update: new streamlit layout and fixed processing

README.md

@@ -5,7 +5,7 @@ colorFrom: indigo
 colorTo: gray
 sdk: streamlit
 sdk_version: 1.21.0
-app_file: app.py
+app_file: aira/streamlit_app.py
 pinned: false
 license: gpl-2.0
 ---

aira/core.py

@@ -16,27 +16,18 @@ from aira.engine.reflections import detect_reflections
 from aira.utils import read_signals_dict, cartesian_to_spherical
 
 
-INTEGRATION_TIME = 0.005
-INTENSITY_THRESHOLD = -60
-ANALYSIS_LENGTH = 1
-
-
 @dataclass
 class AmbisonicsImpulseResponseAnalyzer:
     """Main class for analyzing Ambisonics impulse responses"""
 
-    integration_time: float = INTEGRATION_TIME
-    intensity_threshold: float = INTENSITY_THRESHOLD
-    analysis_length: float = ANALYSIS_LENGTH
-    bformat_frequency_correction: bool = True
     input_builder = InputProcessorChain()
 
     def analyze(
         self,
         input_dict: dict,
-        integration_time: float = INTEGRATION_TIME,
-        intensity_threshold: float = INTENSITY_THRESHOLD,
-        analysis_length: float = ANALYSIS_LENGTH,
+        integration_time: float,
+        intensity_threshold: float,
+        analysis_length: float,
         show: bool = False,
     ) -> go.Figure:
         """Analyzes a set of measurements in Ambisonics format and plots a hedgehog
@@ -150,7 +141,15 @@ if __name__ == "__main__":
     #     "channels_per_file": 4,
     #     "frequency_correction": False,
     # }
-
+    integration_time = 0.01
+    intensity_threshold = -50
+    analysis_length = 0.3
     analyzer = AmbisonicsImpulseResponseAnalyzer()
-    fig = analyzer.analyze(data, show=True)
+    fig = analyzer.analyze(
+        input_dict=data,
+        integration_time=integration_time,
+        intensity_threshold=intensity_threshold,
+        analysis_length=analysis_length,
+        show=True,
+    )
     analyzer.export_xy_projection(fig, "projection.png")

aira/engine/plot.py

@@ -145,6 +145,7 @@ def setup_plotly_layout() -> go.Figure:
     _type_
         _description_
     """
+    initial_fig = go.Figure()
     fig = make_subplots(
         rows=2,
         cols=1,
@@ -152,6 +153,7 @@ def setup_plotly_layout() -> go.Figure:
         vertical_spacing=0.05,
         specs=[[{"type": "scene"}], [{"type": "xy"}]],
         subplot_titles=("<b>Hedgehog</b>", "<b>Omnidirectional channel</b>"),
+        figure=initial_fig,
     )
 
     camera, buttons = get_plotly_scenes()

aira/{gui.py → pyqt_gui.py}

@@ -12,26 +12,21 @@ from PyQt5 import QtCore, QtGui, QtWidgets, QtWebEngineWidgets
 from PyQt5.QtWidgets import (
     QLabel,
     QFileDialog,
-    QMessageBox,
 )
-from PyQt5.QtGui import QPixmap
-from PyQt5.QtCore import Qt
-import os
+from PyQt5.QtGui import QPixmap, QPainter, QImage
+from PyQt5.QtCore import Qt, QPoint
+
 from pathlib import Path
 
 from aira.core import AmbisonicsImpulseResponseAnalyzer
 from aira.engine.input import InputMode
 
-INTEGRATION_TIME = 0.01
-
-analyzer = AmbisonicsImpulseResponseAnalyzer(integration_time=INTEGRATION_TIME)
-
 
 class Ui_MainWindow(object):
     def setupUi(self, MainWindow):
         MainWindow.setObjectName("MainWindow")
         MainWindow.resize(1350, 727)
-        MainWindow.setMinimumSize(QtCore.QSize(1000, 800))
+        MainWindow.setMinimumSize(QtCore.QSize(1200, 900))
         MainWindow.setWindowIcon(QtGui.QIcon(str(Path("docs/images/aira-icon.png"))))
         self.centralwidget = QtWidgets.QWidget(MainWindow)
         self.centralwidget.setStyleSheet("background-color:#313438 ; ")
@@ -258,7 +253,6 @@ class Ui_MainWindow(object):
         font.setPointSize(12)
         self.rB_1ms.setFont(font)
         self.rB_1ms.setObjectName("rB_1ms")
-        self.rB_1ms.setChecked(True)
         self.verticalLayout_6.addWidget(self.rB_1ms)
         self.rB_5ms = QtWidgets.QRadioButton(self.frame_analyze)
         palette = QtGui.QPalette()
@@ -304,6 +298,7 @@ class Ui_MainWindow(object):
         font.setPointSize(12)
         self.rB_5ms.setFont(font)
         self.rB_5ms.setObjectName("rB_5ms")
+        self.rB_5ms.setChecked(True)
         self.verticalLayout_6.addWidget(self.rB_5ms)
         self.rB_10ms = QtWidgets.QRadioButton(self.frame_analyze)
         palette = QtGui.QPalette()
@@ -427,7 +422,7 @@ class Ui_MainWindow(object):
         self.label_analysis_length.setObjectName("label_analysis_length")
         self.verticalLayout_6.addWidget(self.label_analysis_length)
         self.lineEdit_aLength = QtWidgets.QLineEdit(self.frame_analyze)
-        self.lineEdit_aLength.setText("100")
+        self.lineEdit_aLength.setText("500")
         font = QtGui.QFont()
         font.setFamily("Lato")
         font.setPointSize(10)
@@ -494,7 +489,7 @@ class Ui_MainWindow(object):
         self.lineEdit_threshold.setStyleSheet(
             "background-color: rgb(255, 255, 255);\n" "\n" ""
         )
-        self.lineEdit_threshold.setText("60")
+        self.lineEdit_threshold.setText("-60")
         self.lineEdit_threshold.setObjectName("lineEdit_threshold")
         self.verticalLayout_6.addWidget(self.lineEdit_threshold)
         spacerItem5 = QtWidgets.QSpacerItem(
@@ -559,19 +554,9 @@ class Ui_MainWindow(object):
         self.verticalLayout_8 = QtWidgets.QVBoxLayout(self.frame_hedgehog)
         self.verticalLayout_8.setContentsMargins(0, 0, 0, 0)
         self.verticalLayout_8.setObjectName("verticalLayout_8")
-        self.frame_hedgehog_label = QtWidgets.QFrame(self.frame_hedgehog)
-        self.frame_hedgehog_label.setMaximumSize(QtCore.QSize(16777215, 42))
-        self.frame_hedgehog_label.setFrameShape(QtWidgets.QFrame.StyledPanel)
-        self.frame_hedgehog_label.setFrameShadow(QtWidgets.QFrame.Raised)
-        self.frame_hedgehog_label.setObjectName("frame_hedgehog_label")
-        self.horizontalLayout_2 = QtWidgets.QHBoxLayout(self.frame_hedgehog_label)
-        self.horizontalLayout_2.setContentsMargins(0, 0, 0, 0)
-        self.horizontalLayout_2.setObjectName("horizontalLayout_2")
         spacerItem11 = QtWidgets.QSpacerItem(
             430, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum
         )
-        self.horizontalLayout_2.addItem(spacerItem11)
-        self.label_hedgehog = QtWidgets.QLabel(self.frame_hedgehog_label)
         palette = QtGui.QPalette()
         brush = QtGui.QBrush(QtGui.QColor(69, 113, 213))
         brush.setStyle(QtCore.Qt.SolidPattern)
@@ -609,19 +594,12 @@ class Ui_MainWindow(object):
         brush = QtGui.QBrush(QtGui.QColor(49, 52, 56))
         brush.setStyle(QtCore.Qt.SolidPattern)
         palette.setBrush(QtGui.QPalette.Disabled, QtGui.QPalette.Window, brush)
-        self.label_hedgehog.setPalette(palette)
         font = QtGui.QFont()
         font.setFamily("Lato")
         font.setPointSize(15)
-        self.label_hedgehog.setFont(font)
-        self.label_hedgehog.setAlignment(QtCore.Qt.AlignCenter)
-        self.label_hedgehog.setObjectName("label_hedgehog")
-        self.horizontalLayout_2.addWidget(self.label_hedgehog)
         spacerItem12 = QtWidgets.QSpacerItem(
             429, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum
         )
-        self.horizontalLayout_2.addItem(spacerItem12)
-        self.verticalLayout_8.addWidget(self.frame_hedgehog_label)
         self.frame_hedgehog_plot = QtWidgets.QFrame(self.frame_hedgehog)
         self.frame_hedgehog_plot.setFrameShape(QtWidgets.QFrame.StyledPanel)
         self.frame_hedgehog_plot.setFrameShadow(QtWidgets.QFrame.Raised)
@@ -646,6 +624,7 @@ class Ui_MainWindow(object):
         self.verticalLayout_10.setObjectName("verticalLayout_10")
         self.frame_plan_header = QtWidgets.QFrame(self.frame_tab_plan)
         self.frame_plan_header.setMaximumSize(QtCore.QSize(16777215, 60))
+        self.frame_plan_header.setMinimumSize(QtCore.QSize(0, 60))
         self.frame_plan_header.setFrameShape(QtWidgets.QFrame.StyledPanel)
         self.frame_plan_header.setFrameShadow(QtWidgets.QFrame.Raised)
         self.frame_plan_header.setObjectName("frame_plan_header")
@@ -683,7 +662,6 @@ class Ui_MainWindow(object):
         self.label_plan_view.setPixmap(
             pixmap.scaled(750, 3000, aspectRatioMode=Qt.KeepAspectRatio)
         )
-        # self.label_plan_view.addWidget(self.label_plan_view)
         self.horizontalLayout_6.addWidget(self.label_plan_view)
         self.horizontalLayout_5.addWidget(self.frame_plan_view)
         self.verticalLayout_10.addWidget(self.frame_view)
@@ -812,7 +790,7 @@ class Ui_MainWindow(object):
 
         # CONEXIONES DE GUI CON ACCIONES
 
-        # Creo los labels para guardar la data que devuelven las funciones de import triggereadas
+        # Labels para guardar la data que devuelven las funciones de import triggereadas
         self.path_1 = QLabel()
         self.path_2 = QLabel()
         self.path_3 = QLabel()
@@ -834,10 +812,11 @@ class Ui_MainWindow(object):
         self.actionImport_Bformat_4channels.triggered.connect(
             self.import_Bformat_4channels
         )
-
+        self.actionExport_hedgehog_plot.triggered.connect(self.export_hedgehog)
         self.pb_analyze.clicked.connect(self.analyze)
         self.pB_load_plan.clicked.connect(self.load_plan)
         self.pB_export_plan.clicked.connect(self.export_plan)
+        self.label_plan_view.mousePressEvent = lambda event: self.mousePressEvent(event)
 
     def retranslateUi(self, MainWindow):
         _translate = QtCore.QCoreApplication.translate
@@ -855,7 +834,7 @@ class Ui_MainWindow(object):
         )
         self.label_threshold.setText(_translate("MainWindow", "Threshold [dB]"))
         self.pb_analyze.setText(_translate("MainWindow", "Analyze"))
-        self.label_hedgehog.setText(_translate("MainWindow", "Hedgehog Plot"))
+
         self.tabWidget.setTabText(
             self.tabWidget.indexOf(self.tab_main), _translate("MainWindow", "Main")
         )
@@ -950,7 +929,7 @@ class Ui_MainWindow(object):
                     "channel_Z": Z_path,
                     "input_mode": input_mode,
                     "channels_per_file": channels_per_file,
-                    "frequency_correction": True,
+                    "frequency_correction": False,
                 }
             else:
                 B4_path = self.path_1.text()
@@ -959,11 +938,31 @@ class Ui_MainWindow(object):
                     "stacked_signals": B4_path,
                     "input_mode": input_mode,
                     "channels_per_file": channels_per_file,
-                    "frequency_correction": True,
+                    "frequency_correction": False,
                 }
 
-        fig = analyzer.analyze(input_dict=data)
-        self.gV_hedgehog.setHtml(fig.to_html(include_plotlyjs="cdn"))
+        if self.rB_1ms.isChecked():
+            integration_time = 0.001
+        elif self.rB_5ms.isChecked():
+            integration_time = 0.005
+        else:
+            integration_time = 0.01
+
+        intensity_threshold = float(self.lineEdit_threshold.text())
+        analysis_length = float(self.lineEdit_aLength.text()) / 1000
+
+        analyzer = AmbisonicsImpulseResponseAnalyzer()
+        fig = analyzer.analyze(
+            input_dict=data,
+            integration_time=integration_time,
+            intensity_threshold=intensity_threshold,
+            analysis_length=analysis_length,
+        )
+        analyzer.export_xy_projection(fig, "projection.png")
+        fig.write_html("out.html")
+        url = QtCore.QUrl.fromLocalFile(str(Path("out.html").resolve()))
+        self.gV_hedgehog.load(url)
+        self.plotly_fig = fig
 
     def load_plan(self):
         file_dialog = QFileDialog()
@@ -971,12 +970,52 @@ class Ui_MainWindow(object):
             MainWindow, "Select image", "", "Image file (*.png *.jpg *.jpeg)"
         )
         if file_path:
-            pixmap = QPixmap(file_path)
-            self.label_plan_view.setPixmap(
-                pixmap.scaled(750, 3000, aspectRatioMode=Qt.KeepAspectRatio)
+            # Cargar la imagen base
+            self.base_image = QImage(file_path)
+            scaled_image = self.base_image.scaled(
+                1000, 800, Qt.AspectRatioMode.KeepAspectRatio
             )
+
+            # Crear una imagen resultante del mismo tamaño que la imagen base
+            self.result_image = QImage(scaled_image.size(), QImage.Format_ARGB32)
+            self.result_image.fill(0)  # Rellenar con transparencia
+
+            # Mostrar la imagen base en un QLabel
+            self.label_plan_view.setPixmap(QPixmap.fromImage(scaled_image))
+
+            # Ajustar el tamaño del QLabel al tamaño de la imagen base escalada
+            self.label_plan_view.resize(scaled_image.size())
+
             self.enable_export()
 
+    def mousePressEvent(self, event):
+        if event.button() == Qt.LeftButton:
+            # Verificar si el clic ocurrió dentro de los límites de la imagen base
+            if (
+                event.x() < self.base_image.width()
+                and event.y() < self.base_image.height()
+            ):
+                # Cargar la imagen superpuesta
+                overlay_image = QImage("projection.png")
+                overlay_position = QPoint(event.x() - 787, event.y() - 350)
+
+                # Dibujar la imagen base en la imagen resultante
+                painter = QPainter(self.result_image)
+                painter.drawImage(
+                    0,
+                    0,
+                    self.base_image.scaled(
+                        1000, 800, Qt.AspectRatioMode.KeepAspectRatio
+                    ),
+                )
+
+                # Dibujar la imagen superpuesta en la imagen resultante
+                painter.drawImage(overlay_position, overlay_image)
+                painter.end()
+
+                # Mostrar la imagen resultante en el QLabel
+                self.label_plan_view.setPixmap(QPixmap.fromImage(self.result_image))
+
     def enable_export(self):
         self.pB_export_plan.setEnabled(True)
         self.pB_export_plan.setStyleSheet(
@@ -999,6 +1038,8 @@ class Ui_MainWindow(object):
         save_path, _ = file_dialog.getSaveFileName(
             MainWindow, "Export image", "", "Image file (*.png *.jpg *.jpeg)"
         )
+        if save_path:
+            self.result_image.save(save_path)
 
     def import_Aformat_1channel(self):
         file_dialog = QFileDialog()
@@ -1090,6 +1131,7 @@ class Ui_MainWindow(object):
         save_path, _ = file_dialog.getSaveFileName(
             MainWindow, "Export image", "", "Image file (*.png *.jpg *.jpeg)"
         )
+        self.plotly_fig.write_image(save_path, "png", width=1366, height=768, scale=1.0)
 
 
 if __name__ == "__main__":

app.py → aira/streamlit_app.py

@@ -1,9 +1,9 @@
+import os
+import tempfile
 import streamlit as st
-import plotly.graph_objects as go
+
 from aira.core import AmbisonicsImpulseResponseAnalyzer
 from aira.engine.input import InputMode
-import os
-import tempfile
 
 
 def save_temp_file(file):
@@ -23,14 +23,24 @@ def run_streamlit_app():
     logo_path = "docs/images/aira-banner.png"
     personal_logo_path = "docs/images/nahue-passano.png"
     st.columns(11)[10].image(personal_logo_path, use_column_width=True)
-    st.columns(3)[1].image(logo_path, use_column_width=True)
 
     # Audio loading and settings
 
-    audio_files, settings = st.columns(2)
+    settings, audio_files = st.columns(2)
+
+    with settings:
+        st.image(logo_path, use_column_width=True)
+        st.subheader("⚙️ Settings")
+        col1, col2, col3 = st.columns(3)
+        with col1:
+            integration_time = st.selectbox("Integration time [ms]", [1, 5, 10])
+        with col2:
+            analysis_length = st.text_input("Analysis length [ms]", value="500")
+        with col3:
+            intensity_threshold = st.text_input("Intensity threshold [dB]", value=-60)
 
     with audio_files:
-        st.header("🔉 LSS room responses in A-Format")
+        st.subheader("🔉 LSS room responses in A-Format")
         up_files, down_files = st.columns(2)
 
         with up_files:
@@ -45,37 +55,32 @@ def run_streamlit_app():
             "Inverse filter", type=["mp3", "wav"]
         )
 
-    with settings:
-        st.header("⚙️ Settings")
-        integration_time = st.selectbox("Integration time [ms]", [1, 5, 10])
-        analysis_length = st.text_input("Analysis length [ms]", value="500")
-        intensity_threshold = st.text_input("Intensity threshold [dB]", value=-60)
-
-        # "Analyze" button
-        if st.button("Analyze", use_container_width=True):
-            data = {
-                "front_left_up": save_temp_file(audio_file_flu),
-                "front_right_down": save_temp_file(audio_file_frd),
-                "back_right_up": save_temp_file(audio_file_bru),
-                "back_left_down": save_temp_file(audio_file_bld),
-                "inverse_filter": save_temp_file(audio_file_inverse_filter),
-                "input_mode": InputMode.LSS,
-                "channels_per_file": 1,
-                "frequency_correction": True,
-            }
-
-            analyzer = AmbisonicsImpulseResponseAnalyzer(
-                int(integration_time),
-                float(intensity_threshold),
-                float(analysis_length),
-            )
-            fig = analyzer.analyze(data, show=False)
-            fig.update_layout(height=1080)
-            st.plotly_chart(fig, use_container_width=True, height=1080)
-
-            # Generar un gráfico genérico con Plotly
-            fig = go.Figure(data=go.Scatter(x=[1, 2, 3, 4], y=[10, 5, 7, 2]))
-            st.plotly_chart(fig)
+    # "Analyze" button
+    if st.button("Analyze", use_container_width=True):
+        data = {
+            "front_left_up": save_temp_file(audio_file_flu),
+            "front_right_down": save_temp_file(audio_file_frd),
+            "back_right_up": save_temp_file(audio_file_bru),
+            "back_left_down": save_temp_file(audio_file_bld),
+            "inverse_filter": save_temp_file(audio_file_inverse_filter),
+            "input_mode": InputMode.LSS,
+            "channels_per_file": 1,
+            "frequency_correction": True,
+        }
+        analyzer = AmbisonicsImpulseResponseAnalyzer()
+        fig = analyzer.analyze(
+            input_dict=data,
+            integration_time=float(integration_time) / 1000,
+            intensity_threshold=float(intensity_threshold),
+            analysis_length=float(analysis_length) / 1000,
+            show=False,
+        )
+        fig.update_layout(
+            height=1080,
+            paper_bgcolor="rgb(14,17,23)",
+            plot_bgcolor="rgb(14,17,23)",
+        )
+        st.plotly_chart(fig, use_container_width=True, height=1080)
 
 
 if __name__ == "__main__":