mirror of
https://github.com/bec-project/bec_widgets.git
synced 2025-07-14 11:41:49 +02:00
refactor(widget/monitor_scatter_2D): deleted
This commit is contained in:
@ -1,7 +1,6 @@
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from .editor import BECEditor
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from .editor import BECEditor
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from .figure import BECFigure, FigureConfig
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from .figure import BECFigure, FigureConfig
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from .monitor import BECMonitor
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from .monitor import BECMonitor
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from .monitor_scatter_2D import BECMonitor2DScatter
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from .motor_control import (
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from .motor_control import (
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MotorControlAbsolute,
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MotorControlAbsolute,
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MotorControlRelative,
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MotorControlRelative,
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@ -1 +0,0 @@
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from .monitor_scatter_2D import BECMonitor2DScatter
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@ -1,374 +0,0 @@
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# pylint: disable = no-name-in-module,missing-module-docstring
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import time
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from collections import defaultdict
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import numpy as np
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import pyqtgraph as pg
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from bec_lib import MessageEndpoints
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from qtpy.QtCore import Signal as pyqtSignal
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from qtpy.QtCore import Slot as pyqtSlot
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from qtpy.QtWidgets import QApplication, QVBoxLayout, QWidget
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from bec_widgets.utils import yaml_dialog
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from bec_widgets.utils.bec_dispatcher import BECDispatcher
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CONFIG_DEFAULT = {
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"plot_settings": {"colormap": "CET-L4", "num_columns": 1},
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"waveform2D": [
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{
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"plot_name": "Waveform 2D Scatter (1)",
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"x_label": "Sam X",
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"y_label": "Sam Y",
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"signals": {
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"x": [{"name": "samx", "entry": "samx"}],
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"y": [{"name": "samy", "entry": "samy"}],
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"z": [{"name": "bpm4i", "entry": "bpm4i"}],
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},
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},
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{
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"plot_name": "Waveform 2D Scatter (2)",
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"x_label": "Sam Y",
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"y_label": "Sam X",
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"signals": {
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"x": [{"name": "samy", "entry": "samy"}],
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"y": [{"name": "samx", "entry": "samx"}],
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"z": [{"name": "gauss_bpm", "entry": "gauss_bpm"}],
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},
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},
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],
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}
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class BECMonitor2DScatter(QWidget):
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update_signal = pyqtSignal()
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def __init__(
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self,
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parent=None,
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client=None,
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config: dict = None,
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enable_crosshair: bool = True,
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gui_id=None,
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skip_validation: bool = True,
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toolbar_enabled=True,
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):
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super().__init__(parent=parent)
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# Client and device manager from BEC
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self.plot_data = None
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bec_dispatcher = BECDispatcher()
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self.client = bec_dispatcher.client if client is None else client
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self.dev = self.client.device_manager.devices
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self.queue = self.client.queue
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self.validator = None # TODO implement validator when ready
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self.gui_id = gui_id
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if self.gui_id is None:
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self.gui_id = self.__class__.__name__ + str(time.time())
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# Connect dispatcher slots #TODO connect endpoints related to CLI
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bec_dispatcher.connect_slot(self.on_scan_segment, MessageEndpoints.scan_segment())
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# Config related variables
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self.plot_data = None
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self.plot_settings = None
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self.num_columns = None
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self.database = {}
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self.plots = {}
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self.grid_coordinates = []
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self.curves_data = {}
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# Current configuration
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self.config = config
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self.skip_validation = skip_validation
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# Enable crosshair
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self.enable_crosshair = enable_crosshair
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# Displayed Data
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self.database = {}
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self.crosshairs = None
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self.plots = None
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self.curves_data = None
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self.grid_coordinates = None
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self.scan_id = None
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# Connect the update signal to the update plot method
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self.proxy_update_plot = pg.SignalProxy(
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self.update_signal, rateLimit=10, slot=self.update_plot
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)
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# Init UI
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self.layout = QVBoxLayout(self)
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self.setLayout(self.layout)
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if toolbar_enabled: # TODO implement toolbar when ready
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self._init_toolbar()
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self.glw = pg.GraphicsLayoutWidget()
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self.layout.addWidget(self.glw)
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if self.config is None:
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print("No initial config found for BECDeviceMonitor")
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else:
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self.on_config_update(self.config)
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def _init_toolbar(self):
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"""Initialize the toolbar."""
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# TODO implement toolbar when ready
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# from bec_widgets.widgets import ModularToolBar
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#
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# # Create and configure the toolbar
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# self.toolbar = ModularToolBar(self)
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#
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# # Add the toolbar to the layout
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# self.layout.addWidget(self.toolbar)
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def _init_config(self):
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"""Initialize the configuration."""
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# Global widget settings
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self._get_global_settings()
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# Plot data
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self.plot_data = self.config.get("waveform2D", [])
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# Initiate database
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self.database = self._init_database()
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# Initialize the plot UI
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self._init_ui()
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def _get_global_settings(self):
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"""Get the global widget settings."""
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self.plot_settings = self.config.get("plot_settings", {})
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self.num_columns = self.plot_settings.get("num_columns", 1)
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self.colormap = self.plot_settings.get("colormap", "viridis")
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def _init_database(self) -> dict:
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"""
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Initialize the database to store the data for each plot.
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Returns:
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dict: The database.
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"""
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database = defaultdict(lambda: defaultdict(lambda: defaultdict(list)))
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return database
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def _init_ui(self, num_columns: int = 3) -> None:
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"""
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Initialize the UI components, create plots and store their grid positions.
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Args:
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num_columns (int): Number of columns to wrap the layout.
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This method initializes a dictionary `self.plots` to store the plot objects
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along with their corresponding x and y signal names. It dynamically arranges
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the plots in a grid layout based on the given number of columns and dynamically
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stretches the last plots to fit the remaining space.
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"""
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self.glw.clear()
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self.plots = {}
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self.imageItems = {}
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self.grid_coordinates = []
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self.scatterPlots = {}
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self.colorBars = {}
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num_plots = len(self.plot_data)
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# Check if num_columns exceeds the number of plots
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if num_columns >= num_plots:
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num_columns = num_plots
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self.plot_settings["num_columns"] = num_columns # Update the settings
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print(
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"Warning: num_columns in the YAML file was greater than the number of plots."
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f" Resetting num_columns to number of plots:{num_columns}."
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)
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else:
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self.plot_settings["num_columns"] = num_columns # Update the settings
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num_rows = num_plots // num_columns
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last_row_cols = num_plots % num_columns
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remaining_space = num_columns - last_row_cols
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for i, plot_config in enumerate(self.plot_data):
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row, col = i // num_columns, i % num_columns
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colspan = 1
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if row == num_rows and remaining_space > 0:
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if last_row_cols == 1:
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colspan = num_columns
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else:
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colspan = remaining_space // last_row_cols + 1
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remaining_space -= colspan - 1
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last_row_cols -= 1
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plot_name = plot_config.get("plot_name", "")
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x_label = plot_config.get("x_label", "")
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y_label = plot_config.get("y_label", "")
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plot = self.glw.addPlot(row=row, col=col, colspan=colspan, title=plot_name)
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plot.setLabel("bottom", x_label)
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plot.setLabel("left", y_label)
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plot.addLegend()
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self.plots[plot_name] = plot
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self.grid_coordinates.append((row, col))
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self._init_curves()
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def _init_curves(self):
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"""Init scatter plot pg containers"""
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self.scatterPlots = {}
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for i, plot_config in enumerate(self.plot_data):
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plot_name = plot_config.get("plot_name", "")
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plot = self.plots[plot_name]
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plot.clear()
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# Create ScatterPlotItem for each plot
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scatterPlot = pg.ScatterPlotItem(size=10)
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plot.addItem(scatterPlot)
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self.scatterPlots[plot_name] = scatterPlot
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@pyqtSlot(dict)
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def on_config_update(self, config: dict):
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"""
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Validate and update the configuration settings.
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Args:
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config(dict): Configuration settings
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"""
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# TODO implement BEC CLI commands similar to BECPlotter
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# convert config from BEC CLI to correct formatting
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config_tag = config.get("config", None)
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if config_tag is not None:
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config = config["config"]
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if self.skip_validation is True:
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self.config = config
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self._init_config()
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else: # TODO implement validator
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print("Do validation")
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def flush(self):
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"""Reset current plot"""
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self.database = self._init_database()
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self._init_curves()
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@pyqtSlot(dict, dict)
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def on_scan_segment(self, msg, metadata):
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"""
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Handle new scan segments and saves data to a dictionary. Linked through bec_dispatcher.
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Args:
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msg (dict): Message received with scan data.
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metadata (dict): Metadata of the scan.
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"""
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# TODO check if this is correct
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current_scan_id = msg.get("scan_id", None)
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if current_scan_id is None:
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return
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if current_scan_id != self.scan_id:
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self.scan_id = current_scan_id
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self.scan_data = self.queue.scan_storage.find_scan_by_ID(self.scan_id)
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if not self.scan_data:
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print(f"No data found for scan_id: {self.scan_id}") # TODO better error
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return
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self.flush()
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# Update the database with new data
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self.update_database_with_scan_data(msg)
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# Emit signal to update plot #TODO could be moved to update_database_with_scan_data just for coresponding plot name
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self.update_signal.emit()
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def update_database_with_scan_data(self, msg):
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"""
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Update the database with data from the new scan segment.
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Args:
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msg (dict): Message containing the new scan data.
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"""
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data = msg.get("data", {})
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for plot_config in self.plot_data: # Iterate over the list
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plot_name = plot_config["plot_name"]
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x_signal = plot_config["signals"]["x"][0]["name"]
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y_signal = plot_config["signals"]["y"][0]["name"]
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z_signal = plot_config["signals"]["z"][0]["name"]
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if x_signal in data and y_signal in data and z_signal in data:
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x_value = data[x_signal][x_signal]["value"]
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y_value = data[y_signal][y_signal]["value"]
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z_value = data[z_signal][z_signal]["value"]
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# Update database for the corresponding plot
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self.database[plot_name]["x"][x_signal].append(x_value)
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self.database[plot_name]["y"][y_signal].append(y_value)
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self.database[plot_name]["z"][z_signal].append(z_value)
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def update_plot(self):
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"""
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Update the plots with the latest data from the database.
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"""
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for plot_name, scatterPlot in self.scatterPlots.items():
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x_data = self.database[plot_name]["x"]
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y_data = self.database[plot_name]["y"]
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z_data = self.database[plot_name]["z"]
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if x_data and y_data and z_data:
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# Extract values for each axis
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x_values = next(iter(x_data.values()), [])
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y_values = next(iter(y_data.values()), [])
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z_values = next(iter(z_data.values()), [])
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# Check if the data lists are not empty
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if x_values and y_values and z_values:
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# Normalize z_values for color mapping
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z_min, z_max = np.min(z_values), np.max(z_values)
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if z_max != z_min: # Ensure that there is a range in the z values
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z_values_norm = (z_values - z_min) / (z_max - z_min)
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colormap = pg.colormap.get(
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self.colormap
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) # using colormap from global settings
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colors = [colormap.map(z) for z in z_values_norm]
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# Update scatter plot data with colors
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scatterPlot.setData(x=x_values, y=y_values, brush=colors)
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else:
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# Handle case where all z values are the same (e.g., avoid division by zero)
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scatterPlot.setData(x=x_values, y=y_values) # Default brush can be used
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if __name__ == "__main__": # pragma: no cover
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import argparse
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import json
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import sys
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parser = argparse.ArgumentParser()
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parser.add_argument("--config_file", help="Path to the config file.")
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parser.add_argument("--config", help="Path to the config file.")
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parser.add_argument("--id", help="GUI ID.")
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args = parser.parse_args()
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if args.config is not None:
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# Load config from file
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config = json.loads(args.config)
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elif args.config_file is not None:
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# Load config from file
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config = yaml_dialog.load_yaml(args.config_file)
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else:
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config = CONFIG_DEFAULT
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client = BECDispatcher().client
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client.start()
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app = QApplication(sys.argv)
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monitor = BECMonitor2DScatter(config=config, gui_id=args.id, skip_validation=True)
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monitor.show()
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sys.exit(app.exec())
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@ -1,162 +0,0 @@
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# pylint: disable=missing-module-docstring, missing-function-docstring
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||||||
from collections import defaultdict
|
|
||||||
from unittest.mock import MagicMock
|
|
||||||
|
|
||||||
import pytest
|
|
||||||
from qtpy import QtGui
|
|
||||||
|
|
||||||
from bec_widgets.widgets import BECMonitor2DScatter
|
|
||||||
|
|
||||||
CONFIG_DEFAULT = {
|
|
||||||
"plot_settings": {"colormap": "CET-L4", "num_columns": 1},
|
|
||||||
"waveform2D": [
|
|
||||||
{
|
|
||||||
"plot_name": "Waveform 2D Scatter (1)",
|
|
||||||
"x_label": "Sam X",
|
|
||||||
"y_label": "Sam Y",
|
|
||||||
"signals": {
|
|
||||||
"x": [{"name": "samx", "entry": "samx"}],
|
|
||||||
"y": [{"name": "samy", "entry": "samy"}],
|
|
||||||
"z": [{"name": "gauss_bpm", "entry": "gauss_bpm"}],
|
|
||||||
},
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"plot_name": "Waveform 2D Scatter (2)",
|
|
||||||
"x_label": "Sam X",
|
|
||||||
"y_label": "Sam Y",
|
|
||||||
"signals": {
|
|
||||||
"x": [{"name": "samy", "entry": "samy"}],
|
|
||||||
"y": [{"name": "samx", "entry": "samx"}],
|
|
||||||
"z": [{"name": "gauss_bpm", "entry": "gauss_bpm"}],
|
|
||||||
},
|
|
||||||
},
|
|
||||||
],
|
|
||||||
}
|
|
||||||
|
|
||||||
CONFIG_ONE_PLOT = {
|
|
||||||
"plot_settings": {"colormap": "CET-L4", "num_columns": 1},
|
|
||||||
"waveform2D": [
|
|
||||||
{
|
|
||||||
"plot_name": "Waveform 2D Scatter (1)",
|
|
||||||
"x_label": "Sam X",
|
|
||||||
"y_label": "Sam Y",
|
|
||||||
"signals": {
|
|
||||||
"x": [{"name": "aptrx", "entry": "aptrx"}],
|
|
||||||
"y": [{"name": "aptry", "entry": "aptry"}],
|
|
||||||
"z": [{"name": "gauss_bpm", "entry": "gauss_bpm"}],
|
|
||||||
},
|
|
||||||
}
|
|
||||||
],
|
|
||||||
}
|
|
||||||
|
|
||||||
|
|
||||||
@pytest.fixture(scope="function")
|
|
||||||
def monitor_2Dscatter(qtbot):
|
|
||||||
client = MagicMock()
|
|
||||||
widget = BECMonitor2DScatter(client=client)
|
|
||||||
qtbot.addWidget(widget)
|
|
||||||
qtbot.waitExposed(widget)
|
|
||||||
yield widget
|
|
||||||
|
|
||||||
|
|
||||||
@pytest.mark.parametrize("config, number_of_plots", [(CONFIG_DEFAULT, 2), (CONFIG_ONE_PLOT, 1)])
|
|
||||||
def test_initialization(monitor_2Dscatter, config, number_of_plots):
|
|
||||||
config_load = config
|
|
||||||
monitor_2Dscatter.on_config_update(config_load)
|
|
||||||
assert isinstance(monitor_2Dscatter, BECMonitor2DScatter)
|
|
||||||
assert monitor_2Dscatter.client is not None
|
|
||||||
assert monitor_2Dscatter.config == config_load
|
|
||||||
assert len(monitor_2Dscatter.plot_data) == number_of_plots
|
|
||||||
|
|
||||||
|
|
||||||
@pytest.mark.parametrize("config ", [(CONFIG_DEFAULT), (CONFIG_ONE_PLOT)])
|
|
||||||
def test_database_initialization(monitor_2Dscatter, config):
|
|
||||||
monitor_2Dscatter.on_config_update(config)
|
|
||||||
# Check if the database is a defaultdict
|
|
||||||
assert isinstance(monitor_2Dscatter.database, defaultdict)
|
|
||||||
for axis_dict in monitor_2Dscatter.database.values():
|
|
||||||
assert isinstance(axis_dict, defaultdict)
|
|
||||||
for signal_list in axis_dict.values():
|
|
||||||
assert isinstance(signal_list, defaultdict)
|
|
||||||
|
|
||||||
# Access the elements
|
|
||||||
for plot_config in config["waveform2D"]:
|
|
||||||
plot_name = plot_config["plot_name"]
|
|
||||||
|
|
||||||
for axis in ["x", "y", "z"]:
|
|
||||||
for signal in plot_config["signals"][axis]:
|
|
||||||
signal_name = signal["name"]
|
|
||||||
assert not monitor_2Dscatter.database[plot_name][axis][signal_name]
|
|
||||||
assert isinstance(monitor_2Dscatter.database[plot_name][axis][signal_name], list)
|
|
||||||
|
|
||||||
|
|
||||||
@pytest.mark.parametrize("config ", [(CONFIG_DEFAULT), (CONFIG_ONE_PLOT)])
|
|
||||||
def test_ui_initialization(monitor_2Dscatter, config):
|
|
||||||
monitor_2Dscatter.on_config_update(config)
|
|
||||||
assert len(monitor_2Dscatter.plots) == len(config["waveform2D"])
|
|
||||||
for plot_config in config["waveform2D"]:
|
|
||||||
plot_name = plot_config["plot_name"]
|
|
||||||
assert plot_name in monitor_2Dscatter.plots
|
|
||||||
plot = monitor_2Dscatter.plots[plot_name]
|
|
||||||
assert plot.titleLabel.text == plot_name
|
|
||||||
|
|
||||||
|
|
||||||
def simulate_scan_data(monitor, x_value, y_value, z_value):
|
|
||||||
"""Helper function to simulate scan data input with three devices."""
|
|
||||||
msg = {
|
|
||||||
"data": {
|
|
||||||
"samx": {"samx": {"value": x_value}},
|
|
||||||
"samy": {"samy": {"value": y_value}},
|
|
||||||
"gauss_bpm": {"gauss_bpm": {"value": z_value}},
|
|
||||||
},
|
|
||||||
"scan_id": 1,
|
|
||||||
}
|
|
||||||
monitor.on_scan_segment(msg, {})
|
|
||||||
|
|
||||||
|
|
||||||
def test_data_update_and_plotting(monitor_2Dscatter, qtbot):
|
|
||||||
monitor_2Dscatter.on_config_update(CONFIG_DEFAULT)
|
|
||||||
data_sets = [(1, 4, 7), (2, 5, 8), (3, 6, 9)] # (x, y, z) tuples
|
|
||||||
plot_name = "Waveform 2D Scatter (1)"
|
|
||||||
|
|
||||||
for x, y, z in data_sets:
|
|
||||||
simulate_scan_data(monitor_2Dscatter, x, y, z)
|
|
||||||
qtbot.wait(100) # Wait for the plot to update
|
|
||||||
|
|
||||||
# Retrieve the plot and check if the number of data points matches
|
|
||||||
scatterPlot = monitor_2Dscatter.scatterPlots[plot_name]
|
|
||||||
assert len(scatterPlot.data) == len(data_sets)
|
|
||||||
|
|
||||||
# Check if the data in the database matches the sent data
|
|
||||||
x_data = [
|
|
||||||
point
|
|
||||||
for points_list in monitor_2Dscatter.database[plot_name]["x"].values()
|
|
||||||
for point in points_list
|
|
||||||
]
|
|
||||||
y_data = [
|
|
||||||
point
|
|
||||||
for points_list in monitor_2Dscatter.database[plot_name]["y"].values()
|
|
||||||
for point in points_list
|
|
||||||
]
|
|
||||||
z_data = [
|
|
||||||
point
|
|
||||||
for points_list in monitor_2Dscatter.database[plot_name]["z"].values()
|
|
||||||
for point in points_list
|
|
||||||
]
|
|
||||||
|
|
||||||
assert x_data == [x for x, _, _ in data_sets]
|
|
||||||
assert y_data == [y for _, y, _ in data_sets]
|
|
||||||
assert z_data == [z for _, _, z in data_sets]
|
|
||||||
|
|
||||||
|
|
||||||
def test_color_mapping(monitor_2Dscatter, qtbot):
|
|
||||||
monitor_2Dscatter.on_config_update(CONFIG_DEFAULT)
|
|
||||||
data_sets = [(1, 4, 7), (2, 5, 8), (3, 6, 9)] # (x, y, z) tuples
|
|
||||||
for x, y, z in data_sets:
|
|
||||||
simulate_scan_data(monitor_2Dscatter, x, y, z)
|
|
||||||
qtbot.wait(100) # Wait for the plot to update
|
|
||||||
|
|
||||||
scatterPlot = monitor_2Dscatter.scatterPlots["Waveform 2D Scatter (1)"]
|
|
||||||
|
|
||||||
# Check if colors are applied
|
|
||||||
assert all(isinstance(point.brush().color(), QtGui.QColor) for point in scatterPlot.points())
|
|
||||||
Reference in New Issue
Block a user