import streamlit as st
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import plotly.express as px
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import plotly.graph_objects as go
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import pandas as pd
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from datetime import datetime, timedelta
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from app.services.main_process_service import MainProcessService
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def show_main_process_dashboard():
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# 初始化服务
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service = MainProcessService()
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# 页面标题
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st.title("主流程控制数据分析")
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# 初始化会话状态用于日期同步
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if 'main_process_start_date' not in st.session_state:
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st.session_state['main_process_start_date'] = datetime.now().date() - timedelta(days=7)
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if 'main_process_end_date' not in st.session_state:
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st.session_state['main_process_end_date'] = datetime.now().date()
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if 'main_process_quick_select' not in st.session_state:
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st.session_state['main_process_quick_select'] = "最近7天"
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# 定义回调函数
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def update_dates(qs):
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st.session_state['main_process_quick_select'] = qs
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today = datetime.now().date()
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if qs == "今天":
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st.session_state['main_process_start_date'] = today
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st.session_state['main_process_end_date'] = today
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elif qs == "最近3天":
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st.session_state['main_process_start_date'] = today - timedelta(days=3)
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st.session_state['main_process_end_date'] = today
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elif qs == "最近7天":
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st.session_state['main_process_start_date'] = today - timedelta(days=7)
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st.session_state['main_process_end_date'] = today
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elif qs == "最近30天":
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st.session_state['main_process_start_date'] = today - timedelta(days=30)
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st.session_state['main_process_end_date'] = today
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def on_date_change():
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st.session_state['main_process_quick_select'] = "自定义"
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# 查询条件区域
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with st.expander("🔍 查询配置", expanded=True):
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# 添加自定义 CSS 实现响应式换行
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st.markdown("""
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<style>
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/* 强制列容器换行 */
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[data-testid="stExpander"] [data-testid="column"] {
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flex: 1 1 120px !important;
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min-width: 120px !important;
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}
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/* 针对日期输入框列稍微加宽一点 */
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@media (min-width: 768px) {
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[data-testid="stExpander"] [data-testid="column"]:nth-child(6),
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[data-testid="stExpander"] [data-testid="column"]:nth-child(7) {
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flex: 2 1 180px !important;
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min-width: 180px !important;
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}
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}
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</style>
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""", unsafe_allow_html=True)
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# 创建布局
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cols = st.columns([1, 1, 1, 1, 1, 1.5, 1.5, 1])
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options = ["今天", "最近3天", "最近7天", "最近30天", "自定义"]
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for i, option in enumerate(options):
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with cols[i]:
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# 根据当前选择状态决定按钮类型
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button_type = "primary" if st.session_state['main_process_quick_select'] == option else "secondary"
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if st.button(option, key=f"btn_main_{option}", width='stretch', type=button_type):
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update_dates(option)
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st.rerun()
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with cols[5]:
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st.date_input(
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"开始日期",
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label_visibility="collapsed",
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key="main_process_start_date",
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on_change=on_date_change
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)
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with cols[6]:
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st.date_input(
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"结束日期",
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label_visibility="collapsed",
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key="main_process_end_date",
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on_change=on_date_change
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)
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with cols[7]:
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query_button = st.button("🚀 查询", key="main_process_query", width='stretch')
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# 转换为datetime对象
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start_dt = datetime.combine(st.session_state['main_process_start_date'], datetime.min.time())
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end_dt = datetime.combine(st.session_state['main_process_end_date'], datetime.max.time())
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if query_button:
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with st.spinner("正在获取主流程数据..."):
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# 1. 获取主速度数据
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df_speed = service.get_cutting_setting_data(start_dt, end_dt)
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# 2. 获取电机监控数据
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df_motor = service.get_motor_monitoring_data(start_dt, end_dt)
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# 3. 获取温度控制数据
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df_temp = service.get_temperature_control_data(start_dt, end_dt)
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# --- 趋势图 1: 流程主速度 ---
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st.subheader("📈 流程主速度趋势")
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if not df_speed.empty:
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fig_speed = px.line(df_speed, x='time', y='process_main_speed',
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title="流程主速度 (M/Min)",
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labels={'time': '时间', 'process_main_speed': '主速度 (M/Min)'})
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fig_speed.update_layout(
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xaxis=dict(rangeslider=dict(visible=True), type='date'),
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yaxis=dict(fixedrange=False),
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hovermode='x unified',
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dragmode='zoom',
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)
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st.plotly_chart(fig_speed, width='stretch', config={
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'scrollZoom': True,
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'modeBarButtonsToAdd': ['zoom2d', 'zoomIn2d', 'zoomOut2d'],
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'doubleClick': 'reset',
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'displayModeBar': True,
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'toImageButtonOptions': {'format': 'png'}
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})
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else:
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st.info("该时间段内无主速度数据")
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# --- 趋势图 2: 电机运行线速 ---
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st.subheader("📈 电机运行线速趋势")
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if not df_motor.empty:
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fig_motor = go.Figure()
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fig_motor.add_trace(go.Scatter(x=df_motor['time'], y=df_motor['m1_line_speed'], name='拉出一段线速'))
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fig_motor.add_trace(go.Scatter(x=df_motor['time'], y=df_motor['m2_line_speed'], name='拉出二段线速'))
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fig_motor.update_layout(
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title="电机线速 (M/Min)",
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xaxis_title="时间",
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yaxis_title="线速 (M/Min)",
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xaxis=dict(rangeslider=dict(visible=True), type='date'),
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yaxis=dict(fixedrange=False),
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hovermode='x unified',
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dragmode='zoom'
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)
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st.plotly_chart(fig_motor, width='stretch', config={
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'scrollZoom': True,
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'modeBarButtonsToAdd': ['zoom2d', 'zoomIn2d', 'zoomOut2d'],
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'doubleClick': 'reset',
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'displayModeBar': True
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})
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else:
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st.info("该时间段内无电机监控数据")
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# --- 趋势图 3: 中田挤出机温度控制 ---
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st.subheader("📈 中田挤出机温度趋势")
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if not df_temp.empty:
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fig_temp = go.Figure()
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# 螺杆温度
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fig_temp.add_trace(go.Scatter(x=df_temp['time'], y=df_temp['nakata_extruder_screw_set_temp'],
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name='螺杆设定', line=dict(dash='dash')))
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fig_temp.add_trace(go.Scatter(x=df_temp['time'], y=df_temp['nakata_extruder_screw_display_temp'],
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name='螺杆显示'))
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# 后机筒温度
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fig_temp.add_trace(go.Scatter(x=df_temp['time'], y=df_temp['nakata_extruder_rear_barrel_set_temp'],
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name='后机筒设定', line=dict(dash='dash')))
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fig_temp.add_trace(go.Scatter(x=df_temp['time'], y=df_temp['nakata_extruder_rear_barrel_display_temp'],
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name='后机筒显示'))
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# 前机筒温度
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fig_temp.add_trace(go.Scatter(x=df_temp['time'], y=df_temp['nakata_extruder_front_barrel_set_temp'],
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name='前机筒设定', line=dict(dash='dash')))
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fig_temp.add_trace(go.Scatter(x=df_temp['time'], y=df_temp['nakata_extruder_front_barrel_display_temp'],
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name='前机筒显示'))
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# 机头温度
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fig_temp.add_trace(go.Scatter(x=df_temp['time'], y=df_temp['nakata_extruder_head_set_temp'],
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name='机头设定', line=dict(dash='dash')))
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fig_temp.add_trace(go.Scatter(x=df_temp['time'], y=df_temp['nakata_extruder_head_display_temp'],
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name='机头显示'))
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fig_temp.update_layout(
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title="中田挤出机温度 (°C)",
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xaxis_title="时间",
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yaxis_title="温度 (°C)",
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xaxis=dict(rangeslider=dict(visible=True), type='date'),
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yaxis=dict(fixedrange=False),
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hovermode='x unified',
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dragmode='zoom'
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)
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st.plotly_chart(fig_temp, width='stretch', config={
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'scrollZoom': True,
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'modeBarButtonsToAdd': ['zoom2d', 'zoomIn2d', 'zoomOut2d'],
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'doubleClick': 'reset',
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'displayModeBar': True
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})
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else:
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st.info("该时间段内无温度控制数据")
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