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diff --git a/new_plan.md b/new_plan.md deleted file mode 100644 index 6c7186e..0000000 --- a/new_plan.md +++ /dev/null @@ -1,65 +0,0 @@ - Design - -The application will be a single-window GUI built with PyQt5. It will be composed of three main components: a main -window, a refactored plotter widget, and a background worker for data acquisition. - - 1 PicoStreamMainWindow (QMainWindow): This will be the application's central component, serving as the main entry point. - • Layout: It will feature a two-panel layout. The left panel will contain all user-configurable settings for the - acquisition (e.g., sample rate, voltage range, output file). The right panel will contain the embedded live plot. - • Control: It will have "Start" and "Stop" buttons to manage the acquisition lifecycle. It will manage the - application's state (e.g., idle, acquiring, error). - • Persistence: It will use QSettings to automatically save user-entered settings on exit and load them on startup. - • Lifecycle: It will be responsible for creating and managing the background worker thread and ensuring a graceful - shutdown. - 2 HDF5LivePlotter (QWidget): The existing plotter will be refactored from a QMainWindow into a QWidget. - • Responsibility: Its sole responsibility will be to monitor the HDF5 file and display the live data. It will no - longer be a top-level window or control the application's lifecycle. - • Integration: An instance of this widget will be created and embedded directly into the right-hand panel of the - PicoStreamMainWindow. - 3 StreamerWorker (QObject): This class will manage the acquisition task in a background thread to keep the GUI - responsive. - • Execution: It will be moved to a QThread. Its primary method will instantiate the Streamer class with parameters - from the GUI and call the blocking Streamer.run() method. - • Communication: It will use Qt signals to report its status (e.g., finished, error) back to the PicoStreamMainWindow - in a thread-safe manner. The main window will connect to these signals to update the UI, for example, by - re-enabling the "Start" button upon completion. - - Phased Implementation Plan - -This plan breaks the work into five distinct, sequential phases. - -Phase 1: Project Restructuring and GUI Shell The goal is to set up the new file structure and a basic, non-functional GUI -window. - - 1 Rename picostream/main.py to picostream/cli.py. - 2 Create a new, empty picostream/main.py to serve as the GUI entry point. - 3 In the new main.py, create a PicoStreamMainWindow class with a simple layout containing placeholders for the settings - panel and the plot. - 4 Update the justfile with a new target to run the GUI application. - -Phase 2: Background Worker Implementation The goal is to run the data acquisition in a background thread, controlled by -the GUI. - - 1 In picostream/main.py, create the StreamerWorker class inheriting from QObject. - 2 Implement the QThread worker pattern in PicoStreamMainWindow to start the acquisition when a "Start" button is clicked - and to signal a stop using the existing shutdown_event. - 3 Connect the worker's finished and error signals to GUI methods that update the UI state (e.g., re-enable buttons). - -Phase 3: GUI Controls and Settings Persistence The goal is to make the acquisition configurable through the GUI and to -remember settings. - - 1 Populate the settings panel in PicoStreamMainWindow with input widgets for all acquisition parameters. - 2 Pass the values from these widgets to the StreamerWorker when starting an acquisition. - 3 Implement load_settings and save_settings methods using QSettings. - -Phase 4: Plotter Integration The goal is to embed the live plot directly into the main window. - - 1 In picostream/dfplot.py, refactor the HDF5LivePlotter class to inherit from QWidget instead of QMainWindow. Remove its - window-management logic. - 2 In PicoStreamMainWindow, replace the plot placeholder with an instance of the refactored HDF5LivePlotter widget. - -Phase 5: Packaging The goal is to create a standalone, distributable executable. - - 1 Add a new build target to the justfile that uses PyInstaller to bundle the application. - 2 Configure the build to handle dependencies, particularly creating a hook for Numba if necessary. - 3 Test the final executable. |