{"id":21191159,"url":"https://github.com/hasanisaeed/recurrence-plot-py","last_synced_at":"2025-07-10T02:32:50.362Z","repository":{"id":124704631,"uuid":"463261826","full_name":"hasanisaeed/recurrence-plot-py","owner":"hasanisaeed","description":"An advanced technique of nonlinear data analysis","archived":false,"fork":false,"pushed_at":"2024-11-15T16:25:44.000Z","size":537,"stargazers_count":7,"open_issues_count":2,"forks_count":1,"subscribers_count":1,"default_branch":"main","last_synced_at":"2024-11-15T16:33:22.835Z","etag":null,"topics":["cnn","convolutional-neural-networks","recurrence","recurrence-plot","time-series","time-series-analysis","timeseries"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/hasanisaeed.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null}},"created_at":"2022-02-24T18:38:09.000Z","updated_at":"2024-11-15T15:30:44.000Z","dependencies_parsed_at":"2023-10-15T20:09:56.617Z","dependency_job_id":null,"html_url":"https://github.com/hasanisaeed/recurrence-plot-py","commit_stats":null,"previous_names":[],"tags_count":1,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/hasanisaeed%2Frecurrence-plot-py","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/hasanisaeed%2Frecurrence-plot-py/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/hasanisaeed%2Frecurrence-plot-py/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/hasanisaeed%2Frecurrence-plot-py/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/hasanisaeed","download_url":"https://codeload.github.com/hasanisaeed/recurrence-plot-py/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":225615195,"owners_count":17496942,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["cnn","convolutional-neural-networks","recurrence","recurrence-plot","time-series","time-series-analysis","timeseries"],"created_at":"2024-11-20T19:01:29.790Z","updated_at":"2024-11-20T19:02:10.141Z","avatar_url":"https://github.com/hasanisaeed.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Recurrence Plot\n[Recurrence Plot](https://en.wikipedia.org/wiki/Recurrence_plot) – A recurrence plot (RP) is an advanced technique of **nonlinear** data analysis. It is a visualisation (or a graph) of a square matrix, in which the matrix elements correspond to those times at which a state of a dynamical system recurs (columns and rows correspond then to a certain pair of times).\n\n## Result\n![](results/1D_to_2D.jpg)\n\n## Usage\n**1. Install requirements:**\n\nEnsure you have Python 3 installed. Install the required dependencies using:\n\n\n    pip install -r requirements.txt\n\n**2. Run `example.py` script:**\n\n    python3 example.py # or python example.py\n\nThis will:\n\n- Generate a random signal.\n- Smooth the signal using a moving average filter.\n- Compute and visualize the recurrence plot.\n- Save the resulting plot as results/1D_to_2D.jpg.\n\n----\n## How to Use the recurrence Package\n\nIf you want to use the recurrence package in your own projects:\n\n1) **Import the Required Modules:**\n\n    For recurrence plot functions, import from recurrence.plotting.\n    For signal processing utilities, import from recurrence.convolve.\n\n    Example:\n\n    ```python\n    from recurrence.plotting import setup_plot, save_plot\n    from recurrence.convolve import calculate_convolve\n    ```\n\n2) **Process Your Signal:** \n   \n   Use `calculate_convolve` to smooth your input signal, then use the `setup_plot` and `save_plot` functions to generate and save recurrence plots.","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhasanisaeed%2Frecurrence-plot-py","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fhasanisaeed%2Frecurrence-plot-py","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhasanisaeed%2Frecurrence-plot-py/lists"}