34 results about "Python language" patented technology

The invention discloses an automatic administrative boundary fusion charting method and a meteorological charting method based on a python language. Belongs to the technical field of meteorological charting, and particularly relates to the cross technical field of meteorological data processing and geographic information system visualization. The method starts with the construction of a multi-scale adaptive boundary fusion map, so as to solve the problems of cross-scale (such as province-to-village) precision faults and large interpolation errors of complex terrains, and achieve a cross-level administrative division boundary seamless aggregation technology (village level-town level-county level-province level). Therefore, the problem that precision is easy to lose when cross-scale conversion (such as from province to village) is carried out during meteorological mapping is solved.

The invention belongs to the technical field of single-cell multi-omics, and discloses a single-cell multi-omics data analysis system, method and device and a storage medium, a data import module is used for reading sequencing data from different sequencing platforms and storing the sequencing data as S4 objects; the cross-language analysis module is used for calling a single-cell multi-omics analysis tool based on an R language and a Python language to analyze an S4 object according to an analysis process in a unified framework; the deep learning optimization module is used for training a deep learning model based on the cross-language interaction interface and integrating an analysis result of the deep learning model to an object S4; and the interaction and extension module is used for obtaining an analysis process and visualizing an analysis result, constructing a user-defined single-cell multi-omics analysis tool in a plug-in form and loading the tool to the S4 object for analysis. Cross-sequencing platform data compatibility, multi-language tool seamless integration and deep learning framework efficient access are achieved, and the problems of data isomerism, language ecological splitting and algorithm expansibility in the prior art are solved.

The invention discloses an MJS reinforcement parameter optimization method based on finite element-neural network integration. The method comprises the following steps: firstly, constructing a finite element automatic modeling script system based on an ABAQUS platform, taking geological parameters and reinforcement preliminary design parameters of a construction area as input initial codes of automatic modeling, and then modifying different corresponding reinforcement parameters in the codes to realize parameterized modeling and batch model generation; reading and formatting strength and deformation results in a. Odb file output by a calculation result of the ABAQUS platform by utilizing Python, and fusing the strength and deformation results with on-site deformation monitoring data to form a unified database; then, constructing a forward modeling / inversion model based on PINNs by utilizing a Python language; performing preliminary prediction on site deformation by using the forward modeling model; continuously optimizing and updating the reinforcement design target parameters through the inversion model; and finally, comprehensively deciding and determining a foundation reinforcement parameter combination according to the calculation result of the forward / inversion model.

The invention relates to a fishing boat meteorological route planning system, and belongs to the field of meteorological route planning system construction. The system takes a layered structure as a main framework and is sequentially divided into a data source layer, a data processing layer, a supporting layer, an interaction layer, a front-end UI layer and an access layer from bottom to top; in the design of a front-end page, a Vue framework is adopted, Jave and Python languages are adopted for back-end codes, and a PostgreSQL database is adopted for a database end. And finally, the sea condition meteorological data and the course planning process and result are displayed on a front-end page of the system, and the data can also be transmitted to an Internet of Things platform to be displayed.

The application provides a method for calculating the abundance of a fission product nuclear decay process. According to the characteristics of the decay differential equation, only the decay process is considered for n fission product nuclei, the differential equation set for the abundance change is represented by a matrix, a program is written by using Python language to solve it, and the result of the abundance change of the fission product nuclei with time is obtained. The method has simple program design, less input data types, and fast speed, and can quickly obtain the abundance data of the fission product nuclear decay process. In the case of a processor i5-1155G7@2.50GHz, the time consumption is less than 1 second, which is much faster than similar programs.

The application discloses a scientific paper influence evaluation method and system based on adaptive exceeding index. The application sets four modules, namely, a paper theme determination module, a real-time retrieval module, an adaptive exceeding index calculation module and a visual output module. The paper theme determination module analyzes a given paper title and abstract based on a large language model to obtain one or more paper themes. The real-time retrieval module obtains relevant data of the paper from a publicly available database according to the obtained paper theme. The adaptive exceeding index calculation module calculates the adaptive exceeding index of the specified paper according to the returned relevant data. The visual output module uses Python language to real-time render a PDF file with pictures and texts and a neat interface according to the previously obtained and calculated paper relevant data.

The application discloses an integrated visual intelligent platform of WisdomStore local deployment under a brain-like technology, and the platform main body is composed of a user interface layer, a basic service layer, a language framework layer and a bottom service layer; the user interface layer comprises four modules, namely, a data labeling interface, a model training interface, a model reasoning section and a result display interface; the basic service layer comprises two modules, namely, data processing and model management; the language framework layer is based on a Python language and an ecological system thereof; and the bottom service layer combines public data sets and internal customized data sets in the data source part. The application improves the intelligent level of the industry, improves market competitiveness, promotes digital transformation and promotes scientific and technological innovation.

The application discloses a kind of batch fast creation pile foundation model and batch parameter assignment method and system programmed using Python language, and its method includes: S1: extracting the parameter data required for modeling from pile foundation CAD design drawing, and collating to form standardized data table;S2: using Python language and its pandas data processing library, write the data matching and structured script of pile foundation;S3: in the Dynamo visual programming environment of Revit platform, construct Dynamo node package, and node package is used to define the creation rule and parameter assignment logic of pile foundation model;S4: run Dynamo node package in Revit project file, use intermediate file as the input data of Dynamo node package, automatically batch create pile foundation model and give each pile foundation model corresponding parameter.The application innovatively uses Python space index grid algorithm, realizes the automatic accurate matching of pile foundation center circle graphics and numbered text in CAD drawing, solves the problem of artificial checking of massive pile foundation data.

The invention relates to a driver monitoring system test evaluation method based on a simulation robot. Comprising the following steps: step 1, constructing a simulation robot for a DMS test; 2, designing a DMS test simulation robot control system; step 3, establishing a DMS system; step 4, generating and evaluating a test case; according to the method, firstly, a simulation robot used for DMS testing is constructed, then a steering engine is selected and arranged, and fine control over fatigue actions of the simulation robot is achieved through control of a microcontroller; a python language is used as a development basis, modular design is adopted, eye detection, head posture estimation, attention evaluation, parameter configuration, a camera interface and the like are included, and a detected DMS system is deployed; and finally, based on the national standard and the actual driving behavior, generating an efficient and high-coverage test case set by adopting a combined test theory, and executing through a control system, so that the problems of low efficiency, high cost, uncontrollable action, insufficient scene coverage, lack of a standardized evaluation system and the like of the existing DMS test method are solved.

The application discloses a flood evolution analysis method based on instant compiling technology, mainly comprising the following steps: setting a hardware acceleration environment, specifying a calculation time and an iteration step length, loading a grid topological structure, an initial water level and an initial flow velocity, a grid roughness field and model boundary conditions, optimizing codes of a finite volume method and a HLLC shallow water equation solving algorithm based on instant compiling technology, and realizing parallel acceleration simulation of flood evolution. The method is written in Python language with strong interpretability to compile shallow water equation solving codes, and machine codes are generated by instant compiling technology during runtime to greatly improve code running efficiency. Different hardware platforms such as CPU, GPU or CUDA can be selected to perform parallel acceleration solving on the shallow water equation, simple and efficient simulation of flood evolution is realized, and the method has the advantages of strong code readability and high performance.

The application discloses a tooth surface modification optimization method of a two-stage reduction gear system based on an NSGA-II algorithm, and comprises the following steps: establishing a two-stage reducer gear system model according to an actual structure; determining multiple typical working conditions of the two-stage reducer gear system; determining a modification method; establishing a multi-objective optimization mathematical model with the minimum peak-peak value of load transmission error under multiple working conditions as an objective function; based on the NSGA-II algorithm, using a secondary development interface of professional gear analysis software, using a Python language to compile an optimization program, respectively optimizing tooth surface modification parameters of a first-stage reduction gear pair and a second-stage reduction gear pair, and obtaining respective Pareto optimal solution sets; selecting a tooth surface modification optimization scheme in the Pareto optimal solution set, and completing tooth surface modification optimization work. The application combines the NSGA-II multi-objective genetic algorithm with professional gear analysis software, and provides an optimization method with stronger optimization ability and more rapid and accurate optimization for tooth surface modification optimization work under multiple working conditions.

The application relates to a target detection algorithm test method and system based on a python language, and the method comprises the following steps: S1, a step of preparing test data, preparing a test picture needing target detection, and labeling the test picture to generate an xml file of corresponding coordinate points; S2, a step of uploading the test picture to an algorithm interface to obtain response data; S3, a step of reading xml labeling file data, drawing a green rectangular frame in the test picture by reading rectangular frame coordinate point data; writing the rectangular frame coordinate point data into a txt file and saving the txt file to a groundtruths expected result directory; S4, a step of saving test picture classification; S5, a step of counting test results; S6, a step of automatically sending an email, generating a test report after the test is completed, and the test report showing test case execution results; and automatically sending an email after the test is completed, wherein the email content comprises test description information and a test report, and the email is sent to a test person in charge.

The application discloses an industrial system mechanism modeling simulation platform, a unified system modeling simulation code system is constructed based on a Python language, a system identification model function library is constructed based on AI technology, and a dynamic model of a complex industrial system or equipment is identified through industrial big data; a general system modeling simulation environment is provided, a linear dynamic system and an artificial intelligence nonlinear dynamic model are incorporated into a unified modeling simulation system, visual combination modeling and industrial system simulation are carried out, and identification modeling simulation integration is supported; and the application is used for industrial system identification modeling simulation technology required by industrial internet and industrial intelligent construction, and provides a reliable system model for design of a high-end controller.

The present invention discloses a parameterized modeling method for the in-bore motion of rifled guns. First, within the Python language framework, the idea of ​​fragmentation and splicing is employed, combined with the structural parameters of the rifled gun barrel, to calculate the three-dimensional spatial coordinates of each node. The nodes are then connected in numerical order to generate a finite element model file for the rifled gun barrel. Then, based on the body-of-revolution characteristics of the projectile belt, a three-dimensional geometric model of the projectile and belt is established and meshed in ABAQUS software. The generated finite element model file for the rifled gun barrel is imported, and materials are assigned to each component involved in the calculation of the in-bore motion of the gun. Assembly, analysis step creation, contact definition, load and constraint setting are sequentially performed to create a job. The execution log file is retrieved, the key operation step codes are retained, and parameters related to the projectile belt structure are replaced with variables. Finally, the RSG dialog box builder is used to create a GUI plug-in for generating the rifled gun barrel and projectile belt, respectively, and performing pre-processing. The present invention greatly improves the efficiency of modeling and pre-processing by enabling one-click generation of a rifled artillery barrel finite element model, one-click completion of parametric modeling of projectile belts, and one-click completion of finite element analysis pre-processing of the motion within the rifled artillery firing chamber, thus providing a fast and efficient method for finite element simulation analysis of the artillery firing process.

The present invention discloses a Python-based LDO circuit design method, which is applied to a terminal and implemented by executing code, and includes the following steps: Step 10, determining an initial circuit structure module based on design indicators; Step 20, searching for optimal size information for each transistor in a transistor parameter database; Step 30, generating multiple test circuit modules; Step 40, calling a simulator to perform simulation testing to obtain pre-simulation results; Step 50, generating a circuit layout; Step 60, calling a simulator to perform simulation testing to obtain post-simulation results; Step 70, if the post-simulation results do not meet the design indicators, executing Step 30. The present invention codifies and automates the LDO design process, and the code can be run to complete the complete design process from circuit description, size generation, multi-index simulation, and automatic layout and routing of the layout, thereby shortening the LDO layout design cycle, improving design efficiency, and achieving full automation of the LDO circuit to layout design process.

The present application relates to the technical field of wind power steel-concrete structure parameterization calculation, in particular to a Python language-based parameterized automatic modeling method for a tower structure Abaqus finite element model, which solves the problems of low efficiency, easy errors and difficult parameter adjustment of traditional manual modeling. The method comprises the following steps: reading geometric, material, modeling and load information in an Excel parameter file; automatically generating a concrete component, a steel wire body and a steel reinforcement cage; completing prestressed anchor cable system modeling; assembling each component and automatically assigning material and cross-section properties; finally performing mesh division, contact definition, boundary condition application and load loading, and saving a complete finite element model. The present application significantly improves modeling efficiency and consistency through full-process parameter driving and modular script architecture, supports flexible customization of a whole tower structure, and provides a high-reliability pre-processing scheme for complex structure simulation.

The invention discloses a floating board-to-board connector signal terminal pin structure design optimization method, and belongs to the technical field of connectors. According to the method, transient dynamic finite element full-automatic parametric modeling of terminal and plastic shell assembly is achieved through a Python language, associated data of clamping thorn structure parameters and insertion and extraction force characteristics are obtained through orthogonal experimental design, and a multivariate nonlinear prediction model is established. A sub-target multiplication and division method is innovatively adopted to construct an insertion and extraction force comprehensive performance target function, a genetic algorithm is applied to carry out multi-target optimization, and finally an optimal parameter combination meeting working condition requirements is obtained. According to the invention, the intelligent design of the terminal bayonet structure is realized, the mechanical stability, the assembly reliability and the production economy of the connector are obviously improved, and an efficient solution is provided for the design of a high-precision connector.

The invention discloses a high-quality data set construction method and device. The method comprises the steps of obtaining a first data set of a vulnerability list; screening the first data set through a screening function to obtain a second data set of the vulnerability list; based on the second data set, determining a first target data set for constructing a high-quality data set; based on the first target data set, determining a second target data set for constructing a high-quality data set; and based on the second target data set, determining a high-quality data set in the target format. According to the method, the high-quality data set for the Python language is obtained through the high-quality data set construction method, so that powerful support is provided for fine adjustment of a large model, code vulnerability pre-detection and repair are performed on the Python language, and development efficiency and project quality are guaranteed.

The application discloses a kind of Python language password API misuse automated detection method, system, equipment and medium, in the scheme provided by the present application, combined with Python language feature reconstruction abstract syntax tree, reconstruct abstract syntax tree according to Python language feature, while guaranteeing function consistency Simplify node representation, to reduce false positive rate and false negative rate in subsequent taint analysis process;Meanwhile, using static taint analysis technology, based on the reconstructed abstract syntax tree, the process and inter-function taint propagation are carried out, and all password API misuse rules are covered by the taint detector, so as to determine the detected password API misuse instance. Overall, the present application fills the blank of the current password API misuse detection for Python application, and has important support and promotion effect on password application security evaluation field.

The application provides a test method for improving interface script coverage, which comprises the following steps: 1, real-time monitoring of data of a server production environment; 2, processing of the collected data, extraction and processing of different component particles, interface names, request methods and input parameters; 3, converting the processed data into a script in python language, and packaging the script to provide to a specific tester, the tester decompresses the packaged script file; 4, displaying the script on a webpage front end, and checking and modifying the project and sending the project to a specified jenkins server to execute the script; 5, generating a test report and sending a notification to a user after the script is executed; 6, analyzing the generated test report, comparing the executed interface in the test report with the historical test interface, counting the interfaces that have not been tested, and finally comparing the coverage rates before and after the test to obtain the improved coverage rate of this test.

The invention discloses a label printer application opening system, and belongs to the technical field of label printing. The system comprises a label printer and a matched software development kit. The software development kit comprises a Python core software package preset in the label printer and a group of APIs (Application Program Interface) oriented to function calling. A Python interpreter is embedded in a processor of the label printer and used for running a system main program and a user-defined script written by a user based on a Python language. A user script communicates with a system main program by calling an API, external equipment data can be obtained, and a personalized label printing task is executed according to an instruction. The system main program responds to the script running request and monitors the running state of the script running request. According to the invention, an open development platform is constructed by integrating the Python interpreter and the open API, so that a user can conveniently develop customized applications, the problems of limited functions and poor expansibility of traditional printing equipment are solved, intelligence and automation of printing tasks are realized, the process is simplified, the efficiency is improved, and the cost is reduced.

The application provides a power engineering cost software cross-platform secondary development method, and relates to the field of software development.The method comprises the following steps: dividing a C++ original business module, preparing a to-be-generated header file, dividing the C++ original business module, preparing the to-be-generated header file, and forming information such as a header file, a link library dependency, and a link library directory of each module.Through the use of a path moving mechanism and an erasing mechanism, the existing C++ code function can be reused, and C++ objects and Python object data can be interchanged.The core of the method is to introduce Python language for secondary development, and the advantage lies in simple syntax, dynamic support, which can greatly improve the development efficiency, reduce the learning threshold, and simplify the cross-platform adaptation process.

This invention discloses a universal visual flight simulation system, relating to the field of flight simulation. This invention utilizes a technical approach combining Python and UE to implement flight simulation and visual rendering. The Python language implements aircraft guidance, control, and simulation solutions, demonstrating its autonomous controllability, flexibility, and efficiency. The UE implements a visual display of the flight process, demonstrating its advantages in high-fidelity 3D rendering, while also making the code editable and free to use. This flight simulation system, constructed using a modular approach, allows for flexible replacement of simulation models, enabling flight simulation of different types and quantities of aircraft.

An abnormal line degree data cleaning and image effect improving method, after converting the data format of the SQL database into the Dataframe format, the line degree data defect type and characteristics are analyzed, and the data cleaning is realized in a functionized and parallelized manner through the data cleaning strategy, the present application can realize relatively complex and universal data cleaning strategy based on python language programming, and also has high adaptability when serving various language data analysis algorithms.

The present invention relates to the field of geophysics technology and provides a method for accelerating LBFGS inversion using a physics-guided and data-driven multi-task forward simulation. The method comprises the following steps: 1. Using Python to write a physics-guided and data-driven multi-task neural network (PDMNet) to perform fitting training on the MT forward response calculation; 2. Converting the trained Python language model into a dynamic link library program written in C++; 3. Improving the forward response calculation module in a traditional LBFGS inversion method written in Fortran by integrating the dynamic link library program; and 4. Predicting the transverse magnetic (TM) forward response task using the improved traditional LBFGS inversion method. The present invention can effectively accelerate the traditional MT LBFGS inversion method.

The application relates to the technical field of access to an LDAP server. The method for processing an LDAP server based on python comprises the following steps: obtaining a structure and rules of a Schema required for accessing the LDAP server; establishing corresponding input structures and rules based on the structure and rules of the Schema, wherein the input structures and rules are established based on a python language; standardizing and packaging the input structures and rules to form a package, wherein the standardization packaging is provided with a corresponding preset filter for different types of users; and realizing the operation on information in the LDAP server through the data intercommunication between the package and the LDAP server. The method for processing an LDAP server based on python simplifies parameter requirements and reduces the use threshold by standardizing and assigning default values to parameters of input structures and rules.

The invention discloses an ethylene glycol project planning decision analysis system, and belongs to the field of project decision, and the system comprises a parameter input module which is used for receiving ethylene glycol project parameters inputted by a user and packaging the parameters through a Python language; the calculation module is connected with the parameter input module and used for calculating construction investment and operation cost based on the ethylene glycol project parameters; the economic index derivation module is connected with the calculation module and is used for calculating sales revenue and financial internal return rate; the calculation of the financial internal return rate comprises the following steps: constructing a dynamic cash flow model and solving by adopting a numerical analysis method; and the decision output module is used for comparing the financial internal return rate with a preset industry standard return rate and outputting a corresponding investment feasibility decision suggestion. According to the method, the Python language is introduced into the field of engineering economic analysis, an automatic decision-making tool containing core parameters is developed, and quantification of dynamic simulation and economic analysis of an investment scheme is achieved.

The invention provides a method for extracting physical page information from a kernel, which belongs to the technical field of memory page management, and comprises the following steps of: S1, dynamically loading a kernel mirror image and a kernel debugging symbol information table, analyzing by utilizing a drgn debugger, and reading data structure information of the kernel in operation; s2, compiling a drgn script through a python language, and extracting page information from the data structure information read in the step S1 through the drgn script; and S3, outputting the page information extracted in the step S2 in a structured form. According to the method, the function of automatically analyzing any physical page is realized by writing the python script on the basis of drgn and by utilizing the analysis capability of the drgn on a kernel symbol table and a data structure.

The application discloses a multi-tenant-oriented Python language remote checking service and debugging system and method in the technical field of program development auxiliary and debugging tool, and aims to effectively improve the development quality and debugging efficiency of a user's Python application program.In the application, a front-end module is used to send a request for starting a language checking service and a debugging service of an application to a back-end service container; the back-end service container is responsible for managing a hierarchical structure and program code of the application, responding to a request of a front-end for a language service and a debugging process of the application, mapping and binding a session between the front-end and a development container process, routing and forwarding a language service and a debugging message and the like; a database is used to save the hierarchical structure and the program code of the application; and a development container is used to run the language service and the debugging process and manage a process life cycle.The application effectively improves the development and debugging efficiency of the application program, and provides a good solution for the development and visual debugging of a multi-tenant Python application on a Web end.

The invention discloses a method for evaluating and relieving a third-party library API (Application Program Interface) incompatibility problem in large model code completion. The method comprises the following steps of: constructing a third-party library API knowledge base for a Python language third-party library; aiming at the problem that potential third-party library APIs in completion codes generated by a code completion system based on a large language model are incompatible in use, automation is carried out based on a third-party library API knowledge base; and a lightweight intervention mechanism is adopted to detect and repair an incompatibility problem in real time. According to the method, API change information is obtained through systematic analysis and version comparison of the third-party library APIs, incompatible use of the APIs is detected, and lightweight relief is achieved by dynamically injecting problem causes and API standard use information into cues; the API signature and real-time incompatibility detection service can be provided with extremely low performance overhead, and the development efficiency and the code reliability are practically improved.