[feature] 修复完整的文件持久化模块，修复add/del的bug
This commit is contained in:
parent
8619d64f3c
commit
49397eb6b2
6
app.py
6
app.py
@ -105,6 +105,10 @@ class MainWindow(QWidget):
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selected_param_name, selected_project_name = self.widget_card.get_selected_param_name()
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logger.info(f"selected_param_name: {selected_param_name}, selected_project_name: {selected_project_name}")
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#to do: 后续需要封装接口
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self.data_manager._store.current_project = selected_project_name
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self.data_manager._store.current_paramter_name = selected_param_name
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if not selected_param_name or not selected_project_name:
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logger.warning("未选择参数或项目")
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return
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@ -164,8 +168,6 @@ class MainWindow(QWidget):
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for project_name in projects:
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# 从数据管理器获取项目数据
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project_data = self.data_manager.get_project(project_name)
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#to do:目前支持一个项目
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self.data_manager._store.current_project = project_name
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if not project_data:
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logger.warning(f"无法加载项目: {project_name}")
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continue
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@ -17,11 +17,10 @@ sys.path.append(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
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from typing import List, Dict, Optional, Any
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from component.widget_filter.Ui_widget_origin import Ui_Widget
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from component.widget_filter.Ui_widget import Ui_Widget
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from component.widget_filter.checkbox_header import SCheckBoxHeaderView
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from component.widget_filter.audio_filter_model import AudioFilterModel, FilterParams, FilterType
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# from component.widget_filter.Ui_widget_origin import Ui_Widget
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from component.widget_filter.Ui_widget import Ui_Widget
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import component.widget_filter.resources
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# from Ui_widget import Ui_Widget
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@ -163,6 +162,7 @@ class AudioFilterWidget(QWidget):
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filter_enabled_changed = Signal(int, bool) # (filter_index, enabled)
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send_params_clicked = Signal() # 发送参数按钮被点击
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get_params_clicked = Signal() # 获取参数按钮被点击
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lineedit_changed = Signal()
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def __init__(self, parent=None):
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super().__init__(parent)
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@ -395,7 +395,7 @@ class AudioFilterWidget(QWidget):
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if mix_left_key in params:
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self.ui.lineEdit_12.setText(str(params[mix_left_key]))
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def _parse_filter_params(self, params: Dict[str, Any]) -> Dict[int, Dict[str, Any]]:
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def _parse_filter_params_old(self, params: Dict[str, Any]) -> Dict[int, Dict[str, Any]]:
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"""解析滤波器参数"""
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filter_params = {}
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for key in params:
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@ -413,6 +413,35 @@ class AudioFilterWidget(QWidget):
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filter_params[filter_num][param_type] = params[key]
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return filter_params
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def _parse_filter_params(self, params: Dict[str, Any]) -> Dict[int, Dict[str, Any]]:
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"""解析滤波器参数"""
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filter_params = {}
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for key in params:
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# 检查是否是滤波器参数
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if any(key.startswith(prefix) for prefix in [
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f'fc{self.channel_id}_',
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f'q{self.channel_id}_',
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f'gain{self.channel_id}_',
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f'slope{self.channel_id}_',
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f'filterType{self.channel_id}_',
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f'enable{self.channel_id}_',
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f'name{self.channel_id}_'
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]):
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filter_num = int(key.split('_')[-1])
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if filter_num not in filter_params:
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filter_params[filter_num] = {}
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# 提取参数类型（移除channel_id和filter_num）
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if f'enable{self.channel_id}_' in key:
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filter_params[filter_num]['enable'] = params[key]
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elif f'name{self.channel_id}_' in key:
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filter_params[filter_num]['name'] = params[key]
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else:
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param_type = key.split('_')[0][:-len(str(self.channel_id))]
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filter_params[filter_num][param_type] = params[key]
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return filter_params
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def _adjust_table_rows(self, required_rows: int):
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"""调整表格行数"""
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current_rows = self.ui.tableWidget.rowCount()
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@ -424,7 +453,8 @@ class AudioFilterWidget(QWidget):
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# 添加需要的行
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while current_rows < required_rows:
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self._on_add_filter_clicked()
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# self._on_add_filter_clicked()
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self._on_add_filter_clicked_no_model_data()
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current_rows += 1
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def _update_filter_params(self, filter_params: Dict[int, Dict[str, Any]]):
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@ -436,10 +466,24 @@ class AudioFilterWidget(QWidget):
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if not self.ui.tableWidget.cellWidget(row, 0):
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self._create_checkbox(row)
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# 更新复选框状态
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container = self.ui.tableWidget.cellWidget(row, 0)
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if container and 'enable' in filter_data:
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checkbox = container.layout().itemAt(0).widget()
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if isinstance(checkbox, QCheckBox):
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print(f"filter_data_enable:{filter_data['enable']}")
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checkbox.setChecked(filter_data['enable'])
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# 更新或创建下拉框
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if not self.ui.tableWidget.cellWidget(row, 2):
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self._create_combobox(row)
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# 更新滤波器名称
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if 'name' in filter_data:
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name_item = QTableWidgetItem(str(filter_data['name']))
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name_item.setTextAlignment(Qt.AlignCenter)
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self.ui.tableWidget.setItem(row, 1, name_item)
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# 更新滤波器类型
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if 'filterType' in filter_data:
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combo = self.ui.tableWidget.cellWidget(row, 2)
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@ -513,17 +557,17 @@ class AudioFilterWidget(QWidget):
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)
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# 参数输入框变化
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self.ui.lineEdit_11.textChanged.connect(
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lambda v: self._on_param_changed('delay', v)
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self.ui.lineEdit_11.editingFinished.connect(
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lambda : self._on_param_changed('delay')
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)
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self.ui.lineEdit_10.textChanged.connect(
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lambda v: self._on_param_changed('volume', v)
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self.ui.lineEdit_10.editingFinished.connect(
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lambda : self._on_param_changed('volume')
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)
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self.ui.lineEdit_13.textChanged.connect(
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lambda v: self._on_param_changed('mix_right', v)
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self.ui.lineEdit_13.editingFinished.connect(
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lambda : self._on_param_changed('mix_right')
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)
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self.ui.lineEdit_12.textChanged.connect(
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lambda v: self._on_param_changed('mix_left', v)
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self.ui.lineEdit_12.editingFinished.connect(
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lambda : self._on_param_changed('mix_left')
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)
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# 按钮点击
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@ -541,10 +585,10 @@ class AudioFilterWidget(QWidget):
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"""安全地断开所有UI信号连接"""
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# 断开参数输入框信号
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try:
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self.ui.lineEdit_11.textChanged.disconnect()
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self.ui.lineEdit_10.textChanged.disconnect()
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self.ui.lineEdit_13.textChanged.disconnect()
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self.ui.lineEdit_12.textChanged.disconnect()
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self.ui.lineEdit_11.editingFinished.disconnect()
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self.ui.lineEdit_10.editingFinished.disconnect()
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self.ui.lineEdit_13.editingFinished.disconnect()
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self.ui.lineEdit_12.editingFinished.disconnect()
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except TypeError:
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# 信号可能未连接，忽略错误
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pass
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@ -576,17 +620,17 @@ class AudioFilterWidget(QWidget):
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def connect_param_signals(self):
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"""重新连接所有UI信号"""
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# 连接参数输入框信号
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self.ui.lineEdit_11.textChanged.connect(
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lambda v: self._on_param_changed('delay', v)
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self.ui.lineEdit_11.editingFinished.connect(
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lambda: self._on_param_changed('delay')
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)
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self.ui.lineEdit_10.textChanged.connect(
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lambda v: self._on_param_changed('volume', v)
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self.ui.lineEdit_10.editingFinished.connect(
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lambda: self._on_param_changed('volume')
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)
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self.ui.lineEdit_13.textChanged.connect(
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lambda v: self._on_param_changed('mix_right', v)
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self.ui.lineEdit_13.editingFinished.connect(
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lambda: self._on_param_changed('mix_right')
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)
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self.ui.lineEdit_12.textChanged.connect(
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lambda v: self._on_param_changed('mix_left', v)
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self.ui.lineEdit_12.editingFinished.connect(
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lambda: self._on_param_changed('mix_left')
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)
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# 连接滑块信号
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@ -679,7 +723,7 @@ class AudioFilterWidget(QWidget):
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self.model.update_filter(self.current_filter_index, filter_params)
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def _on_param_changed(self, param: str, value: str):
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def _on_param_changed(self, param: str):
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"""处理参数值变化"""
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if hasattr(self, 'model'):
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try:
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@ -687,15 +731,16 @@ class AudioFilterWidget(QWidget):
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# 更新model中的通道参数
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channel_params = self.model.channel_params
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if param == 'delay':
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channel_params.delay = value
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channel_params.delay = self.ui.lineEdit_11.text()
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elif param == 'volume':
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channel_params.volume = value
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channel_params.volume = self.ui.lineEdit_10.text()
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elif param == 'mix_right':
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channel_params.mix_right = value
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channel_params.mix_right = self.ui.lineEdit_13.text()
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elif param == 'mix_left':
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channel_params.mix_left = value
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channel_params.mix_left = self.ui.lineEdit_12.text()
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self.model.set_channel_params(channel_params)
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self.lineedit_changed.emit()
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except ValueError:
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pass
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@ -791,6 +836,38 @@ class AudioFilterWidget(QWidget):
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self.ui.groupBox_4.setTitle("")
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self.current_filter_index = -1
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def _on_add_filter_clicked_no_model_data(self):
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"""处理添加滤波器按钮点击
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****不更新model中的数据
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"""
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# 增加行
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row = self.ui.tableWidget.rowCount()
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self.ui.tableWidget.setRowCount(row + 1)
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self.filter_count += 1
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# 创建类型选择下拉框
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combo = QComboBox()
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combo.addItems(self.filter_types)
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combo.currentTextChanged.connect(lambda text: self._on_filter_type_changed(row, text))
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self.ui.tableWidget.setCellWidget(row, 2, combo)
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# 创建新的滤波器项，使用唯一的默认名称
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filter_data = {
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'filter_name': f"Filter_{row}", # 使用行号创建唯一名称
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'filter_type': self.filter_types[0],
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'enable': True,
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'freq': 0,
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'q': 0,
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'gain': 0,
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'slope': 0
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}
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# 更新表格
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self._update_table_row(row, filter_data)
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# 发送信号
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# self.filter_added.emit(self.filter_types[0])
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def _on_add_filter_clicked(self):
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"""处理添加滤波器按钮点击
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同时更新model中的数据
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@ -810,7 +887,7 @@ class AudioFilterWidget(QWidget):
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filter_data = {
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'filter_name': f"Filter_{row}", # 使用行号创建唯一名称
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'filter_type': self.filter_types[0],
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'enabled': True,
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'enable': True,
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'freq': 0,
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'q': 0,
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'gain': 0,
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@ -828,7 +905,7 @@ class AudioFilterWidget(QWidget):
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q_value=float(filter_data['q']),
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gain=float(filter_data['gain']),
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slope=float(filter_data['slope']),
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enabled=filter_data['enabled']
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enable=filter_data['enable']
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)
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self.model.add_filter(filter_params)
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@ -851,9 +928,10 @@ class AudioFilterWidget(QWidget):
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def _on_delete_filter_clicked(self):
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"""处理删除滤波器按钮点击"""
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if self.current_filter_index >= 0:
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self.filter_deleted.emit(self.current_filter_index)
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self.ui.tableWidget.removeRow(self.current_filter_index)
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self.filter_count -= 1
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self.filter_deleted.emit(self.current_filter_index)
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# 重置当前选择
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if self.filter_count == 0:
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@ -940,7 +1018,7 @@ class AudioFilterWidget(QWidget):
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if hasattr(self, 'model'):
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# 更新model中的滤波器启用状态
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filter_params = self.model.filters[row]
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filter_params.enabled = checked
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filter_params.enable = checked
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self.model.update_filter(row, filter_params)
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self.filter_enabled_changed.emit(row, checked)
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@ -973,7 +1051,7 @@ class AudioFilterWidget(QWidget):
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layout.setContentsMargins(0, 0, 0, 0)
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layout.setAlignment(Qt.AlignCenter)
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checkbox = QCheckBox()
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checkbox.setChecked(data.get('enabled', True))
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checkbox.setChecked(data.get('enable', True))
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# 添加复选框样式
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checkbox_style = """
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@ -11,7 +11,7 @@ class FilterPreset:
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q: float
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gain: float
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slope: float
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enabled: bool = True
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enable: bool = True
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class AudioFilterConfig:
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def __init__(self, config_path: str = None):
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@ -3,7 +3,7 @@ from PySide6.QtCore import QTimer
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from typing import Dict, Any, Optional
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from dataclasses import dataclass
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from enum import Enum, auto
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import csv
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import sys
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import time
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import os
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@ -136,7 +136,9 @@ class AudioFilterController(QObject):
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frequency=filter_data.get('frequency', 0.0) or filter_data.get('fc', 0.0),
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q_value=filter_data.get('q', 0.0),
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gain=filter_data.get('gain', 0.0),
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slope=filter_data.get('slope', 0.0)
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slope=filter_data.get('slope', 0.0),
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enable = filter_data.get('enable', True),
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name = filter_data.get('name', None)
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)
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self.model.filters.append(filter_params)
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@ -179,10 +181,11 @@ class AudioFilterController(QObject):
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# pass
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# to do:后续看情况调整是否需要单独下发调整的滤波器数据
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self.widget.filter_changed.connect(self._on_widget_filter_changed)
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self.widget.lineedit_changed.connect(self._on_lineedit_changed)
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# self.widget.param_changed.connect(self._on_widget_param_changed)
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# self.widget.filter_added.connect(self._on_widget_filter_added)
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# self.widget.filter_deleted.connect(self._on_widget_filter_deleted)
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# self.widget.filter_enabled_changed.connect(self._on_widget_filter_enabled_changed)
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self.widget.filter_added.connect(self._on_widget_filter_added)
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self.widget.filter_deleted.connect(self._on_widget_filter_deleted)
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self.widget.filter_enabled_changed.connect(self._on_widget_filter_enabled_changed)
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def _convert_struct_data_to_model(self, struct_data: Dict[str, Any]) -> Dict[str, Any]:
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@ -332,27 +335,47 @@ class AudioFilterController(QObject):
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try:
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self.state = AudioControllerState.UPDATING
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params = self.model.get_all_data()
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struct_params = self._convert_model_data_to_struct(params)
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# 准备所有参数
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channel_id = self.model.channel_id
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channel_id = params['channel_id']
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all_params = {}
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# 1. 添加基础参数
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base_params = {
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f'tuning_parameters.mix_parameters[{channel_id}].ch_n': channel_id + 1,
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f'tuning_parameters.mix_parameters[{channel_id}].mix_left_data': struct_params[f'tuning_parameters.mix_parameters[{channel_id}].mix_left_data'],
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f'tuning_parameters.mix_parameters[{channel_id}].mix_right_data': struct_params[f'tuning_parameters.mix_parameters[{channel_id}].mix_right_data'],
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f'tuning_parameters.mix_parameters[{channel_id}].mix_left_data': params['channel_params']['mix_left'],
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f'tuning_parameters.mix_parameters[{channel_id}].mix_right_data': params['channel_params']['mix_right'],
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f'tuning_parameters.delay_parameters[{channel_id}].ch_n': channel_id + 1,
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f'tuning_parameters.delay_parameters[{channel_id}].delay_data': struct_params[f'tuning_parameters.delay_parameters[{channel_id}].delay_data'],
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f'tuning_parameters.delay_parameters[{channel_id}].delay_data': params['channel_params']['delay'],
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f'tuning_parameters.volume_parameters[{channel_id}].ch_n': channel_id + 1,
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f'tuning_parameters.volume_parameters[{channel_id}].vol_data': struct_params[f'tuning_parameters.volume_parameters[{channel_id}].vol_data']
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f'tuning_parameters.volume_parameters[{channel_id}].vol_data': params['channel_params']['volume']
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}
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all_params.update(base_params)
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# 2. 添加所有滤波器参数
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filter_params = {k: v for k, v in struct_params.items() if 'eq_parameters' in k}
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all_params.update(filter_params)
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# 2. 添加所有滤波器参数（包括未使用的滤波器位置）
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base_idx = channel_id * 20
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||||
for i in range(20): # 每个通道固定20个滤波器位置
|
||||
idx = base_idx + i
|
||||
|
||||
# 如果有滤波器数据且enable为True就使用，否则用默认值0
|
||||
if i < len(params['filters']) and params['filters'][i]['enable']:
|
||||
filter_data = params['filters'][i]
|
||||
all_params.update({
|
||||
f'tuning_parameters.eq_parameters[{idx}].fc': filter_data['frequency'],
|
||||
f'tuning_parameters.eq_parameters[{idx}].q': filter_data['q_value'],
|
||||
f'tuning_parameters.eq_parameters[{idx}].gain': filter_data['gain'],
|
||||
f'tuning_parameters.eq_parameters[{idx}].slope': filter_data['slope'],
|
||||
f'tuning_parameters.eq_parameters[{idx}].filterType': filter_data['filter_type'].value
|
||||
})
|
||||
else:
|
||||
# 未使用或禁用的滤波器位置填充默认值0
|
||||
all_params.update({
|
||||
f'tuning_parameters.eq_parameters[{idx}].fc': 0.0,
|
||||
f'tuning_parameters.eq_parameters[{idx}].q': 0.0,
|
||||
f'tuning_parameters.eq_parameters[{idx}].gain': 0.0,
|
||||
f'tuning_parameters.eq_parameters[{idx}].slope': 0.0,
|
||||
f'tuning_parameters.eq_parameters[{idx}].filterType': 0
|
||||
})
|
||||
|
||||
# 3. 一次性发送所有参数
|
||||
ServiceManager.instance().params_service.set_params(
|
||||
@ -454,6 +477,10 @@ class AudioFilterController(QObject):
|
||||
|
||||
|
||||
#########################################################################################
|
||||
#line Edit 信号处理器
|
||||
def _on_lineedit_changed(self):
|
||||
self._sync_to_csv()
|
||||
|
||||
# Widget信号处理器
|
||||
def _on_widget_filter_changed(self, index: int, param_name: str, value: float):
|
||||
"""处理widget滤波器参数变化"""
|
||||
@ -481,7 +508,6 @@ class AudioFilterController(QObject):
|
||||
current_project = data_store_manager.current_project
|
||||
current_param = data_store_manager.current_param
|
||||
|
||||
|
||||
# 如果仍然没有当前项目或参数，则不进行同步
|
||||
if not current_project or not current_param:
|
||||
return
|
||||
@ -507,16 +533,91 @@ class AudioFilterController(QObject):
|
||||
'q': filter_param['q_value'],
|
||||
'gain': filter_param['gain'],
|
||||
'slope': filter_param['slope'],
|
||||
'filterType': filter_param['filter_type'].value
|
||||
'filterType': filter_param['filter_type'].value,
|
||||
'enable': filter_param['enable'],
|
||||
'name': filter_param['name']
|
||||
}
|
||||
channel_data[channel_id]['filters'].append(filter_data)
|
||||
|
||||
# 保存到CSV文件
|
||||
data_store_manager.save_param(current_project, current_param, channel_data)
|
||||
# 保存到CSV文件 os.path.join(self.storage_dir, "params")
|
||||
# storage_dir/"current_project"_"current_paramter_name".csv
|
||||
current_paramter_name = data_store_manager._store.current_paramter_name
|
||||
path = os.path.join(data_store_manager._store.storage_dir, "params")
|
||||
csv_path = os.path.join(path, f"{current_project}_{current_paramter_name}.csv")
|
||||
self.save_param_to_csv(csv_path, channel_data)
|
||||
# data_store_manager.save_param(current_project, current_param, channel_data)
|
||||
|
||||
except Exception as e:
|
||||
self.error_occurred.emit(f"同步到CSV文件时发生错误: {str(e)}")
|
||||
|
||||
# to do：后续该接口需要放入data_store_manager中
|
||||
def save_param_to_csv(self, csv_path, channel_data):
|
||||
"""保存参数到CSV文件"""
|
||||
try:
|
||||
# 读取现有CSV数据
|
||||
param_data = {}
|
||||
with open(csv_path, 'r', newline='') as csvfile:
|
||||
reader = csv.DictReader(csvfile)
|
||||
for row in reader:
|
||||
param_data[row['parameter']] = row['value']
|
||||
|
||||
# 获取当前通道ID
|
||||
channel_id = self.model.channel_id
|
||||
|
||||
param_data[f'dataset.tuning_parameters.mix_parameters[{channel_id}].mix_left_data'] = str(channel_data[channel_id]['mix_left_data'])
|
||||
param_data[f'dataset.tuning_parameters.mix_parameters[{channel_id}].mix_right_data'] = str(channel_data[channel_id]['mix_right_data'])
|
||||
|
||||
param_data[f'dataset.tuning_parameters.delay_parameters[{channel_id}].delay_data'] = str(channel_data[channel_id]['delay_data'])
|
||||
|
||||
param_data[f'dataset.tuning_parameters.volume_parameters[{channel_id}].vol_data'] = str(channel_data[channel_id]['vol_data'])
|
||||
|
||||
base_idx = channel_id * 20 # 每个通道20个均衡器
|
||||
|
||||
# 如果没有滤波器数据，将所有20个滤波器位置都设置为0
|
||||
if not channel_data[channel_id]['filters']:
|
||||
for i in range(20):
|
||||
idx = base_idx + i
|
||||
param_data[f'dataset.tuning_parameters.eq_parameters[{idx}].fc'] = '0'
|
||||
param_data[f'dataset.tuning_parameters.eq_parameters[{idx}].q'] = '0'
|
||||
param_data[f'dataset.tuning_parameters.eq_parameters[{idx}].gain'] = '0'
|
||||
param_data[f'dataset.tuning_parameters.eq_parameters[{idx}].slope'] = '0'
|
||||
param_data[f'dataset.tuning_parameters.eq_parameters[{idx}].filterType'] = '0'
|
||||
param_data[f'dataset.tuning_parameters.eq_parameters[{idx}].enable'] = 'false'
|
||||
else:
|
||||
# 有滤波器数据时的原有逻辑
|
||||
for i, filter_data in enumerate(channel_data[channel_id]['filters']):
|
||||
idx = base_idx + i
|
||||
param_data[f'dataset.tuning_parameters.eq_parameters[{idx}].fc'] = str(filter_data['fc'])
|
||||
param_data[f'dataset.tuning_parameters.eq_parameters[{idx}].q'] = str(filter_data['q'])
|
||||
param_data[f'dataset.tuning_parameters.eq_parameters[{idx}].gain'] = str(filter_data['gain'])
|
||||
param_data[f'dataset.tuning_parameters.eq_parameters[{idx}].slope'] = str(filter_data['slope'])
|
||||
param_data[f'dataset.tuning_parameters.eq_parameters[{idx}].filterType'] = str(filter_data['filterType'])
|
||||
param_data[f'dataset.tuning_parameters.eq_parameters[{idx}].enable'] = str(filter_data['enable'])
|
||||
param_data[f'dataset.tuning_parameters.eq_parameters[{idx}].name'] = str(filter_data['name'])
|
||||
|
||||
# 将剩余未使用的滤波器位置设置为0
|
||||
for i in range(len(channel_data[channel_id]['filters']), 20):
|
||||
idx = base_idx + i
|
||||
param_data[f'dataset.tuning_parameters.eq_parameters[{idx}].fc'] = '0'
|
||||
param_data[f'dataset.tuning_parameters.eq_parameters[{idx}].q'] = '0'
|
||||
param_data[f'dataset.tuning_parameters.eq_parameters[{idx}].gain'] = '0'
|
||||
param_data[f'dataset.tuning_parameters.eq_parameters[{idx}].slope'] = '0'
|
||||
param_data[f'dataset.tuning_parameters.eq_parameters[{idx}].filterType'] = '0'
|
||||
param_data[f'dataset.tuning_parameters.eq_parameters[{idx}].enable'] = 'false'
|
||||
|
||||
# 将更新后的数据写回CSV文件
|
||||
with open(csv_path, 'w', newline='') as csvfile:
|
||||
writer = csv.DictWriter(csvfile, fieldnames=['parameter', 'value'])
|
||||
writer.writeheader()
|
||||
for parameter, value in param_data.items():
|
||||
writer.writerow({'parameter': parameter, 'value': value})
|
||||
|
||||
except Exception as e:
|
||||
print(f"保存参数到CSV文件时发生错误: {str(e)}")
|
||||
self.error_occurred.emit(f"保存参数到CSV文件时发生错误: {str(e)}")
|
||||
|
||||
|
||||
|
||||
# def _on_widget_param_changed(self, param_name: str, value: float):
|
||||
# """处理widget通道参数变化"""
|
||||
# try:
|
||||
@ -527,36 +628,38 @@ class AudioFilterController(QObject):
|
||||
# except Exception as e:
|
||||
# self.error_occurred.emit(f"Error updating channel params: {str(e)}")
|
||||
|
||||
# def _on_widget_filter_added(self, filter_type: str):
|
||||
# """处理widget添加滤波器"""
|
||||
# try:
|
||||
# filter_params = FilterParams(
|
||||
# filter_type=FilterType[filter_type],
|
||||
# frequency=0.0,
|
||||
# q_value=0.0,
|
||||
# gain=0.0,
|
||||
# slope=0.0
|
||||
# )
|
||||
# self.model.add_filter(filter_params)
|
||||
# except Exception as e:
|
||||
# self.error_occurred.emit(f"Error adding filter: {str(e)}")
|
||||
def _on_widget_filter_added(self, filter_type: str):
|
||||
"""处理widget添加滤波器"""
|
||||
try:
|
||||
filter_params = FilterParams(
|
||||
filter_type=FilterType[filter_type],
|
||||
frequency=0.0,
|
||||
q_value=0.0,
|
||||
gain=0.0,
|
||||
slope=0.0
|
||||
)
|
||||
self.model.add_filter(filter_params)
|
||||
except Exception as e:
|
||||
self.error_occurred.emit(f"Error adding filter: {str(e)}")
|
||||
|
||||
# def _on_widget_filter_deleted(self, index: int):
|
||||
# """处理widget删除滤波器"""
|
||||
# try:
|
||||
# self.model.remove_filter(index)
|
||||
# except Exception as e:
|
||||
# self.error_occurred.emit(f"Error removing filter: {str(e)}")
|
||||
def _on_widget_filter_deleted(self, index: int):
|
||||
"""处理widget删除滤波器"""
|
||||
try:
|
||||
self.model.remove_filter(index)
|
||||
self._sync_to_csv()
|
||||
except Exception as e:
|
||||
self.error_occurred.emit(f"Error removing filter: {str(e)}")
|
||||
|
||||
# def _on_widget_filter_enabled_changed(self, index: int, enabled: bool):
|
||||
# """处理widget滤波器启用状态变化"""
|
||||
# try:
|
||||
# filter_params = self.model.get_filter(index)
|
||||
# if filter_params:
|
||||
# filter_params.enabled = enabled
|
||||
# self.model.update_filter(index, filter_params)
|
||||
# except Exception as e:
|
||||
# self.error_occurred.emit(f"Error updating filter state: {str(e)}")
|
||||
def _on_widget_filter_enabled_changed(self, index: int, enabled: bool):
|
||||
"""处理widget滤波器启用状态变化"""
|
||||
try:
|
||||
filter_params = self.model.get_filter(index)
|
||||
if filter_params:
|
||||
filter_params.enabled = enabled
|
||||
self.model.update_filter(index, filter_params)
|
||||
self._sync_to_csv()
|
||||
except Exception as e:
|
||||
self.error_occurred.emit(f"Error updating filter state: {str(e)}")
|
||||
##########################################################################################
|
||||
|
||||
|
||||
|
||||
@ -18,7 +18,8 @@ class FilterParams:
|
||||
q_value: float
|
||||
gain: float
|
||||
slope: float
|
||||
enabled: bool = True
|
||||
enable: bool = True
|
||||
name: Optional[str] = None
|
||||
|
||||
def to_dict(self, channel_id: int, filter_num: int) -> Dict[str, Any]:
|
||||
"""转换为与组件兼容的字典格式"""
|
||||
@ -27,7 +28,9 @@ class FilterParams:
|
||||
f'fc{channel_id}_{filter_num}': self.frequency,
|
||||
f'q{channel_id}_{filter_num}': self.q_value,
|
||||
f'gain{channel_id}_{filter_num}': self.gain,
|
||||
f'slope{channel_id}_{filter_num}': self.slope
|
||||
f'slope{channel_id}_{filter_num}': self.slope,
|
||||
f'enable{channel_id}_{filter_num}': self.enable,
|
||||
f'name{channel_id}_{filter_num}': self.name
|
||||
}
|
||||
|
||||
@classmethod
|
||||
@ -200,12 +203,12 @@ class AudioFilterModel(QObject):
|
||||
def is_filter_enabled(self, index: int) -> bool:
|
||||
"""检查指定滤波器是否启用"""
|
||||
if 0 <= index < len(self.filters):
|
||||
return self.filters[index].enabled
|
||||
return self.filters[index].enable
|
||||
return False
|
||||
|
||||
def get_enabled_filters(self) -> List[FilterParams]:
|
||||
"""获取所有启用的滤波器"""
|
||||
return [f for f in self.filters if f.enabled]
|
||||
return [f for f in self.filters if f.enable]
|
||||
|
||||
def get_widget_params(self) -> Dict[str, Any]:
|
||||
"""获取用于widget的参数格式（与to_widget_params相同）"""
|
||||
|
||||
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
@ -19,606 +19,846 @@ dataset.tuning_parameters.mix_parameters[4].mix_right_data,0.0
|
||||
dataset.tuning_parameters.mix_parameters[5].ch_n,5
|
||||
dataset.tuning_parameters.mix_parameters[5].mix_left_data,0.0
|
||||
dataset.tuning_parameters.mix_parameters[5].mix_right_data,0.0
|
||||
dataset.tuning_parameters.eq_parameters[0].fc,10.0
|
||||
dataset.tuning_parameters.eq_parameters[0].q,10.0
|
||||
dataset.tuning_parameters.eq_parameters[0].fc,10
|
||||
dataset.tuning_parameters.eq_parameters[0].q,10
|
||||
dataset.tuning_parameters.eq_parameters[0].gain,10.0
|
||||
dataset.tuning_parameters.eq_parameters[0].slope,10.0
|
||||
dataset.tuning_parameters.eq_parameters[0].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[1].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[1].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[1].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[0].enable,True
|
||||
dataset.tuning_parameters.eq_parameters[0].name,name_0
|
||||
dataset.tuning_parameters.eq_parameters[1].fc,0
|
||||
dataset.tuning_parameters.eq_parameters[1].q,0
|
||||
dataset.tuning_parameters.eq_parameters[1].gain,0
|
||||
dataset.tuning_parameters.eq_parameters[1].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[1].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[2].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[2].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[2].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[1].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[1].name,None
|
||||
dataset.tuning_parameters.eq_parameters[2].fc,0
|
||||
dataset.tuning_parameters.eq_parameters[2].q,0
|
||||
dataset.tuning_parameters.eq_parameters[2].gain,0
|
||||
dataset.tuning_parameters.eq_parameters[2].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[2].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[3].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[3].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[3].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[2].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[2].name,name_2
|
||||
dataset.tuning_parameters.eq_parameters[3].fc,0
|
||||
dataset.tuning_parameters.eq_parameters[3].q,0
|
||||
dataset.tuning_parameters.eq_parameters[3].gain,0
|
||||
dataset.tuning_parameters.eq_parameters[3].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[3].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[4].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[4].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[4].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[3].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[3].name,name_3
|
||||
dataset.tuning_parameters.eq_parameters[4].fc,0
|
||||
dataset.tuning_parameters.eq_parameters[4].q,0
|
||||
dataset.tuning_parameters.eq_parameters[4].gain,0
|
||||
dataset.tuning_parameters.eq_parameters[4].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[4].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[5].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[5].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[5].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[4].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[4].name,name_4
|
||||
dataset.tuning_parameters.eq_parameters[5].fc,0
|
||||
dataset.tuning_parameters.eq_parameters[5].q,0
|
||||
dataset.tuning_parameters.eq_parameters[5].gain,0
|
||||
dataset.tuning_parameters.eq_parameters[5].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[5].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[6].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[6].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[6].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[5].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[5].name,name_5
|
||||
dataset.tuning_parameters.eq_parameters[6].fc,0
|
||||
dataset.tuning_parameters.eq_parameters[6].q,0
|
||||
dataset.tuning_parameters.eq_parameters[6].gain,0
|
||||
dataset.tuning_parameters.eq_parameters[6].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[6].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[7].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[7].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[7].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[6].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[6].name,name_6
|
||||
dataset.tuning_parameters.eq_parameters[7].fc,0
|
||||
dataset.tuning_parameters.eq_parameters[7].q,0
|
||||
dataset.tuning_parameters.eq_parameters[7].gain,0
|
||||
dataset.tuning_parameters.eq_parameters[7].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[7].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[8].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[8].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[8].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[7].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[7].name,name_7
|
||||
dataset.tuning_parameters.eq_parameters[8].fc,0
|
||||
dataset.tuning_parameters.eq_parameters[8].q,0
|
||||
dataset.tuning_parameters.eq_parameters[8].gain,0
|
||||
dataset.tuning_parameters.eq_parameters[8].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[8].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[9].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[9].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[9].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[8].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[8].name,name_8
|
||||
dataset.tuning_parameters.eq_parameters[9].fc,0
|
||||
dataset.tuning_parameters.eq_parameters[9].q,0
|
||||
dataset.tuning_parameters.eq_parameters[9].gain,0
|
||||
dataset.tuning_parameters.eq_parameters[9].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[9].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[10].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[10].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[10].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[9].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[9].name,name_9
|
||||
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dataset.tuning_parameters.eq_parameters[94].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[94].name,name_94
|
||||
dataset.tuning_parameters.eq_parameters[95].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[95].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[95].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[95].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[95].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[95].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[95].name,name_95
|
||||
dataset.tuning_parameters.eq_parameters[96].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[96].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[96].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[96].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[96].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[96].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[96].name,name_96
|
||||
dataset.tuning_parameters.eq_parameters[97].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[97].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[97].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[97].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[97].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[97].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[97].name,name_97
|
||||
dataset.tuning_parameters.eq_parameters[98].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[98].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[98].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[98].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[98].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[98].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[98].name,name_98
|
||||
dataset.tuning_parameters.eq_parameters[99].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[99].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[99].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[99].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[99].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[99].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[99].name,name_99
|
||||
dataset.tuning_parameters.eq_parameters[100].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[100].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[100].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[100].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[100].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[100].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[100].name,name_100
|
||||
dataset.tuning_parameters.eq_parameters[101].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[101].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[101].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[101].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[101].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[101].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[101].name,name_101
|
||||
dataset.tuning_parameters.eq_parameters[102].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[102].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[102].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[102].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[102].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[102].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[102].name,name_102
|
||||
dataset.tuning_parameters.eq_parameters[103].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[103].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[103].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[103].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[103].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[103].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[103].name,name_103
|
||||
dataset.tuning_parameters.eq_parameters[104].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[104].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[104].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[104].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[104].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[104].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[104].name,name_104
|
||||
dataset.tuning_parameters.eq_parameters[105].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[105].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[105].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[105].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[105].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[105].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[105].name,name_105
|
||||
dataset.tuning_parameters.eq_parameters[106].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[106].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[106].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[106].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[106].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[106].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[106].name,name_106
|
||||
dataset.tuning_parameters.eq_parameters[107].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[107].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[107].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[107].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[107].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[107].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[107].name,name_107
|
||||
dataset.tuning_parameters.eq_parameters[108].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[108].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[108].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[108].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[108].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[108].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[108].name,name_108
|
||||
dataset.tuning_parameters.eq_parameters[109].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[109].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[109].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[109].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[109].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[109].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[109].name,name_109
|
||||
dataset.tuning_parameters.eq_parameters[110].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[110].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[110].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[110].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[110].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[110].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[110].name,name_110
|
||||
dataset.tuning_parameters.eq_parameters[111].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[111].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[111].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[111].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[111].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[111].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[111].name,name_111
|
||||
dataset.tuning_parameters.eq_parameters[112].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[112].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[112].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[112].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[112].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[112].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[112].name,name_112
|
||||
dataset.tuning_parameters.eq_parameters[113].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[113].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[113].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[113].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[113].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[113].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[113].name,name_113
|
||||
dataset.tuning_parameters.eq_parameters[114].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[114].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[114].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[114].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[114].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[114].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[114].name,name_114
|
||||
dataset.tuning_parameters.eq_parameters[115].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[115].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[115].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[115].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[115].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[115].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[115].name,name_115
|
||||
dataset.tuning_parameters.eq_parameters[116].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[116].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[116].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[116].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[116].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[116].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[116].name,name_116
|
||||
dataset.tuning_parameters.eq_parameters[117].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[117].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[117].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[117].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[117].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[117].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[117].name,name_117
|
||||
dataset.tuning_parameters.eq_parameters[118].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[118].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[118].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[118].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[118].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[118].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[118].name,name_118
|
||||
dataset.tuning_parameters.eq_parameters[119].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[119].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[119].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[119].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[119].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[119].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[119].name,name_119
|
||||
dataset.tuning_parameters.delay_parameters[0].ch_n,0
|
||||
dataset.tuning_parameters.delay_parameters[0].delay_data,10.0
|
||||
dataset.tuning_parameters.delay_parameters[1].ch_n,1
|
||||
|
||||
|
@ -2,11 +2,11 @@ parameter,value
|
||||
dataset.audio_mode,0
|
||||
dataset.send_action,0
|
||||
dataset.tuning_parameters.mix_parameters[0].ch_n,0
|
||||
dataset.tuning_parameters.mix_parameters[0].mix_left_data,0.7
|
||||
dataset.tuning_parameters.mix_parameters[0].mix_right_data,0.3
|
||||
dataset.tuning_parameters.mix_parameters[0].mix_left_data,1.0
|
||||
dataset.tuning_parameters.mix_parameters[0].mix_right_data,1.0
|
||||
dataset.tuning_parameters.mix_parameters[1].ch_n,1
|
||||
dataset.tuning_parameters.mix_parameters[1].mix_left_data,0.5
|
||||
dataset.tuning_parameters.mix_parameters[1].mix_right_data,0.5
|
||||
dataset.tuning_parameters.mix_parameters[1].mix_left_data,0.0
|
||||
dataset.tuning_parameters.mix_parameters[1].mix_right_data,0.0
|
||||
dataset.tuning_parameters.mix_parameters[2].ch_n,2
|
||||
dataset.tuning_parameters.mix_parameters[2].mix_left_data,0.0
|
||||
dataset.tuning_parameters.mix_parameters[2].mix_right_data,0.0
|
||||
@ -19,611 +19,850 @@ dataset.tuning_parameters.mix_parameters[4].mix_right_data,0.0
|
||||
dataset.tuning_parameters.mix_parameters[5].ch_n,5
|
||||
dataset.tuning_parameters.mix_parameters[5].mix_left_data,0.0
|
||||
dataset.tuning_parameters.mix_parameters[5].mix_right_data,0.0
|
||||
dataset.tuning_parameters.eq_parameters[0].fc,100.0
|
||||
dataset.tuning_parameters.eq_parameters[0].q,0.7
|
||||
dataset.tuning_parameters.eq_parameters[0].gain,2.0
|
||||
dataset.tuning_parameters.eq_parameters[0].slope,12
|
||||
dataset.tuning_parameters.eq_parameters[0].filterType,1
|
||||
dataset.tuning_parameters.eq_parameters[1].fc,200.0
|
||||
dataset.tuning_parameters.eq_parameters[1].q,1.0
|
||||
dataset.tuning_parameters.eq_parameters[1].gain,-3.0
|
||||
dataset.tuning_parameters.eq_parameters[1].slope,6
|
||||
dataset.tuning_parameters.eq_parameters[1].filterType,2
|
||||
dataset.tuning_parameters.eq_parameters[0].fc,10.0
|
||||
dataset.tuning_parameters.eq_parameters[0].q,10.0
|
||||
dataset.tuning_parameters.eq_parameters[0].gain,10.0
|
||||
dataset.tuning_parameters.eq_parameters[0].slope,10.0
|
||||
dataset.tuning_parameters.eq_parameters[0].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[0].enable,true
|
||||
dataset.tuning_parameters.eq_parameters[0].name,name_0
|
||||
dataset.tuning_parameters.eq_parameters[1].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[1].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[1].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[1].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[1].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[1].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[1].name,name_1
|
||||
dataset.tuning_parameters.eq_parameters[2].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[2].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[2].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[2].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[2].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[2].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[2].name,name_2
|
||||
dataset.tuning_parameters.eq_parameters[3].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[3].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[3].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[3].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[3].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[3].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[3].name,name_3
|
||||
dataset.tuning_parameters.eq_parameters[4].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[4].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[4].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[4].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[4].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[4].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[4].name,name_4
|
||||
dataset.tuning_parameters.eq_parameters[5].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[5].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[5].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[5].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[5].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[5].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[5].name,name_5
|
||||
dataset.tuning_parameters.eq_parameters[6].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[6].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[6].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[6].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[6].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[6].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[6].name,name_6
|
||||
dataset.tuning_parameters.eq_parameters[7].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[7].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[7].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[7].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[7].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[7].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[7].name,name_7
|
||||
dataset.tuning_parameters.eq_parameters[8].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[8].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[8].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[8].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[8].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[8].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[8].name,name_8
|
||||
dataset.tuning_parameters.eq_parameters[9].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[9].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[9].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[9].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[9].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[9].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[9].name,name_9
|
||||
dataset.tuning_parameters.eq_parameters[10].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[10].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[10].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[10].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[10].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[10].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[10].name,name_10
|
||||
dataset.tuning_parameters.eq_parameters[11].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[11].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[11].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[11].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[11].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[11].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[11].name,name_11
|
||||
dataset.tuning_parameters.eq_parameters[12].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[12].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[12].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[12].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[12].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[12].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[12].name,name_12
|
||||
dataset.tuning_parameters.eq_parameters[13].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[13].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[13].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[13].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[13].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[13].enable,false
|
||||
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|
||||
dataset.tuning_parameters.eq_parameters[101].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[101].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[101].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[101].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[101].name,name_101
|
||||
dataset.tuning_parameters.eq_parameters[102].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[102].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[102].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[102].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[102].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[102].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[102].name,name_102
|
||||
dataset.tuning_parameters.eq_parameters[103].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[103].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[103].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[103].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[103].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[103].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[103].name,name_103
|
||||
dataset.tuning_parameters.eq_parameters[104].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[104].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[104].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[104].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[104].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[104].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[104].name,name_104
|
||||
dataset.tuning_parameters.eq_parameters[105].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[105].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[105].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[105].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[105].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[105].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[105].name,name_105
|
||||
dataset.tuning_parameters.eq_parameters[106].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[106].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[106].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[106].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[106].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[106].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[106].name,name_106
|
||||
dataset.tuning_parameters.eq_parameters[107].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[107].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[107].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[107].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[107].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[107].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[107].name,name_107
|
||||
dataset.tuning_parameters.eq_parameters[108].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[108].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[108].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[108].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[108].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[108].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[108].name,name_108
|
||||
dataset.tuning_parameters.eq_parameters[109].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[109].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[109].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[109].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[109].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[109].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[109].name,name_109
|
||||
dataset.tuning_parameters.eq_parameters[110].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[110].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[110].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[110].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[110].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[110].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[110].name,name_110
|
||||
dataset.tuning_parameters.eq_parameters[111].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[111].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[111].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[111].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[111].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[111].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[111].name,name_111
|
||||
dataset.tuning_parameters.eq_parameters[112].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[112].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[112].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[112].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[112].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[112].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[112].name,name_112
|
||||
dataset.tuning_parameters.eq_parameters[113].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[113].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[113].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[113].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[113].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[113].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[113].name,name_113
|
||||
dataset.tuning_parameters.eq_parameters[114].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[114].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[114].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[114].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[114].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[114].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[114].name,name_114
|
||||
dataset.tuning_parameters.eq_parameters[115].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[115].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[115].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[115].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[115].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[115].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[115].name,name_115
|
||||
dataset.tuning_parameters.eq_parameters[116].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[116].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[116].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[116].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[116].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[116].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[116].name,name_116
|
||||
dataset.tuning_parameters.eq_parameters[117].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[117].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[117].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[117].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[117].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[117].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[117].name,name_117
|
||||
dataset.tuning_parameters.eq_parameters[118].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[118].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[118].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[118].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[118].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[118].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[118].name,name_118
|
||||
dataset.tuning_parameters.eq_parameters[119].fc,0.0
|
||||
dataset.tuning_parameters.eq_parameters[119].q,0.0
|
||||
dataset.tuning_parameters.eq_parameters[119].gain,0.0
|
||||
dataset.tuning_parameters.eq_parameters[119].slope,0
|
||||
dataset.tuning_parameters.eq_parameters[119].filterType,0
|
||||
dataset.tuning_parameters.eq_parameters[119].enable,false
|
||||
dataset.tuning_parameters.eq_parameters[119].name,name_119
|
||||
dataset.tuning_parameters.delay_parameters[0].ch_n,0
|
||||
dataset.tuning_parameters.delay_parameters[0].delay_data,0.05
|
||||
dataset.tuning_parameters.delay_parameters[0].delay_data,10.0
|
||||
dataset.tuning_parameters.delay_parameters[1].ch_n,1
|
||||
dataset.tuning_parameters.delay_parameters[1].delay_data,0.1
|
||||
dataset.tuning_parameters.delay_parameters[1].delay_data,0.0
|
||||
dataset.tuning_parameters.delay_parameters[2].ch_n,2
|
||||
dataset.tuning_parameters.delay_parameters[2].delay_data,0.0
|
||||
dataset.tuning_parameters.delay_parameters[3].ch_n,3
|
||||
@ -633,9 +872,9 @@ dataset.tuning_parameters.delay_parameters[4].delay_data,0.0
|
||||
dataset.tuning_parameters.delay_parameters[5].ch_n,5
|
||||
dataset.tuning_parameters.delay_parameters[5].delay_data,0.0
|
||||
dataset.tuning_parameters.volume_parameters[0].ch_n,0
|
||||
dataset.tuning_parameters.volume_parameters[0].vol_data,-3.0
|
||||
dataset.tuning_parameters.volume_parameters[0].vol_data,10.0
|
||||
dataset.tuning_parameters.volume_parameters[1].ch_n,1
|
||||
dataset.tuning_parameters.volume_parameters[1].vol_data,-6.0
|
||||
dataset.tuning_parameters.volume_parameters[1].vol_data,0.0
|
||||
dataset.tuning_parameters.volume_parameters[2].ch_n,2
|
||||
dataset.tuning_parameters.volume_parameters[2].vol_data,0.0
|
||||
dataset.tuning_parameters.volume_parameters[3].ch_n,3
|
||||
|
||||
|
@ -10,7 +10,7 @@ class FilterData:
|
||||
q: float
|
||||
gain: float
|
||||
slope: float
|
||||
enabled: bool = True
|
||||
enable: bool = True
|
||||
position: int = 0
|
||||
config_id: Optional[int] = None
|
||||
id: Optional[int] = None
|
||||
|
||||
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@ -11,6 +11,7 @@ class DataStore:
|
||||
self.storage_dir = storage_dir
|
||||
self.current_project: Optional[str] = None
|
||||
self.current_param: Optional[str] = None
|
||||
self.current_paramter_name: Optional[str] = None
|
||||
self._ensure_storage_dir()
|
||||
|
||||
def _ensure_storage_dir(self):
|
||||
@ -256,7 +257,7 @@ class DataStore:
|
||||
channel_data = {}
|
||||
|
||||
# 处理混音参数
|
||||
# to do:后续处理这个6
|
||||
# to do: 后续处理这个6
|
||||
for i in range(6): # 假设最多6个通道
|
||||
ch_key = f'dataset.tuning_parameters.mix_parameters[{i}].ch_n'
|
||||
if ch_key in param_data:
|
||||
@ -265,17 +266,17 @@ class DataStore:
|
||||
if channel_id not in channel_data:
|
||||
channel_data[channel_id] = {'filters': []}
|
||||
|
||||
# 左混音
|
||||
|
||||
left_key = f'dataset.tuning_parameters.mix_parameters[{i}].mix_left_data'
|
||||
if left_key in param_data:
|
||||
channel_data[channel_id]['mix_left_data'] = float(param_data[left_key])
|
||||
|
||||
# 右混音
|
||||
|
||||
right_key = f'dataset.tuning_parameters.mix_parameters[{i}].mix_right_data'
|
||||
if right_key in param_data:
|
||||
channel_data[channel_id]['mix_right_data'] = float(param_data[right_key])
|
||||
|
||||
# 处理延迟参数
|
||||
|
||||
for i in range(6):
|
||||
ch_key = f'dataset.tuning_parameters.delay_parameters[{i}].ch_n'
|
||||
if ch_key in param_data:
|
||||
@ -288,7 +289,7 @@ class DataStore:
|
||||
if delay_key in param_data:
|
||||
channel_data[channel_id]['delay_data'] = float(param_data[delay_key])
|
||||
|
||||
# 处理音量参数
|
||||
|
||||
for i in range(6):
|
||||
ch_key = f'dataset.tuning_parameters.volume_parameters[{i}].ch_n'
|
||||
if ch_key in param_data:
|
||||
@ -301,7 +302,7 @@ class DataStore:
|
||||
if vol_key in param_data:
|
||||
channel_data[channel_id]['vol_data'] = float(param_data[vol_key])
|
||||
|
||||
# 处理滤波器参数
|
||||
|
||||
for i in range(120): # 最多120个滤波器
|
||||
fc_key = f'dataset.tuning_parameters.eq_parameters[{i}].fc'
|
||||
if fc_key in param_data:
|
||||
@ -338,6 +339,15 @@ class DataStore:
|
||||
# 先转为浮点数再转为整数
|
||||
filter_data['filterType'] = int(float(param_data[filter_type_key]))
|
||||
|
||||
# 添加enable和name参数
|
||||
enable_key = f'dataset.tuning_parameters.eq_parameters[{i}].enable'
|
||||
if enable_key in param_data:
|
||||
filter_data['enable'] = param_data[enable_key].lower() == 'true'
|
||||
|
||||
name_key = f'dataset.tuning_parameters.eq_parameters[{i}].name'
|
||||
if name_key in param_data:
|
||||
filter_data['name'] = param_data[name_key]
|
||||
|
||||
return channel_data
|
||||
|
||||
def list_projects(self) -> List[str]:
|
||||
|
||||
@ -9,7 +9,7 @@ class FilterConfig:
|
||||
q: float
|
||||
gain: float
|
||||
slope: int
|
||||
enabled: bool
|
||||
enable: bool
|
||||
|
||||
|
||||
|
||||
|
||||
@ -201,7 +201,7 @@ class AudioFilterController:
|
||||
position=len(self.model.filters),
|
||||
config_id=self.model.current_config_id,
|
||||
channel_id=self.model.current_channel_id,
|
||||
enabled=True,
|
||||
enable=True,
|
||||
id=None # 初始创建时 id 为 None
|
||||
)
|
||||
|
||||
@ -283,7 +283,7 @@ class AudioFilterWidget(QWidget):
|
||||
# 创建带复选框的滤波器名称项
|
||||
filter_item = QTableWidgetItem()
|
||||
filter_item.setFlags(filter_item.flags() | Qt.ItemFlag.ItemIsUserCheckable)
|
||||
filter_item.setCheckState(Qt.CheckState.Checked if filter_data.enabled else Qt.CheckState.Unchecked)
|
||||
filter_item.setCheckState(Qt.CheckState.Checked if filter_data.enable else Qt.CheckState.Unchecked)
|
||||
filter_item.setText(str(filter_data.filter_type)) # 设置文本，这样文本会和复选框一起显示
|
||||
|
||||
# 更新各列的值
|
||||
|
||||
Loading…
Reference in New Issue
Block a user