CodingToolBox

github:

CodingToolBox

Requires:

• Python 3.6 (or above)
• numpy

Update dialog

• 1.0.0: Upload package.
• 1.1.0: Add two methods: ask_file_popup, ask_folder_popup
• 1.2.0: Add method: install_checker
  • 1.2.1: Edit copy in var_form.
  • 1.2.2: Fix init bug.
  • 1.2.3: Fix bug at DetailRecorder.
  • 1.2.4: Fix bug at DetailRecorder.
• 1.3.0: Add method: cal_SNR.
  • 1.3.1: Fix bug at cal_SNR.
  • 1.3.2: Use importlib.util.find_spec instead of ModuleNotFoundError.
• 1.4.0: Add module: TorchLoss, contains various of loss function including MSE, RMSE, MAPE, MAE, SNR and SSIM.
• 2.0.0: Rewrite library, remove AnimatedPlot.
  • 2.0.1: fix bug.

Lib Description

• Most of the functions are elaborated at my another repository useful_coding_tools.
• There're some demo at CodingToolBox.

Lib Structure

• CodingToolBox
  • get_peak: Get indices and values of peaks of periodical signal by automatic multiscale-based peak detection (AMPD) algorithm.
  • DetailRecorder: Convenient recording tool.
  • raw_var: Return raw variable string that can easily be used in another script.
  • TkMethods: Methods based on tkinter.
    • ask_file: Popup menu for asking file location.
    • ask_folder: Popup menu for asking folder location.
  • Math: Math module.
    • norm_p: Return norm.
    • sqrt: Support negative value.
  • NpLoss: Loss function (NumPy version).
    • MAE: mean absulate error.
    • MAPE: mean absolute percentage error.
    • MSE: mean square error.
    • RMSE: root mean square error.
    • SNR: signal-to-noise ratio.
    • SSIM: structural similarity index.
  • TorchLoss: Loss function (PyTorch version).
    • MAE: mean absulate error.
    • MAPE: mean absolute percentage error.
    • MSE: mean square error.
    • RMSE: root mean square error.
    • SNR: signal-to-noise ratio.
    • SSIM: structural similarity index.