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Merge pull request #42 from EIT-ALIVE/037_implement_eeli_wbaccinelli
037 implement eeli wbaccinelli
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,176 @@ | ||
| import contextlib | ||
|
|
||
| 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, RAW_EIT_LABEL | ||
| from eit_dash.utils.common import ( | ||
| create_filter_results_card, | ||
| create_info_card, | ||
| create_selected_period_card, | ||
| ) | ||
|
|
||
| eeli = [] | ||
|
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||
|
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| @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] | ||
|
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| filter_params = {} | ||
|
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| for period in data_object.get_all_stable_periods(): | ||
| 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(), | ||
| }, | ||
| ) | ||
|
|
||
| if not filter_params: | ||
| try: | ||
| filter_params = period.get_data().continuous_data.data[FILTERED_EIT_LABEL].parameters | ||
| except KeyError: | ||
| contextlib.suppress(Exception) | ||
| if filter_params: | ||
| summary += [create_filter_results_card(filter_params)] | ||
|
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| return summary, options | ||
|
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|
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| @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 | ||
|
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| eeli.clear() | ||
|
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| periods = data_object.get_all_stable_periods() | ||
|
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| for period in periods: | ||
| sequence = period.get_data() | ||
| if sequence.continuous_data.get(FILTERED_EIT_LABEL): | ||
| eeli_result_filtered = EELI().compute_parameter( | ||
| sequence, | ||
| FILTERED_EIT_LABEL, | ||
| ) | ||
| else: | ||
| eeli_result_filtered = EELI().compute_parameter(sequence, RAW_EIT_LABEL) | ||
|
|
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| # TODO: the results should be stored in the sequence object | ||
| eeli_result_filtered["index"] = period.get_period_index() | ||
|
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| eeli.append(eeli_result_filtered) | ||
|
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| return False | ||
|
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|
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| @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() | ||
|
|
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| sequence = data_object.get_stable_period(int(selected)).get_data() | ||
| for e in eeli: | ||
| if e["index"] == int(selected): | ||
| result = e | ||
|
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||
| if sequence.continuous_data.get(FILTERED_EIT_LABEL): | ||
| data = sequence.continuous_data.get(FILTERED_EIT_LABEL) | ||
| else: | ||
| data = sequence.continuous_data.get(RAW_EIT_LABEL) | ||
|
|
||
| figure.add_trace( | ||
| go.Scatter( | ||
| x=data.time, | ||
| y=data.values, | ||
| name=data.label, | ||
| ), | ||
| ) | ||
|
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| figure.add_hline(y=result["mean"], line_color="red", name="Mean") | ||
| figure.add_hline(y=result["median"], line_color="red", name="Median") | ||
|
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| figure.add_scatter( | ||
| x=data.time[result["indices"]], | ||
| y=result["values"], | ||
| line_color="black", | ||
| name="EELIs", | ||
| mode="markers", | ||
| ) | ||
|
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| sd_upper = result["mean"] + result["standard deviation"] | ||
| sd_lower = result["mean"] - result["standard deviation"] | ||
|
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| figure.add_trace( | ||
| go.Scatter( | ||
| x=data.time, | ||
| y=[sd_upper] * len(data.time), | ||
| fill=None, | ||
| mode="lines", | ||
| line_color="rgba(0,0,255,0)", # Set to transparent blue | ||
| name="Standard deviation", | ||
| ), | ||
| ) | ||
|
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| # Add the lower bound line | ||
| figure.add_trace( | ||
| go.Scatter( | ||
| x=data.time, | ||
| y=[sd_lower] * len(data.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 |
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