54 results about "Multidimensional visualization" patented technology

A water pollution risk early warning and tracing method based on multi-source data fusion belongs to the technical field of water pollution monitoring and early warning, and comprises the following steps: step 1, constructing a multi-source heterogeneous data acquisition network and realizing real-time data transmission; 2, performing multi-source data fusion and feature enhancement processing based on space-time reference; 3, constructing a water pollution risk dynamic early warning system based on a WOA-LSSVM model; fourthly, reverse positioning of the pollution source is completed on the basis of a CNN-GRU-SE Attention model; and 5, carrying out development and emergency response on a multi-dimensional visual decision support system, and positioning a pollution source. Multi-source information such as water quality sensor data, unmanned aerial vehicle image data and geographic information data is fused, and an intelligent monitoring network is constructed; through multi-source data fusion and an intelligent algorithm, water pollution risk early warning accuracy and traceability efficiency are effectively improved, and the method has the advantages of high response speed, wide monitoring range, accurate positioning and the like, can be widely applied to the fields of urban water supply, drainage basin management and the like, and meets the requirements of water environment safety guarantee.

The invention discloses a wind-solar complementary energy storage direct current charging method and system based on liquid cooling heat dissipation, and relates to the technical field of energy storage charging. Comprising the following steps: S1, collecting wind-solar complementary energy storage data in real time, and carrying out data preprocessing; s2, converting wind-solar power generation into direct current, judging the flow direction of wind-solar power generation energy, and performing corresponding wind-solar power generation energy transmission power supply; s3, judging the limit of the output power of the charging pile, and controlling and adjusting the output of the charging pile in stages; s4, quantifying the liquid cooling flow required by heat dissipation, and performing heat source heat dissipation on the energy storage system and the charging pile; and S5, carrying out coordinated regulation and control, strategy optimization and multi-dimensional visualization on the flow direction of wind and light power generation energy, charging pile output and heat source heat dissipation. The problems that an existing charging station is difficult to deploy in remote and power transmission difficult areas, high-power charging heat dissipation and energy efficiency bottlenecks are prominent, and the efficiency of traditional air cooling and alternating current conversion is low, so that efficient, safe and green energy supplementation is difficult to achieve are solved.

The invention provides a medical image visualization analysis system based on deep learning, and relates to the field of artificial intelligence. The objective of the invention is to overcome the defects of an existing system in the aspects of deep learning model interpretability, clinical interactivity and multi-modal data fusion. The system comprises an image data acquisition and standardization module, a deep feature extraction and representation learning module, a multi-task intelligent analysis module, an interpretability analysis module, a multi-dimensional visualization and interaction module, a clinical knowledge fusion and feedback learning module and a system management and integration module. Through the system, the diagnosis efficiency and accuracy can be improved, the trust of doctors is enhanced, the obstacle of a traditional black box model is overcome, and a new man-machine cooperation intelligent diagnosis normal form is constructed.

The invention discloses a power load time sequence anomaly detection method and system based on a Mama and LSTM hybrid network, and belongs to the technical field of power system data analysis and artificial intelligence, and the method comprises the steps: inputting the preprocessed power load and related factor time sequence data into a Mama-LSTM hybrid encoder; performing time sequence data reconstruction and anomaly probability prediction in parallel by using depth features output by an encoder, and performing model training by jointly optimizing reconstruction error loss and anomaly detection loss; calculating a comprehensive abnormal score based on the trained model, and judging an abnormal point by adopting a dynamic threshold value; and outputting an anomaly detection result and providing an analysis report containing an unsupervised evaluation index and multi-dimensional visualization. Through deep series fusion of Mama and LSTM, long-term dependence and complex modes in a power load sequence are effectively captured, and the accuracy, robustness and interpretability of anomaly detection are significantly improved in combination with a joint training strategy and an unsupervised evaluation system of the system.

The invention discloses a natural resource asset checking management system and method based on a cross-platform architecture, and relates to the technical field of resource management, and the system comprises a cross-platform adaptive architecture module, a real-time data synchronization and verification module and an intelligent analysis and multi-dimensional visualization module. The cross-platform adaptive architecture module carries out fragmentation preprocessing on collected data through a uniform interface abstraction layer, a dynamic adaptation layer, a cross-platform rendering engine and a platform difference compensation mechanism and the real-time data synchronization and verification module, and the transmission efficiency is optimized through multi-link transmission and dynamic path selection. And the timeliness and accuracy of data synchronization are ensured in combination with block chain hash check and conflict detection. According to the system, through cross-platform adaptation, efficient data synchronization and intelligent visual analysis, the efficiency and scientificity of natural resource asset checking management are remarkably improved.

The invention discloses a VR panoramic flood disaster analysis method and system combining a knowledge graph and a visual large model, belongs to the technical field of disaster information intelligent analysis, and particularly relates to technologies such as virtual reality panoramic images, knowledge graphs and visual large models. The method is suitable for automatic extraction, structured analysis and visual expression of disaster information in a flood scene, and solves the problems that in the prior art, a unified disaster information recognition rule is lacked, accurate extraction and spatial mapping of disaster parameters and scene objects are affected, and automatic recognition and dynamic labeling of flood disaster elements of VR panoramic images cannot be achieved. According to the method, a vertical vision large model of a flood disaster scene constrained by a knowledge graph is constructed and trained; and performing automatic identification and risk labeling on disaster information in the preprocessed VR panoramic image based on the trained vertical vision large model, and performing multi-dimensional visualization after labeling. The method is used for VR panoramic flood disaster analysis.

The invention discloses an RAG and knowledge graph question-answering method and system for security classification and grading of cross-border data, and belongs to the crossing field of big data security management, artificial intelligence and compliance technologies. The method comprises the following steps: step S101, receiving and preprocessing user input; step S102, performing question analysis and semantic intention recognition; step S103, intelligent scheduling control decision making; step S104, reasoning and executing the knowledge graph; step S105, performing RAG generation reasoning execution; step S106, performing intelligent fusion and decision traceability; step S107, carrying out multi-dimensional visual display; step S108, audit record and report generation; and S109, updating the dynamic knowledge. The method has the advantages of intelligent question and answer, multi-source fusion, sustainable evolution, traceability of the whole process and the like, and can be widely applied to compliance management and intelligent decision-making scenes related to data cross-border flow, such as enterprises, governments, finance, medical treatment and the like.

The invention relates to the technical field of building intelligent management and operation control, and discloses a solid building data visualization and simulation analysis system, which is characterized in that dynamic monitoring data is acquired by constructing a building three-dimensional model and deploying multiple types of sensors, and a tensor structure is generated through standardization and three-dimensional index fusion; mapping the tensor into a three-dimensional model to realize regional data visualization; historical sequence modeling and strategy-driven future simulation prediction are carried out based on a sliding window; a user can control system behaviors through model interaction, the system automatically monitors index changes and triggers strategy simulation and visual dynamic updating in a linkage mode, and visual analysis and intelligent response control of the building state are achieved. Through fusion of three-dimensional model mapping, tensor construction and strategy response prediction, building state multi-dimensional visualization, continuous intelligent prediction and dynamic feedback control are realized, and innovative technologies such as sliding window modeling and interactive strategy driving are provided.

The invention relates to the technical field of distributed electric energy, in particular to a distributed electric energy electricity consumption summary settlement system, which comprises an electricity consumption data acquisition module, a multi-source heterogeneous data processing module, a dynamic verification module, a cross-regional settlement module, a block chain evidence storage module and a visual interaction module. By configuring a multi-channel acquisition circuit, parallel acquisition of power utilization characteristic data of distributed energy nodes is realized; performing cross-protocol fusion and noise reduction on the received data, and endowing credibility weight; finishing verification of timestamp precision + / -1ms by using a block chain intelligent contract mechanism; dynamically adjusting settlement parameters according to the verification weight, and generating a dynamic settlement list in combination with an electricity price gradient model; hash evidence storage is carried out through the alliance chain node, finally, multi-dimensional visual rendering is completed in combination with an evidence storage result, and a traceable and auditing settlement report is generated. The system has the advantages of data fusion intelligence, settlement result credibility, account book record compliance and report interaction transparency.

The invention relates to an electric power resource adjustability resource multi-dimensional analysis and visualization method, which comprises the following steps of: selecting four dimensions of response time, service time, adjustable capacity and credibility in electric power resource adjustability characteristic indexes as a rating system, and drawing an electric power adjustability resource adjustability characteristic radar map; and constructing a power adjustable resource characteristic cube by taking the power adjustable resource adjustment characteristic radar map as a bottom surface and taking the corresponding scale capacity as a high surface to represent the adjustable characteristic characteristics of the source network load power resources. Compared with the prior art, the multi-dimensional visualization of the adjustment performance of the power adjustable resource is realized by constructing the characteristic cube, the adjustable characteristic characteristics of the source network load power resource can be comprehensively and accurately represented, and a large number of, multiple and dispersed flexible resources can be aggregated to participate in system adjustment.

Systems and methods are disclosed for multidimensional visualization of data and using the visualization in any of a number of applications to result in visualization configurations usable for a variety of purposes. The system includes one or more processors, one or more databases, at least one graphical user interface (GUI), and control technology for a user to control a display, where the display typically is visualizable through the GUI.

A method and a system for online integrated environmental monitoring, assessment, and impact visualization of projects are disclosed. The method includes receiving project site data representing the geographical boundary of a project in a virtual environment and collecting real-world environmental data from fixed and mobile monitoring devices. Model data, modeling parameters, and digital ground data associated with the project are retrieved and unified through a unified connector interface to form a unified input data. The unified input data is processed through one or more impact modeling entities to assess environmental impacts, including air quality, noise, water quality, and ecological effects. Visualizations of the environmental impact determined are transmitted to an environmental assessment planner interface for display. The method and the system provide for real-time integration, efficient impact modeling, and multi-dimensional visualization, enabling stakeholders to evaluate and monitor environmental effects with enhanced precision and accessibility in a seamless digital environment.

The invention relates to the field of intelligent data management and analysis, in particular to a multi-dimensional data integrated work file tracing method and system. The method comprises the following steps: acquiring work file data; extracting a first archive feature, a second archive feature and a third archive feature; obtaining a tracing path and a confidence score; judging a first-level condition, a second-level condition and a third-level condition; and in combination with an improved space-time coupling multi-dimensional visualization technology, starting a tracing optimization process, and realizing tracing of the work file. According to the method, through multi-source data fusion and feature extraction, entity association, time sequence abnormity and dynamic risks are accurately quantified; by constructing a multi-dimensional model for comprehensively evaluating the reliability of a tracing path and combining a three-level intelligent judgment and self-adaptive optimization mechanism, the accuracy and the service fitting degree of a tracing result are remarkably improved; through visual presentation and knowledge precipitation, full-link intelligent tracing of the work file is realized, and efficient decision support is provided for safety audit and risk management and control.

The invention relates to the technical field of intelligent investment advisers, and discloses an intelligent investment adviser interaction and asset allocation visual decision-making system based on augmented reality, and the system comprises an augmented reality display device; the user interaction module is used for capturing an input instruction of a user; a data acquisition module; intelligent investment advisor and commissioning; a visualization processing unit; a decision execution module; a system control center; a user identity authentication module; a data storage module; a network communication module; and a calculation acceleration module. According to the intelligent investment adviser interaction and asset allocation visual decision-making system based on augmented reality, by integrating augmented reality display equipment and a multi-dimensional visual processing unit, an abstract asset allocation scheme, a market trend and risk information are overlaid in a real environment in visual forms such as a three-dimensional hologram and a spectrogram; the understanding efficiency and decision immersion of the user on the complex financial data are remarkably improved, and the problems that traditional two-dimensional interface information is not visual in presentation and poor in interaction experience are solved.

The invention discloses a Python-based power transmission line electromagnetic field finite element automatic modeling and analysis method in the field of electromagnetic field finite element simulation and power system analysis. A Python script language is combined with a finite element calculation engine, information is analyzed through programming, and the precise spatial position of each hanging point of the power transmission line in a global coordinate system is obtained through automatic conversion of coordinates; based on the obtained parameters, script programming is used for completing three-dimensional geometric modeling of the wire, and then automatic modeling and parameterized definition are achieved; then, script programming is used for achieving calculation domain setting, boundary condition setting, voltage and current giving, phase sequence setting and other setting of a line section to be calculated, and three-dimensional finite element simulation calculation of an alternating current electric field and a magnetic field of the designated line section is completed; and performing multi-dimensional visual display on the electric field and magnetic induction intensity in combination with a Python visual library. According to the system, automatic processing from GIM data to an electromagnetic field calculation result is achieved, electromagnetic field calculation of complex lines such as mixed voltage and cross crossing can be completed, modeling efficiency and calculation precision are remarkably improved, and an efficient simulation means is provided for electromagnetic environment evaluation and equipment optimization arrangement of the power transmission line.

This invention discloses a DC charging method and system for wind-solar hybrid energy storage based on liquid cooling, relating to the field of energy storage charging technology. It includes the following steps: S1, real-time acquisition of wind-solar hybrid energy storage data and data preprocessing; S2, conversion of wind and solar power into DC power, determination of the energy flow direction, and corresponding energy transmission and power supply; S3, determination of the charging pile's output power limit, and phased control and adjustment of the charging pile's output; S4, quantification of the liquid cooling flow required for heat dissipation, providing heat source cooling for the energy storage system and charging pile; S5, coordinated control, strategy optimization, and multi-dimensional visualization of the wind and solar energy flow direction, charging pile output, and heat source cooling. This solves the problems of difficult deployment of existing charging stations in remote and power transmission-difficult areas, prominent bottlenecks in heat dissipation and energy efficiency for high-power charging, and low efficiency of traditional wind cooling and AC conversion, which hinder efficient, safe, and green energy replenishment.

The application discloses a data simulation method based on data visualization, and relates to the technical field of data analysis, comprising: constructing a distributed stream processing framework, performing parallel preprocessing on a target data set to be simulated to generate a time sequence characteristic stream; converting the time sequence characteristic stream into a multi-dimensional visualization model through an adaptive mapping layer, and realizing dynamic rendering in a visualization interface; triggering a simulation engine to execute real-time simulation based on the multi-dimensional visualization model, and jointly optimizing the visualization parameters and the simulation parameters through a feedback optimization mechanism. Through the introduction of a dynamic calculation method of the job level correlation coefficient and the space-time overlap degree, the design of the time-varying adjustment factor and the hierarchical attention mechanism, and the construction of a novel data processing and visualization framework, the application realizes the accurate identification of the talent development path across different levels, the timeliness optimization of data preprocessing, and the effective sharing of the best practices among departments.

The invention relates to the technical field of building energy consumption monitoring, and discloses an industrial building operation stage energy consumption monitoring system and method.The system comprises a data acquisition layer, a data processing and storage layer, an energy consumption analysis layer and an application layer which are electrically connected in sequence; the data acquisition layer acquires total energy consumption, environmental parameters and production activity data, the processing layer realizes data cleaning, quality closed-loop management and space-time alignment storage, the analysis layer constructs a dynamic energy consumption reference model containing an equipment aging coefficient, calculates a two-dimensional production intensity coefficient, completes energy consumption double-layer decomposition and normalized energy efficiency evaluation, and performs energy consumption analysis and energy efficiency evaluation. The application layer realizes multi-dimensional visualization, intelligent report generation and graded alarm. The method is executed according to the steps of data acquisition, processing, modeling, coefficient calculation, energy consumption decomposition, energy efficiency evaluation and application display. According to the method, the problems of energy consumption and production coupling deficiency, reference static state and the like are solved, objective energy efficiency evaluation and accurate energy consumption positioning are realized, and support is provided for industrial building energy saving.

This invention relates to the field of data visualization technology, and provides a method and system for visualizing operation and maintenance data based on smart grids. This method aims to improve the efficiency and intelligence of power grid operation and maintenance visualization, thereby enhancing the timeliness of power grid operation and maintenance decision-making and management. The method includes: real-time acquisition of multi-source heterogeneous operation and maintenance data sets from the smart grid; cross-modal cleaning and time alignment processing of the operation and maintenance data sets to generate a preprocessed data set; dynamic feature fusion and correlation analysis of the preprocessed data set to generate a set of equipment status features and a set of equipment-environment interaction features; generation of an interactive visualization element set based on the set of equipment status features and the set of equipment-environment interaction features through a multi-dimensional visualization strategy; dynamic rendering and layout optimization of the interactive visualization element set to output a real-time updated power grid operation and maintenance visualization interface; and configuration of a user operation priority response mechanism for handling interaction conflicts within the power grid operation and maintenance visualization interface.

The invention discloses a vehicle track perception and analysis system based on MR data of vehicle-mounted communication equipment, which comprises a data processing module and a visual display module, and is characterized in that the data processing module is used for access, analysis, analysis and track generation of the MR data of the vehicle-mounted communication equipment; the visual display module is used for multi-dimensional visual display of the vehicle track and the network quality, and the data processing module and the visual display module work cooperatively to realize high-precision perception of the vehicle track and deep analysis of the network quality; the data processing module comprises an MR data access unit, an MR cleaning and latitude and longitude backfilling unit, a vehicle state identification unit, a track smoothing and denoising processing unit, a road adsorption and track generation unit and an output structured track unit, and has the capabilities of high-precision track restoration, network quality fusion display and intelligent segmentation identification; the method can effectively support fault positioning and user experience analysis in the operation and maintenance scene of the Internet of Vehicles, and has the advantages of high automation degree, high positioning precision, friendly visual interaction and the like.

The invention discloses an artificial intelligence-based natural disaster damage intelligent assessment method and system. The method comprises the following steps of: acquiring a restoration period image and a disaster sensitive factor through a satellite remote sensing technology; performing land utilization type intelligent interpretation and generating a grid map layer, and automatically extracting geological disaster stress factors at the same time; innovatively coupling an InVEST ecological environment quality evaluation model and an AI disaster loss evaluation engine, synchronously calculating an ecological environment quality index and a disaster loss risk index, and generating an ecological quality thermodynamic diagram and a disaster sensitivity dynamic map; analyzing an evolvement rule of an ecological quality spatial pattern by adopting a space-time diagram convolutional network, and quantifying a synergistic effect in combination with a natural disaster damage degree-disaster resistance incidence matrix; and finally, multi-dimensional visual deduction of the natural disaster damage degree and the disaster resistance capability is realized on a three-dimensional digital twinborn platform, and an ecological restoration-disaster toughness double-target intelligent evaluation closed loop is formed.

The invention discloses a fund transaction service quality evaluation method and device, a storage medium and a computer program product, and relates to the technical field of financial information processing, and the method comprises the steps: collecting full-link log burying point data; inputting the full-link log burying point data into a pre-constructed systematized scoring model to carry out service quality weighted scoring so as to obtain a multi-dimensional service quality score value; and processing the multi-dimensional service quality score value to obtain multi-dimensional visual evaluation data, and quantifying the fund transaction service quality according to the multi-dimensional visual evaluation data. Real-time and accurate quantitative evaluation of fund transaction service quality is realized through full-link log burying point data acquisition, service quality weighted scoring by a systematic scoring model, and multi-dimensional visual evaluation data processing and display.

The invention relates to the technical field of engineering construction safety monitoring, and particularly discloses a tall and large formwork support attitude sensing system, which is characterized in that support deformation and stress parameters are synchronously acquired through a distributed intelligent sensor array, and a mixed monitoring sequence is generated; performing data purification and confidence enhancement processing on the sequence to generate a unified state vector; inputting the vector into the digital twin body for real-time response matching, and dynamically correcting and reconstructing a three-dimensional deformation field and an internal force distribution map through parameters; analyzing a structure evolution trajectory based on the atlas, predicting a stability attenuation trend and a bearing boundary, and outputting a time-varying safety index; and when the indexes break through the self-adaptive early warning boundary, graded alarm is automatically triggered, a risk positioning report is generated, and a safety state and a disposal scheme are dynamically displayed through a multi-dimensional visual platform.

The invention relates to the technical field of land resource management, and discloses a data integration and utilization management system based on land surveying and mapping, the system comprises a governance module, a storage module and an access module, the governance module integrates multi-source land surveying and mapping data by constructing a fused data recording structure; the storage module stores the integrated data to a corresponding database system according to the data type, constructs a multi-level index to improve the retrieval efficiency, and generates a multi-dimensional visual view at the same time; and the access module carries out authority verification and security control based on role and business process stages to ensure the security and compliance of data access. According to the method, standardized integration, efficient storage and rapid retrieval of multi-source data are realized, the data security management level is improved, multi-dimensional visual display is supported, and the efficiency and accuracy of land resource management are effectively improved.

The invention discloses a data-driven updating method for a digital twin during simulation operation. The data-driven updating method comprises the following steps: step S1, a data access and preprocessing step; s2, a state updating and driving step; step S3, a multi-dimensional visual rendering step; s4, a simulation behavior verification and feedback step; s5, a dynamic evaluation and report generation step; step S6, a multi-person collaborative synchronization step; and S7, a simulation process backtracking and replaying step. According to the method, real-time access and fusion of multi-source heterogeneous data are realized, state updating of digital twin driven by multi-dimensional data such as a sensor, a service system and a simulation model is supported, and the real-time performance and data integrity of a simulation system are improved; through high-precision collision detection, a physical engine and a state synchronization mechanism, the behavior authenticity and consistency of the digital twin in scenes of interactive operation, fault simulation, multi-person cooperation and the like are guaranteed.

The application discloses a multi-dimensional visualization method, system and program product for a three-dimensional integrated circuit, comprising obtaining configuration parameters of the three-dimensional integrated circuit, constructing a three-dimensional model of each layout layer and stacking according to a stacking order determined by a first plane distribution and attribute parameters, and constructing a three-dimensional model of each layout unit, thereby forming a three-dimensional model of the three-dimensional integrated circuit; dividing clusters and calculating a spatial distance between each cluster and a current position of a virtual camera; and rendering the three-dimensional model of the three-dimensional integrated circuit based on the spatial distance, a rendering color parameter, the first plane distribution and attribute parameters and a second plane distribution and attribute parameters, to generate a visual display image of the three-dimensional integrated circuit. Designers can directly observe the structure of the three-dimensional integrated circuit in a three-dimensional space, without repeatedly switching between multiple two-dimensional views and manually comparing, thereby greatly reducing the time required for spatial imagination and improving the efficiency of design review and analysis.

A method includes receiving raw input signals corresponding to a duration of time, analyzing the signals using a trained coding architecture to generate embedded features, and displaying, via a graphical user interface, a visualization of the embedded features corresponding to the patient conditions. Another method includes receiving raw input signals, automatically generating embedded features corresponding to the signals' reduced dimensionality representation, and displaying multi-dimensional visualizations of the features to allow diagnosticians to analyze meaningful visual separation of conditions. A method also identifies noise in signals by receiving signals, generating embedded features, reconstructing signals from embedded features using a decoder, calculating an error between received and reconstructed signals, and determining noise levels by analyzing the error, with larger discrepancies indicating higher noise levels.

The invention discloses an integrated multi-dimensional visualization intelligent maintenance value evaluation and interaction system and method, and relates to the technical field of health and predictive maintenance, and the system comprises a state prediction module which is used for obtaining a health state prediction result of each device; the central monitoring board is used for generating an equipment health state display diagram based on the health state prediction result by taking a layout diagram of the industrial system as a base diagram; the energy efficiency optimization module is used for adjusting operation parameters of corresponding equipment; the decision support module is used for generating at least one quantitative decision corresponding to the equipment when the health state prediction result is that the equipment fails; the augmented reality module is used for superposing and displaying the equipment information and the health state prediction result of the equipment on the equipment of the industrial system based on an augmented reality technology; and the calculation tracking module is used for calculating the return on investment of the industrial system after each fault early warning. The technical problem of low information transmission efficiency in the prior art is relieved.

This invention provides a method, apparatus, equipment, and storage medium for accurate identification and evaluation of bitter gourd skin color, belonging to the field of fruit skin color identification technology. The method includes: acquiring fruit images; extracting color features from the fruit images using ImageJ software to construct an original sequence dataset; cleaning and organizing the original sequence dataset using the tidyverse package; exploring the data using a multi-dimensional visualization method; optimizing the color center coordinates using a K-means clustering algorithm combined with the CIE 1976 ΔE formula; introducing an LSTM model to model the bitter gourd skin color data; and analyzing the skin color classification results using the LSTM model and outputting the analysis results. By using bitter gourd fruit images collected under field conditions as the research object, a skin color quantification dataset based on the CIE Lab color space is constructed to establish an objective, repeatable, and biologically significant accurate identification and evaluation system for bitter gourd skin color, thereby improving the accuracy of bitter gourd skin color identification and providing technical support for bitter gourd germplasm resource identification and breeding applications.

A mechanism to show how code is operating with different sets of input. After accessing the code that is to be evaluated along with the multiple input sets for that code, the computing system generates a multi-dimensional array of values. This is done by, for each of at least some of the multiple input sets, generating a corresponding intermediate value set of one or more intermediate values that are generated as the code operates upon the corresponding input set to generate a corresponding output value set. Then, the computing system causes a multi-dimensional array of values to be visualized using a multi-dimensional representation. In this multi-dimensional visualization, input sets are represented in at least one dimension against at least one intermediate value of the corresponding intermediate value set in at least another dimension.