106 results about "Python language" patented technology

The present invention discloses a crystal plasticity finite element modeling simulation method, comprising the following steps: obtaining grain information based on EBSD analysis; importing the ctf format file generated by the EBSD analysis into Dream.3D software to realize automatic reconstruction of the grain structure, and outputting the input file and the geometric orientation data of each grain; then processing the grain geometric orientation data through a Python language script to obtain the average geometric orientation information of each grain; combining the average geometric orientation information of the grain with the input file using a Python script to generate a complete input file with geometric model information and material property information; assigning boundary conditions to the model in ABAQUS finite element analysis software and setting its constitutive relationship using the UMAT subroutine, thereby realizing the entire crystal plasticity finite element analysis process. The present invention realizes the process of crystal plasticity finite element modeling and simulation analysis.

According to the rapid modeling method for the finite element of the bridge rod system unit disclosed by the invention, a clearer and more reasonable modeling method is constructed by combining rod system structure modeling and BIM modeling logic, and a user can obtain the finite element of the bridge rod system unit by modifying simple underlying data or utilizing a result formed in the method. And analysis and modeling are realized by effectively combining with other software at low cost. The method uses a Python language, and comprises the following steps of: 1, realizing attributes of editing classes by utilizing the Python language; 2, creating a material and a section instance; 3, the bridge structure is divided into different component instances corresponding to the bridge types, boundary information between different components is bound through the boundary class, and loads acting on the different components are determined through the load class; 4, packaging the axis class, and binding the component instance with the axis instance; 5, adding a calculation module, and carrying out mesh generation; 6, obtaining each subdivision point on the axis, and connecting the subdivision points to generate a corresponding unit set; and 7, establishing boundary and load examples.

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 present invention belongs to the technical field of engineering design and optimization, specifically, a method for parameterizing and generating surfaces of propeller blades based on B-splines: first, based on the B-spline curve method, the least squares method is adopted to fit the blade section value points at different radii, and the parameterization of the blade section and the outer contour is realized by using methods such as proportion, offset, and coordinate transformation; secondly, based on the B-spline surface method, the propeller blade surface, blade back, blade root and blade top surfaces are efficiently generated; finally, the relevant program is written based on the Python language, and a UML class diagram of the program is given; the present invention programs the entire process through the language Python to realize the parameterization of propeller blades and the automatic generation of surfaces, effectively improving the propeller modeling efficiency and the flexibility of parameterization variable selection in the optimization process.

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 a python language-based Excel data verification and import method, system and device and a medium, and the method comprises the following steps: S1, obtaining an Excel file, and obtaining a corresponding import parameter; s2, reading the data of the Excel file; and storing the data in a memory. S3, verifying the data of the Excel file; and verifying each row of data one by one by utilizing a rule engine technology, and recording a verification result in a log. And if the data verification is not passed, displaying corresponding error prompt information. And S4, processing a verification result, if verification is qualified, storing Excel file data into a specified database or data table, and in the storage process, enabling fields in the data table to correspond to columns in the Excel file by a system according to a field mapping relationship set by a user, so as to ensure the correctness and integrity of the data. If the verification result is not qualified, the data of the Excel file is wrongly recorded. The method has the advantage that the efficiency and the accuracy of Excel file data processing are improved.

The invention provides a hardware health monitoring method, system and equipment of a test machine and a medium. The method comprises the steps that temperature data of to-be-monitored hardware of a test machine and the health state of a disk are obtained according to a first detection rule, and the to-be-monitored hardware comprises a controller, a case and the disk; judging whether the to-be-monitored hardware of the test machine is abnormal or not based on whether the temperature data of the to-be-monitored hardware and / or the health state of the disk meet preset conditions or not; and if the target hardware of the test machine is abnormal, writing alarm information into a log file and executing an alarm operation. In the mode, the python language can be used for coding, and the monitoring of the temperature and health state of each hardware of different types of test machines in a cross-platform manner is supported, so that the production efficiency is improved, the maintenance cost is reduced, and the stable operation of the test machines is ensured.

The invention provides a method for simulating heavy non-aqueous phase liquid in underground water by coupling a mathematical model and an optimization algorithm. The method comprises the following steps: respectively acquiring underground water dynamic change data, environmental index change data and DNAPL concentration data; hydrogeological conditions of the site and the DNAPL pollution migration and transformation process are analyzed; performing simulation based on a multiphase flow and solute transport coupling model; and constructing a simulation system in which a mathematical model and an optimization algorithm are coupled, simulating and evaluating the transfer process of the DNAPL in the underground water according to the acquired data, and acquiring a simulation result matched with an actual monitoring condition. According to the method, programming is carried out based on the Python language, through mutual coupling of open source programs, simulation of the whole process of different phase states of DNAPL pollution is achieved, meanwhile, model parameters are corrected based on an optimization algorithm, an optimal simulation result conforming to actual monitoring data is finally obtained, and a foundation is laid for subsequent deeper DNAPL simulation work.

The invention discloses an automatic detection method, system and device for Python language password API misuse and a medium. In the scheme provided by the invention, an abstract syntax tree is reconstructed in combination with Python language characteristics, the abstract syntax tree is reconstructed according to the Python language characteristics, node representation is simplified while function consistency is guaranteed, and the probability of misuse of the Python language password API misuse is lowered. Therefore, the false alarm rate and the missing report rate are reduced in the subsequent taint analysis process; meanwhile, a static taint analysis technology is utilized, taint propagation in the process and between functions is carried out based on reconstruction of an abstract syntax tree, and all password API misuse rules are covered through a taint detector, so that a detected password API misuse instance is determined. Generally speaking, the method fills up the blank that no password API misuse detection for the Python application program exists at present, and plays an important supporting and promoting role in the field of password application security evaluation.

The invention discloses a grid optimization generation method and device of a one-dimensional and two-dimensional coupling hydrodynamic model, a medium and a product, and relates to the field of data processing.The method comprises the steps that after a grid river network digital elevation model is generated based on original terrain data, a river channel center line and boundary lines of the two banks of a river channel are determined; a hydrodynamic simulation system is used for obtaining an unstructured grid unit information file based on a riverway center line and riverway two-bank boundary lines, a coupling point processing module is written through a python language, and unstructured grid unit information is received and preprocessed; and a python script is operated, a cross product function and a straddling condition are utilized, the verification model is calibrated based on the preprocessed unstructured grid unit information, and grid optimization of the one-two-dimensional coupling hydrodynamic model is completed. According to the method and the device, the grid optimization of the one-two-dimensional coupled hydrodynamic model can be completed under the condition of not depending on third-party hydrodynamic modeling software, so that the accuracy of generating the coupling point of the one-two-dimensional coupled hydrodynamic model and the grid optimization generation speed are improved.

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 invention discloses a multi-software combined special-shaped superconducting coil structure design method, and aims to optimize a modeling mode of a special-shaped superconducting coil and improve modeling efficiency on the premise of ensuring result precision. According to the method, for a three-dimensional special-shaped complex superconducting magnet structure, a platform is built based on a Python language, and a multi-software combined geometric modeling system is built by combining mechanical design software SolidWorks, finite element software Abaqus and electromagnetic analysis software Opa-3d. The method comprises the following steps: firstly, establishing a geometric model through SolidWorks software, and outputting the geometric model in a general file format; and then, importing the geometric file into Abaqus to carry out automatic unit division. Geometric model data files of the divided units are obtained through calculation, geometric coordinates of unit nodes are read in sequence, the geometric coordinates are arranged into coil geometric data files which can be recognized by Opera-3d, and finally geometric modeling is completed in Opera-3d. According to the method, the blank that the coil in Opera-3d cannot be directly imported through mechanical design software is filled up, and the geometric modeling mode of the coil in the software is enriched.

The invention discloses a data set expansion method and system for a password misuse detector, and belongs to the field of password misuse detector performance detection calculation. The method comprises the following steps: collecting open source items related to password misuse, and sorting out an API (Application Program Interface) related to password misuse and a password library used by the API; the method comprises the following steps: collecting open source codes related to a password algorithm in a Githhub warehouse, and screening out the open source codes related to password misuse from the open source codes related to the password algorithm based on an API (Application Program Interface) related to password misuse and a password library used by the API; wherein the programming language used by the open source code comprises a Java language, a C / C + + language, a Go language and a Python language; performing variation on the open source code using the Java language; a dataset of a password misuse detector is constructed based on the open source code associated with password misuse and the variant open source code using the Java language. The password misuse data set can be expanded.

The invention provides a system-level verification convergence system, method and product, and belongs to the technical field of chip verification. The system is a cocotb system verification platform based on a Python language, and the system comprises an application component app agent which is used for calling an application program based on a Python library to carry out network message testing on a DUT; the cocotblet-pcie TLP transmission layer adapter is used for receiving and transmitting a PCIe (Peripheral Component Interconnect Express) message at a TLP transmission layer interface; the network message transmitting and receiving component pktgen scapy agent is used for executing the processes of transmitting, receiving, analyzing and automatically responding different types of network messages based on the scapy application program of the Python library; the cocotbleth-th TLP transmission layer adapter is used for receiving and transmitting a network message at a TLP transmission layer interface; and the checker agent is used for generating a comparison result of the test expected result and an actual output result of the DUT. The invention aims to improve the convergence speed of intelligent network card chip system-level verification.

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 present invention relates to a system and method for realizing SAS data analysis capability in a python environment, wherein the system comprises the following modules: a SAS log analysis module, configured to periodically extract SAS execution logs from SAS, and perform statistics, preprocessing and analysis on the SAS program execution statement information therein; a newly added operator module, configured to use the result of periodic analysis of the SAS execution log to screen the operator list that needs to be stored; a python conversion module, configured to convert and encapsulate statements and parameters with a frequency of occurrence that meet the standard into python operators according to the screened operator list, and test and encapsulate the python operators into a sastopy library; a sastopy library, configured to convert statements in SAS into operator forms of python language when encapsulating the python operators into the sastopy library, and store them; an operator operation and maintenance module, configured to monitor and maintain the sastopy library. The present invention enables business personnel to complete data analysis tasks more intuitively and conveniently, thereby improving work efficiency and flexibility.

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 invention discloses a railway tunnel portal parametric modeling method based on an IFC file, and the method specifically comprises the following steps: 1, extracting three types of core parameter sets of an inner contour section, an open cut tunnel lining section and a portal member based on a railway tunnel general reference graph; 2, on the basis of the IFC file structure features and an IfCpenShell toolkit, entity elements of an inner contour, an open cut tunnel lining and a tunnel portal component are constructed in the IFC file through the python language; 3, based on the spatial assembly constraint condition of the railway tunnel portal, establishing a geometric association relationship among the three parts of entity elements, and forming an IFC file of the whole railway tunnel portal; and 4, importing the IFC file formed in the step 3 into BIM software for parametric modeling. According to the method, the problems of poor compatibility of different software and insufficient data interoperability and expansibility in the existing parametric modeling are solved.

The invention belongs to the technical field of filling type field-induced phase-change materials, and discloses a method for regulating and controlling the performance of a filling type field-induced phase-change material. The method comprises the following steps: (1) data set acquisition: acquiring previous experimental data from publicly published literatures, tables and graphs and forming a data set; (2) data preprocessing: executing all preprocessing by using a Python language in the Juputer Notebook, wherein the Python language is used in the Juputer Notebook; standard Scaler is used to carry out standardization on the data set; (3) constructing a machine learning model: constructing a prediction model of the nonlinear conductivity of the filled polymer composite material by adopting support vector regression, kernel ridge regression, random forest regression, XGBoost regression and gradient enhanced regression; and (4) integrating prediction results by adopting a Stacking integration algorithm. According to the method, the SEL strategy is adopted, the performance of the Eb and alpha models is improved by integrating the five basic models, the prediction performance of the models can be improved, the generalization ability of the models can be enhanced, and the models can well express new and unseen 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 invention provides a method for carrying out objective evaluation by utilizing dynamic software data and a Python language. The method comprises the following steps: collecting and processing data; evaluation index and algorithm realization: designing a Python script to realize a corresponding evaluation index according to an actual operation condition and an analysis target of the vehicle, and performing quantitative evaluation according to different index algorithms by using data corresponding to the related evaluation index; wherein the evaluation indexes comprise the following four types: operation stability evaluation, drivability evaluation, cross-country evaluation and comfort evaluation; and the evaluation result is visualized. Data analysis is carried out through an algorithm, a consistent and standardized evaluation result can be provided, man-made subjective judgment interference is removed, and therefore the objectivity of evaluation is improved. The method is realized based on a Python language, and the system can be adjusted and expanded according to actual requirements.

The present invention relates to the technical field of chip verification, and in particular to a chip system-level verification system based on the Python language, including: a preset Python script set in a first verification module, and a design under test set in a second verification module; the preset Python script sets the first verification module as the master device party and the second verification module as the slave device party; the first verification module generates a main thread of the Python script, sends a command to start the verification platform simulation thread to the second verification module, starts the verification platform simulation thread, and establishes a connection between the main thread of the Python script and the verification platform simulation thread; the main thread of the Python script controls the first verification module to send a verification request command to the second verification module, and the verification platform simulation thread controls the second verification module to process the verification request command. The present invention simplifies the chip system-level verification process, improves the verification efficiency, and reduces the verification cost.

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 present invention discloses a parametric modeling method of an Abaqus model of a bolted ECC-RC beam based on Python language, which belongs to the field of image recognition and data processing technology, and includes the following steps: creating a concrete beam model; assembling the concrete beam according to axisymmetry; digging holes and splitting; creating hinge supports and loading support steel plates; creating bolts and placing them in holes, creating a steel cage for the beam and a steel cage for the plate; creating an analysis step; setting a contact relationship; dividing the grid; and applying a load. In the above manner, compared with the traditional GUI modeling method, the present invention uses Python language to perform secondary development on Abaqus, realizes intelligent parametric modeling of finite element models, and only takes tens of seconds to complete the modeling process compared to the original modeling process of several hours, saving a lot of time for finite element modeling and greatly improving the efficiency of finite element modeling.

The present invention discloses a phase change heat sink design method based on topological optimization. The phase change heat sink includes phase change material, fins, shell, and substrate. The design method includes the following steps: determine the heat sink shell size, material, and phase change material type according to the design working conditions; establish a finite element analysis model of the phase change heat sink heat transfer, set optimization goals and constraints, and establish a topological optimization model; use Python language to solve the topological optimization model to preliminarily obtain the size, structure, and layout of the fins; use a binary processing method to reconstruct the topologically optimized fins, and check the structural strength and heat transfer characteristics of the heat sink. The method is used to optimize the design of the phase change heat sink, and the maximum heat transfer performance can be achieved under certain materials. The method provides theoretical guidance for the structural design of the phase change heat sink.

The invention discloses a method for optimizing event trigger test efficiency, which relates to the technical field of software testing, and comprises the following steps: S1, arranging an event library by using a notebook or Excel, collecting and storing information related to events, and carrying out classified management on the events; s2, according to a test requirement, setting a sending frequency and a data type of an event, writing a sending related code, and appointing a sending target server; and S3, after network communication is debugged to be normal, executing a sending program, sending event information to a platform, and checking the condition of a rule triggered after the data is sent at the platform side. According to the method for optimizing the event trigger test efficiency, the technology is used for simulating the operation behavior of a person, generating events, collecting the events into an event library, compiling an automatic script by using a Python language, and sending the events which are pre-stored in the event library in advance to a platform in batches, so that the effect generated by manual operation is achieved, manual operation is replaced, and the efficiency is improved by more than 20 times.

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.