Analysis

Numerical Analysis toolkit centred around PDEs, for demonstration and understanding purposes not production

Numerical Analysis toolkit centred around PDEs, for demonstration and understanding purposes not production Use procedure: Initialise a new instance of the PDE class, all calculations and variables will be managed by this object Inputs: tlim – time to solve up to dx – x spacing, by default a uniform grid is used xlims – np.array([lower, upper]) bounds    

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Scripts

A python script to generate a random Euler circuit with given number of vertices and edges

An okayish python script to generate a random Euler circuit with given number of vertices and edges. Executing the Script Just download or copy the code in testcasegen.py,use your python IDE or terminal to run the script and give the number of vertices and edges as asked.The output is generated in the input format specified by the assignment along with one of the possible outputs for the assignment program. Very Very Important⭐ ⭐ ⭐ The program will run into infinite […]

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Wrapper

Little wrapper around asyncpg for specific experience

Little wrapper around asyncpg for specific experience. Basic usage from asyncpg_engine import Engine engine = await Engine.create(“postgres://guest:[email protected]:5432/guest?sslmode=disable”) async with engine.acquire() as con: # https://magicstack.github.io/asyncpg/current/api/index.html#asyncpg.connection.Connection assert await con.fetchval(“SELECT 1”) == 1 Custom type conversions You can specify custom encoderdecoder by subclassing Engine: from asyncpg_engine import Engine import orjson class MyEngine(Engine): @staticmethod async def _set_codecs(con: Connection) -> None: # https://magicstack.github.io/asyncpg/current/api/index.html#asyncpg.connection.Connection.set_type_codec await con.set_type_codec( “json”, encoder=orjson.dumps, decoder=orjson.loads, schema=”pg_catalog” ) Development and contribution First of all you should install Poetry using official instructions or solutions […]

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Hunting

Monster hunter world randomizer project

monster hunter world randomizer project Settings are in rando_config.py Current script for attack randomization is n mytest.py There are a million esoteric things to keep track of for quest generation, so i’ve included the main file from the old codebase as a reference. MHW editor used for debugging and encryption is provided by synthlight at https://github.com/Synthlight/MHW-Editor this would be much more difficult without it, so I thank him immensely GitHub View Github    

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PDF

Extract the table in the PDF，outputs the data similar to the json format

在开发RPA项目时，需要提取pdf表格内容，并保留表格格式。在网络中苦苦寻求多日，未能找到一份完全满足项目需求的开源库。最终采用pymupdf+cv2框架实现对pdf表格的提取。由pymupdf读取pdf（pumupdf还支持xps格式文件）内容，而cv2依据提出内容中的线条绘制并计算表格轮廓，最终找找到文本内容与表格对应关系。项目比较小众，代码也很零散，但希望能够帮助到恰好有需要的人。 In the RPA project, the content in pdf format needs to be extracted and the table format is retained. I have been struggling for many days in the network to find an open source library that fully meets the needs of the project. Finally, the pymupdf + cv2 framework is used to read the content of pdf from pymupdf (pumupdf also supports xps format files), and cv2 elaborates the drawing in the proposed content and calculates the table, and […]

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Controller

Closed Loop Control system of Sharp Wave Ripples in Hippocampus CA3 region

Mengzhan (John) code for Closed Loop Control system of Sharp Wave Ripples in Hippocampus CA3 region Creating Python Virtual Environment To run the project, you’ll first need to create a python virtual environment with specific dependencies installed. The packages needed can be found at this ”’clc_packages”’ repository. Link: https://bitbucket.org/LauFoo/clc_packages/src/master/ Create a python virtual environment with pyvenv packages and venv command Go to clc_packages repository and clone it, make a local repository Activate the virtual environment with the line (name_of_venv)Scriptsactivate Change […]

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identification

Vehicle direction identification consists of three module detection , tracking and direction recognization

Vehicle direction identification consists of three module detection , tracking and direction recognization. Algorithm used : Yolo algorithm for detection + SORT algorithm to track vehicles + vector based direction detection Backend : opencv and python Library required: opencv = ‘4.5.4-dev’ scipy = ‘1.4.1’ filterpy lap scikit-image IMPORTANT: I hadn’t uploaded model weights and configuration files (which were used for object detection) here because those were already available in yolo_detection repo download yolo tiny weights , config file and coco.names […]

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