037 implement eeli wbaccinelli

docs/user_manual.md

@@ -72,3 +72,12 @@ the preview will update. When you are happy with a particular setting/selection,
 <kbd>
 <img src=images/preprocessing_filter.png width="800px" style="border: 1px solid black">
 </kbd>
+
+## ANALYZE page
+
+Click `Apply EELI` to run EELI analysis. When the analysis is completed, it is possible to see 
+the results by selecting the period to visualize using the dropdown menu.
+
+<kbd>
+<img src=images/apply_eeli.png width="800px" style="border: 1px solid black">
+</kbd>

eit_dash/callbacks/analyze_callbacks.py

@@ -0,0 +1,164 @@
+import plotly.graph_objects as go
+from dash import Input, Output, State, callback, ctx
+from eitprocessing.parameters.eeli import EELI
+
+import eit_dash.definitions.element_ids as ids
+import eit_dash.definitions.layout_styles as styles
+from eit_dash.app import data_object
+from eit_dash.definitions.constants import FILTERED_EIT_LABEL
+from eit_dash.utils.common import (
+    create_filter_results_card,
+    create_info_card,
+    create_selected_period_card,
+)
+
+eeli = []
+
+
+@callback(
+    Output(ids.SUMMARY_COLUMN_ANALYZE, "children", allow_duplicate=True),
+    Output(ids.ANALYZE_SELECT_PERIOD_VIEW, "options"),
+    [
+        Input(ids.ANALYZE_RESULTS_TITLE, "children"),
+    ],
+    [
+        State(ids.SUMMARY_COLUMN_ANALYZE, "children"),
+    ],
+    # this allows duplicate outputs with initial call
+    prevent_initial_call="initial_duplicate",
+)
+def page_setup(_, summary):
+    """Setups the page elements when it starts up.
+
+    When the page is loaded, it populates the summary column
+    with the info about the loaded datasets and the preprocessing steps.
+    Populates the periods selections element with the loaded periods.
+    """
+    trigger = ctx.triggered_id
+    options = []
+
+    if trigger is None:
+        for d in data_object.get_all_sequences():
+            card = create_info_card(d)
+            summary += [card]
+
+        filter_params = {}
+
+        for period in data_object.get_all_stable_periods():
+            if not filter_params:
+                filter_params = (
+                    period.get_data()
+                    .continuous_data.data[FILTERED_EIT_LABEL]
+                    .parameters
+                )
+
+            summary += [
+                create_selected_period_card(
+                    period.get_data(),
+                    period.get_dataset_index(),
+                    period.get_period_index(),
+                    False,
+                ),
+            ]
+
+            # populate period selection
+            options.append(
+                {
+                    "label": f"Period {period.get_period_index()}",
+                    "value": period.get_period_index(),
+                },
+            )
+
+        summary += [create_filter_results_card(filter_params)]
+
+    return summary, options
+
+
+@callback(
+    Output(ids.EELI_RESULTS_GRAPH_DIV, "hidden"),
+    Input(ids.EELI_APPLY, "n_clicks"),
+    prevent_initial_call=True,
+)
+def apply_eeli(_):
+    """Apply EELI and store results."""
+    global eeli  # noqa: PLW0602
+
+    eeli.clear()
+
+    periods = data_object.get_all_stable_periods()
+
+    for period in periods:
+        sequence = period.get_data()
+        eeli_result_filtered = EELI().compute_parameter(sequence, FILTERED_EIT_LABEL)
+
+        # TODO: the results should be stored in the sequence object
+        eeli_result_filtered["index"] = period.get_period_index()
+
+        eeli.append(eeli_result_filtered)
+
+    return False
+
+
+@callback(
+    [
+        Output(ids.EELI_RESULTS_GRAPH, "figure"),
+        Output(ids.EELI_RESULTS_GRAPH, "style"),
+    ],
+    Input(ids.ANALYZE_SELECT_PERIOD_VIEW, "value"),
+    prevent_initial_call=True,
+)
+def show_eeli(selected):
+    """Show the results of the EELI for the selected period."""
+    figure = go.Figure()
+
+    sequence = data_object.get_stable_period(int(selected)).get_data()
+    for e in eeli:
+        if e["index"] == int(selected):
+            result = e
+
+    figure.add_trace(
+        go.Scatter(
+            x=sequence.continuous_data[FILTERED_EIT_LABEL].time,
+            y=sequence.continuous_data[FILTERED_EIT_LABEL].values,
+            name=FILTERED_EIT_LABEL,
+        ),
+    )
+
+    figure.add_hline(y=result["mean"], line_color="red", name="Mean")
+    figure.add_hline(y=result["median"], line_color="red", name="Median")
+
+    figure.add_scatter(
+        x=sequence.continuous_data[FILTERED_EIT_LABEL].time[result["indices"]],
+        y=result["values"],
+        line_color="black",
+        name="EELIs",
+        mode="markers",
+    )
+
+    sd_upper = result["mean"] + result["standard deviation"]
+    sd_lower = result["mean"] - result["standard deviation"]
+
+    figure.add_trace(
+        go.Scatter(
+            x=sequence.continuous_data[FILTERED_EIT_LABEL].time,
+            y=[sd_upper] * len(sequence.continuous_data[FILTERED_EIT_LABEL].time),
+            fill=None,
+            mode="lines",
+            line_color="rgba(0,0,255,0)",  # Set to transparent blue
+            name="Standard deviation",
+        ),
+    )
+
+    # Add the lower bound line
+    figure.add_trace(
+        go.Scatter(
+            x=sequence.continuous_data[FILTERED_EIT_LABEL].time,
+            y=[sd_lower] * len(sequence.continuous_data[FILTERED_EIT_LABEL].time),
+            fill="tonexty",  # Fill area below this line
+            mode="lines",
+            line_color="rgba(0,0,255,0.3)",  # Set to semi-transparent blue
+            name="Standard deviation",
+        ),
+    )
+
+    return figure, styles.GRAPH

eit_dash/callbacks/load_callbacks.py

@@ -3,7 +3,6 @@
 import os
 from pathlib import Path
 
-import dash_bootstrap_components as dbc
 import plotly.graph_objects as go
 from dash import ALL, Input, Output, State, callback, ctx, html
 from dash.exceptions import PreventUpdate
@@ -15,9 +14,10 @@
 
 import eit_dash.definitions.element_ids as ids
 from eit_dash.app import data_object
-from eit_dash.definitions import layout_styles as styles
+from eit_dash.definitions.constants import RAW_EIT_LABEL
 from eit_dash.definitions.option_lists import InputFiletypes
 from eit_dash.utils.common import (
+    create_info_card,
     create_slider_figure,
     get_selections_slidebar,
     get_signal_options,
@@ -26,35 +26,6 @@
 file_data: Sequence | None = None
 
 
-def create_info_card(dataset: Sequence, file_type: int) -> dbc.Card:
-    """Create the card with the information on the loaded dataset to be displayed in the Results section.
-
-    Args:
-        dataset: Sequence object containing the selected dataset
-        file_type: Index of the selected type of selected
-    """
-    info_data = {
-        "Name": dataset.eit_data["raw"].path.name,
-        "n_frames": dataset.eit_data["raw"].nframes,
-        "start_time": dataset.eit_data["raw"].time[0],
-        "end_time": dataset.eit_data["raw"].time[-1],
-        "vendor": dataset.eit_data["raw"].vendor,
-        "continuous signals": str(list(dataset.continuous_data)),
-        "path": str(dataset.eit_data["raw"].path),
-    }
-
-    card_list = [
-        html.H4(dataset.label, className="card-title"),
-        html.H6(InputFiletypes(file_type).name, className="card-subtitle"),
-    ]
-    card_list += [
-        dbc.Row(f"{data}: {value}", style=styles.INFO_CARD)
-        for data, value in info_data.items()
-    ]
-
-    return dbc.Card(dbc.CardBody(card_list), id="card-1")
-
-
 # managing the file selection. Confirm button clicked
 @callback(
     Output(ids.CHOOSE_DATA_POPUP, "is_open"),
@@ -134,13 +105,13 @@ def open_data_selector(data, cancel_load, sig, file_type, fig):
 
     trigger = ctx.triggered_id
 
-    # cancelled selection. Reset the data and turn of the data selector
+    # cancelled selection. Reset the data and turn off the data selector
     if trigger == ids.LOAD_CANCEL_BUTTON:
         data = None
         file_data = None
 
     if not data:
-        # this is needed, because a figure object must be returned for the graph, evn if empty
+        # this is needed, because a figure object must be returned for the graph, even if empty
         figure = go.Figure()
         return True, [], figure
 
@@ -160,12 +131,11 @@ def open_data_selector(data, cancel_load, sig, file_type, fig):
 
             figure = create_slider_figure(
                 file_data,
-                ["raw"],
-                list(file_data.continuous_data),
-                True,
+                continuous_data=list(file_data.continuous_data),
+                clickable_legend=True,
             )
 
-        ok = ["raw"]
+        ok = [RAW_EIT_LABEL]
         if sig:
             ok += [options[s]["label"] for s in sig]
 
@@ -205,12 +175,12 @@ def show_info(
             start_sample, stop_sample = get_selections_slidebar(slidebar_stat)
 
             if not start_sample:
-                start_sample = file_data.eit_data["raw"].time[0]
+                start_sample = file_data.continuous_data[RAW_EIT_LABEL].time[0]
             if not stop_sample:
-                stop_sample = file_data.eit_data["raw"].time[-1]
+                stop_sample = file_data.continuous_data[RAW_EIT_LABEL].time[-1]
         else:
-            start_sample = file_data.eit_data["raw"].time[0]
-            stop_sample = file_data.eit_data["raw"].time[-1]
+            start_sample = file_data.continuous_data[RAW_EIT_LABEL].time[0]
+            stop_sample = file_data.continuous_data[RAW_EIT_LABEL].time[-1]
 
         dataset_name = f"Dataset {data_object.get_sequence_list_length()}"
 
@@ -227,8 +197,8 @@ def show_info(
             eit_data_cut.add(data[data_type].select_by_time(start_sample, stop_sample))
 
         for data_type in (data := file_data.continuous_data):
-            # add just the selected signals
-            if data_type in selected:
+            # add just the selected signals and the raw EIT
+            if data_type in selected or data_type == RAW_EIT_LABEL:
                 continuous_data_cut.add(
                     data[data_type].select_by_time(start_sample, stop_sample),
                 )
@@ -244,7 +214,7 @@ def show_info(
         data_object.add_sequence(cut_data)
 
         # create the info summary card
-        card = create_info_card(cut_data, int(filetype))
+        card = create_info_card(cut_data)
 
         # add the card to the current results
         if container_state:
@@ -284,9 +254,7 @@ def list_cwd_files(cwd):
             full_path = Path(cwd) / filepath
 
             is_dir = Path(full_path).is_dir()
-            extension = (
-                filepath.suffix if not filepath.name.startswith(".") else filepath.name
-            )
+            extension = filepath.suffix if not filepath.name.startswith(".") else filepath.name
 
             if is_dir or extension in [".bin", ".txt", ".zri"]:
                 link = html.A(
@@ -320,3 +288,5 @@ def store_clicked_file(n_clicks, title):
     for state in ctx.states_list[0]:
         if state["id"]["index"] == index:
             return state["value"]
+
+    return None