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https://github.com/bec-project/bec_widgets.git
synced 2025-07-13 19:21:50 +02:00
refactor: improve plotting behaviour from history
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@ -1098,17 +1098,20 @@ class Waveform(PlotBase):
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if len(np.shape(device_data)) > 1:
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device_data = device_data[-1, :]
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x_data = self._get_x_data(device_name, device_entry)
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if device_data is None:
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logger.warning(f"Async data for curve {curve.name()} is None.")
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continue
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# Async curves only support plotting vs index or other device
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if self.x_axis_mode["name"] in ["timestamp", "index", "auto"]:
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device_data_x = np.linspace(0, len(device_data) - 1, len(device_data))
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else:
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# Fetch data from signal instead
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device_data_x = self._get_x_data(device_name, device_entry)
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self._auto_adjust_async_curve_settings(curve, len(device_data))
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curve.setData(device_data_x, device_data)
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# If there's actual data, set it
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if device_data is not None:
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self._auto_adjust_async_curve_settings(curve, len(device_data))
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if x_data is not None or self.x_axis_mode["name"] == "timestamp":
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curve.setData(x_data, device_data)
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else:
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curve.setData(
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np.linspace(0, len(device_data) - 1, len(device_data)), device_data
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)
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self.request_dap_update.emit()
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def _setup_async_curve(self, curve: Curve):
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@ -1137,69 +1140,72 @@ class Waveform(PlotBase):
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@SafeSlot(dict, dict)
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def on_async_readback(self, msg, metadata):
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"""
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Get async data readback.
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Get async data readback. This code needs to be fast, therefor we try
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to reduce the number of copies in between cycles. Be careful when refactoring
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this part as it will affect the performance of the async readback.
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Note:
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We create data_plot_x and data_plot_y and modify them within this function
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to avoid creating new arrays. This is important for performance.
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We adjust the variables based on instruction type.
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- add: Add the new data to the existing data.
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- add_slice: Add the new data to the existing data and set the slice index.
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- replace: Replace the existing data with the new data.
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Args:
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msg(dict): Message with the async data.
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metadata(dict): Metadata of the message.
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"""
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instruction = metadata.get("async_update", {}).get("type")
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if instruction not in ["add", "add_slice", "replace"]:
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logger.warning(f"Invalid async update instruction: {instruction}")
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return
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max_shape = metadata.get("async_update", {}).get("max_shape", [])
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plot_mode = self.x_axis_mode["name"]
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for curve in self._async_curves:
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new_data = None
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y_data = None
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x_data = None
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x_name = self.x_axis_mode["name"]
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x_data = None # Reset x_data
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# Get the curve data
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async_data = msg["signals"].get(curve.config.signal.entry, None)
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if async_data is None:
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continue
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data_plot = async_data["value"]
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# y-data
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data_plot_y = async_data["value"]
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if data_plot_y is None:
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logger.warning(f"Async data for curve {curve.name()} is None.")
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continue
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# Add
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if instruction == "add":
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if len(max_shape) > 1:
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if len(data_plot.shape) > 1:
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data_plot = data_plot[-1, :]
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# Ensure that data_plot_y is numpy array, this avoids copying if data_plot_y is already a numpy array
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data_plot_y = np.asarray(data_plot_y)
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if len(data_plot_y.shape) > 1:
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data_plot_y = data_plot_y[-1, :]
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else:
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x_data, y_data = curve.get_data()
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if y_data is not None:
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new_data = np.hstack((y_data, data_plot)) # TODO check performance
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else:
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new_data = data_plot
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if x_name == "timestamp":
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if x_data is not None:
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x_data = np.hstack((x_data, async_data["timestamp"]))
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else:
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x_data = async_data["timestamp"]
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# FIXME x axis wrong if timestamp switched during scan
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if y_data is not None:
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data_plot_y = np.hstack((y_data, data_plot_y))
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# Add slice
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elif instruction == "add_slice":
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if instruction == "add_slice":
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current_slice_id = metadata.get("async_update", {}).get("index")
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data_plot = async_data["value"]
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if current_slice_id != curve.slice_index:
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curve.slice_index = current_slice_id
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else:
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x_data, y_data = curve.get_data()
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if y_data is not None:
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new_data = np.hstack((y_data, data_plot))
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else:
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new_data = data_plot
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# Replace
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elif instruction == "replace":
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if x_name == "timestamp":
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x_data = async_data["timestamp"]
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new_data = data_plot
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if y_data is not None:
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data_plot_y = np.hstack((y_data, data_plot_y))
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# If update is not add, add_slice or replace, continue.
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if new_data is None:
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continue
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# Hide symbol, activate downsampling if data >1000
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self._auto_adjust_async_curve_settings(curve, len(new_data))
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# Set data on the curve
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if x_name == "timestamp" and instruction != "add_slice":
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curve.setData(x_data, new_data)
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# Replace is trivial, no need to modify data_plot_y
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# Get the x data if 'timestamp' is selected, otherwise compute it
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data_plot_x = async_data["timestamp"]
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if plot_mode == "timestamp" and instruction != "add_slice":
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if data_plot_x is not None and x_data is not None:
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data_plot_x = np.hstack((x_data, data_plot_x))
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else:
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curve.setData(np.linspace(0, len(new_data) - 1, len(new_data)), new_data)
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data_plot_x = np.linspace(0, len(data_plot_y) - 1, len(data_plot_y))
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# Set the x data
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self._auto_adjust_async_curve_settings(curve, len(data_plot_y))
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curve.setData(data_plot_x, data_plot_y)
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self.request_dap_update.emit()
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