a corresponding cluster template.