Merge branch 'master' of flt6.top:flt/tools
This commit is contained in:
2
.gitignore
vendored
2
.gitignore
vendored
@ -7,3 +7,5 @@ __pycache__
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*.mp4
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*.log
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test
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.venv
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uv.lock
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199
cord/main.py
Normal file
199
cord/main.py
Normal file
@ -0,0 +1,199 @@
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from matplotlib import pyplot as plt
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import pandas as pd
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import numpy as np
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import io
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import streamlit as st
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# import scienceplots
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# plt.style.use(['nature', 'no-latex',"cjk-sc-font"])
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plt.rcParams['font.family'] = 'sans-serif'
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plt.rcParams['font.sans-serif'] = ['SimHei'] # 设置中文字体
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plt.rcParams['axes.unicode_minus'] = False # 解决负号显示问题
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||||
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def cubic_bezier_with_zero_derivatives(p0, p1, t_array, influence_factor):
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"""
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创建三次贝塞尔曲线，确保起点和终点的导数为0
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参数:
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p0: 起点 [x0, y0]
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p1: 终点 [x1, y1]
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t_array: 参数数组 (0到1)
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influence_factor: 影响因子，控制控制点的位置
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返回:
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x_array, y_array: 贝塞尔曲线上的点
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"""
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x0, y0 = p0
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x1, y1 = p1
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# 计算控制点，确保起点和终点导数为0
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# 控制点位置基于影响因子和两点间距离
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dx = x1 - x0
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# 第一个控制点：在起点右侧，y坐标与起点相同（确保起点导数为0）
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p1_control = [x0 + dx * influence_factor[0], y0]
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# 第二个控制点：在终点左侧，y坐标与终点相同（确保终点导数为0）
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p2_control = [x1 - dx * influence_factor[1], y1]
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# 计算贝塞尔曲线
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x_bezier = ((1-t_array)**3 * x0 +
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3*(1-t_array)**2 * t_array * p1_control[0] +
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3*(1-t_array) * t_array**2 * p2_control[0] +
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t_array**3 * x1)
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y_bezier = ((1-t_array)**3 * y0 +
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3*(1-t_array)**2 * t_array * p1_control[1] +
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3*(1-t_array) * t_array**2 * p2_control[1] +
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t_array**3 * y1)
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return x_bezier, y_bezier
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# @st.cache_resource
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def plot_reaction_coordinate(changed=None, _lines=None):
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"""
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绘制反应坐标图
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"""
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lines = []
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fig,ax1 = plt.subplots(figsize=(9, 6))
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last=(-1,-1)
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maxy = data["Energy"].max()
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miny = data["Energy"].min()
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varyy = maxy - miny
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for i in range(data.shape[0]):
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line:pd.Series = data.loc[i]
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if last == (-1,-1):
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last = (1, line["Energy"])
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if not pd.isna(line["Name"]):
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ax1.annotate(str(line["Name"]), (1, line["Energy"]+varyy*K_POS[i]), ha='center')
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else:
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p1 = last[0]+2,line["Energy"]
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x,y = cubic_bezier_with_zero_derivatives(last,p1, np.linspace(0, 1, 300), INFLU_FACTORS[(i*2-2):i*2])
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l = ax1.plot(x, y, "-", color="black")[0]
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lines.append(l)
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if not pd.isna(line["Name"]):
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p = p1[0],p1[1]+varyy*K_POS[i]
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ax1.annotate(str(line["Name"]), p, ha='center')
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last = p1
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ax1.set_xlabel("Reaction Coordinate")
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ax1.xaxis.set_ticks([])
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ax1.set_ylabel("Energy (kcal/mol)")
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ax1.set_ylim(miny-varyy*0.1, maxy+varyy*0.1)
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return fig,lines
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# 创建图形和坐标轴
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def callback_gen(x,typ=0):
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if typ:
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def callback():
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global K_POS
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K_POS[x] = st.session_state.get(f'text_slider_{x}', 0.05)
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plot_reaction_coordinate(changed=x, _lines=lines)
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else:
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def callback():
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global INFLU_FACTORS
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INFLU_FACTORS[x-1] = st.session_state.get(f'slider_{x}', 0.5)
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plot_reaction_coordinate(changed=x, _lines=lines)
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return callback
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def on_save():
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global out_file
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# for slider in slides:
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# slider.ax.set_visible(False)
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plt.draw()
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plt.tight_layout()
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out_file = io.BytesIO()
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fig.savefig(out_file, format=st.session_state.get("export_format", ".tiff")[1:], dpi=300, bbox_inches='tight')
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out_file.seek(0)
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return out_file.getvalue()
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@st.cache_resource
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def load_data(file):
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# 读取数据文件
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if file is not None:
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try:
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data = pd.read_excel(file) if file.name.endswith((".xlsx", ".xls")) else pd.read_csv(file)
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except Exception as e:
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st.error(f"Error reading file: {e}")
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exit()
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else:
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exit()
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INFLU_FACTORS = [0.5] * data.shape[0] * 2 # 动态创建数组
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ene = data["Energy"].to_numpy()
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K_POS = np.where(ene[1:]>ene[:1],0.03,-0.05)
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K_POS = [-0.05] + K_POS.tolist()
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st.info(K_POS)
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data["Energy"] -= data["Energy"][0]
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data["Energy"]*=627.509
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return data, INFLU_FACTORS,K_POS
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out_file = io.BytesIO()
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st.set_page_config(
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page_title="反应坐标绘制",
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page_icon=":chart_with_upwards_trend:",
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layout="wide",
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initial_sidebar_state="expanded"
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)
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st.title("反应坐标绘制")
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st.write("---")
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col1,col2,col3 = st.columns([0.4,0.25,0.25],gap="medium")
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with col1:
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file = st.file_uploader("上传能量文件", type=["xlsx", "xls", "csv"])
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data, INFLU_FACTORS,K_POS = load_data(file)
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fig,lines = plot_reaction_coordinate()
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stfig = st.pyplot(fig,False)
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st.slider("字体大小",8,20, value=12, key="font_size",
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on_change=lambda: plt.rcParams.update({'font.size': st.session_state.get("font_size", 12)}))
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st.selectbox("导出文件拓展名",[".tiff",".pdf",".png",".pgf"],key="export_format")
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st.download_button(
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label="Download Plot",
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data=on_save(),
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file_name="reaction_coordinate"+st.session_state.get("export_format", ".tiff"),
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# mime="image/tiff"
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)
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with col2:
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st.write("调整滑块以改变反应坐标图曲线形状。")
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for i in range(data.shape[0]):
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if i!=0:
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st.slider(
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f'{data.loc[i,"Name"]} 左',
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0.0, 1.0, value=INFLU_FACTORS[i*2-1],
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key=f'slider_{i*2}',
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on_change=callback_gen(i*2)
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)
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if i!= data.shape[0] - 1:
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st.slider(
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f'{data.loc[i,"Name"]} 右',
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0.0, 1.0, value=INFLU_FACTORS[i*2],
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key=f'slider_{i*2+1}',
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on_change=callback_gen(i*2+1)
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)
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with col3:
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st.write("调整参数以改变文字位置。")
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for i in range(data.shape[0]):
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st.slider(
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f'{data.loc[i,"Name"]}',
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-0.1, 0.1, value=K_POS[i],
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key=f'text_slider_{i}',
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on_change=callback_gen(i,1)
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)
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st.write("---")
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st.dataframe(data)
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4
cord/requirements.txt
Normal file
4
cord/requirements.txt
Normal file
@ -0,0 +1,4 @@
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matplotlib>=3.10.5
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openpyxl>=3.1.5
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pandas>=2.3.1
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streamlit>=1.47.1
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1271
mw_tool/main.py
1271
mw_tool/main.py
File diff suppressed because it is too large
Load Diff
581
mw_tool/main_old.py
Normal file
581
mw_tool/main_old.py
Normal file
@ -0,0 +1,581 @@
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||||
import streamlit as st
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||||
import pubchempy as pcp
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from rdkit import Chem
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from rdkit.Chem import rdMolDescriptors
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import requests
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||||
from io import BytesIO
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||||
st.set_page_config(
|
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page_title="质量及密度查询",
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||||
layout="wide"
|
||||
)
|
||||
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||||
# 初始化 session state
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||||
if 'compound_data' not in st.session_state:
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||||
st.session_state.compound_data = None
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||||
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||||
def search_compound(query):
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||||
"""搜索化合物信息"""
|
||||
try:
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||||
compounds = None
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||||
try:
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||||
comp = Chem.MolFromSmiles(query)
|
||||
if comp:
|
||||
compounds = pcp.get_compounds(query, 'smiles', listkey_count=3)
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||||
except Exception:
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||||
st.error("使用smiles精确查询失败")
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||||
# 尝试通过化学式搜索
|
||||
if not (isinstance(compounds, list) and len(compounds) != 0):
|
||||
# 尝试通过名称搜索
|
||||
try:
|
||||
compounds = pcp.get_compounds(query, 'name', listkey_count=3)
|
||||
except Exception:
|
||||
st.error("使用名称查询失败")
|
||||
|
||||
if not (isinstance(compounds, list) and len(compounds) != 0):
|
||||
try:
|
||||
compounds = pcp.get_compounds(query, 'formula', listkey_count=3)
|
||||
except Exception:
|
||||
st.error("使用化学式精确查询失败")
|
||||
|
||||
if isinstance(compounds, list) and len(compounds) > 0:
|
||||
st.info("成功查询物质基本信息，正在获取更多数据。")
|
||||
return compounds[0]
|
||||
else:
|
||||
return None
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||||
except Exception as e:
|
||||
st.error(f"搜索时发生错误: {str(e)}")
|
||||
# raise e
|
||||
return None
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||||
|
||||
def calculate_molecular_weight_from_smiles(smiles):
|
||||
"""从SMILES计算分子量"""
|
||||
try:
|
||||
mol = Chem.MolFromSmiles(smiles)
|
||||
if mol:
|
||||
return rdMolDescriptors.CalcExactMolWt(mol)
|
||||
else:
|
||||
return None
|
||||
except Exception as e:
|
||||
st.error(f"SMILES分子量计算错误: {str(e)}")
|
||||
return None
|
||||
|
||||
|
||||
def get_pubchem_properties(compound):
|
||||
"""从PubChem获取密度、熔点、沸点信息"""
|
||||
try:
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||||
# 初始化返回数据
|
||||
properties = {
|
||||
'density': None,
|
||||
'melting_point': None,
|
||||
'boiling_point': None
|
||||
}
|
||||
|
||||
cid = compound.cid
|
||||
|
||||
# 尝试获取物理化学性质相关的记录
|
||||
try:
|
||||
url = f"https://pubchem.ncbi.nlm.nih.gov/rest/pug_view/data/compound/{cid}/JSON?heading=Experimental+Properties"
|
||||
data = requests.get(url, timeout=3).json()
|
||||
for section in data["Record"]["Section"]:
|
||||
if section["TOCHeading"] == "Chemical and Physical Properties":
|
||||
for sub in section["Section"]:
|
||||
if sub["TOCHeading"] == "Experimental Properties":
|
||||
for prop in sub["Section"]:
|
||||
prop_heading = prop["TOCHeading"]
|
||||
|
||||
if prop_heading == "Density" and not properties['density']:
|
||||
# 可能有多条不同温度/浓度的记录，逐条返回
|
||||
properties['density'] = [
|
||||
info["Value"]["StringWithMarkup"][0]["String"]
|
||||
for info in prop["Information"]
|
||||
if "Value" in info and "StringWithMarkup" in info["Value"]
|
||||
]
|
||||
|
||||
elif prop_heading == "Melting Point" and not properties['melting_point']:
|
||||
properties['melting_point'] = [
|
||||
info["Value"]["StringWithMarkup"][0]["String"]
|
||||
for info in prop["Information"]
|
||||
if "Value" in info and "StringWithMarkup" in info["Value"]
|
||||
]
|
||||
|
||||
elif prop_heading == "Boiling Point" and not properties['boiling_point']:
|
||||
properties['boiling_point'] = [
|
||||
info["Value"]["StringWithMarkup"][0]["String"]
|
||||
for info in prop["Information"]
|
||||
if "Value" in info and "StringWithMarkup" in info["Value"]
|
||||
]
|
||||
|
||||
return properties
|
||||
|
||||
except Exception:
|
||||
return properties
|
||||
|
||||
except Exception as e:
|
||||
# 静默处理异常，返回空的properties字典
|
||||
return {
|
||||
'density': None,
|
||||
'melting_point': None,
|
||||
'boiling_point': None
|
||||
}
|
||||
|
||||
def sync_calculations(compound_data, mmol=None, mass=None, volume=None, changed_field=None):
|
||||
"""同步计算mmol、质量、体积"""
|
||||
if not compound_data:
|
||||
return mmol, mass, volume
|
||||
|
||||
# 确保数值类型转换
|
||||
try:
|
||||
molecular_weight = float(compound_data.get('molecular_weight', 0))
|
||||
density_select = compound_data.get('density_select', None)
|
||||
density = float(density_select) if density_select is not None else None
|
||||
except (ValueError, TypeError):
|
||||
st.error("分子量或密度数据格式错误，无法进行计算")
|
||||
return mmol, mass, volume
|
||||
|
||||
if molecular_weight == 0:
|
||||
return mmol, mass, volume
|
||||
|
||||
try:
|
||||
if changed_field == 'mmol' and mmol is not None:
|
||||
# 根据mmol计算质量
|
||||
mass = (mmol / 1000) * molecular_weight # mmol转mol再乘分子量
|
||||
# 如果有密度，计算体积
|
||||
if density and density > 0:
|
||||
volume = mass / density
|
||||
|
||||
elif changed_field == 'mass' and mass is not None:
|
||||
# 根据质量计算mmol
|
||||
mmol = (mass / molecular_weight) * 1000 # 质量除分子量得mol，再转mmol
|
||||
# 如果有密度，计算体积
|
||||
if density and density > 0:
|
||||
volume = mass / density
|
||||
|
||||
elif changed_field == 'volume' and volume is not None and density and density > 0:
|
||||
# 根据体积计算质量
|
||||
mass = volume * density
|
||||
# 根据质量计算mmol
|
||||
mmol = (mass / molecular_weight) * 1000
|
||||
|
||||
except Exception as e:
|
||||
st.error(f"计算错误: {str(e)}")
|
||||
|
||||
return mmol, mass, volume
|
||||
|
||||
# 主界面
|
||||
col1, col2 = st.columns([1, 2])
|
||||
|
||||
with col1:
|
||||
st.subheader("物质查询")
|
||||
query = st.text_input("输入化学式、名称或SMILES:", placeholder="例如: H2O, water, CCO")
|
||||
|
||||
# 添加直接计算分子量选项
|
||||
calc_mw_only = st.checkbox("仅计算分子量（不查询数据库）", help="勾选此项将跳过数据库查询，仅从SMILES计算分子量")
|
||||
|
||||
if st.button("查询" if not calc_mw_only else "计算", type="primary"):
|
||||
if query:
|
||||
with st.spinner("正在处理..."):
|
||||
# 如果选择仅计算分子量，直接从SMILES计算
|
||||
if calc_mw_only:
|
||||
mol_weight = calculate_molecular_weight_from_smiles(query)
|
||||
if mol_weight:
|
||||
compound_data = {
|
||||
'name': "用户输入化合物",
|
||||
'formula': "从SMILES计算",
|
||||
'molecular_weight': mol_weight,
|
||||
'melting_point': None,
|
||||
'density_src': None,
|
||||
'melting_point_src': None,
|
||||
'boiling_point_src': None,
|
||||
'smiles': query,
|
||||
"inchi": None,
|
||||
'found': False
|
||||
}
|
||||
st.session_state.compound_data = compound_data
|
||||
st.success("分子量计算完成！")
|
||||
else:
|
||||
st.error("输入的SMILES格式无效")
|
||||
st.session_state.compound_data = None
|
||||
else:
|
||||
# 原有的查询逻辑
|
||||
compound = search_compound(query)
|
||||
|
||||
if compound is not None:
|
||||
# 查询到化合物
|
||||
# 获取PubChem的物理化学性质信息
|
||||
pubchem_properties = get_pubchem_properties(compound)
|
||||
|
||||
compound_data = {
|
||||
'name': compound.iupac_name,
|
||||
'cid': compound.cid,
|
||||
'formula': compound.molecular_formula,
|
||||
'molecular_weight': compound.molecular_weight,
|
||||
"density_src": pubchem_properties['density'],
|
||||
'melting_point_src': pubchem_properties['melting_point'],
|
||||
'boiling_point_src': pubchem_properties['boiling_point'],
|
||||
'smiles': compound.canonical_smiles,
|
||||
"inchi": compound.inchi if hasattr(compound, 'inchi') else None,
|
||||
'found': True,
|
||||
}
|
||||
|
||||
|
||||
st.session_state.compound_data = compound_data
|
||||
|
||||
# 显示查询结果信息
|
||||
if compound_data['density_src'] or compound_data['melting_point_src'] or compound_data['boiling_point_src']:
|
||||
properties_found = []
|
||||
if compound_data['density_src']:
|
||||
properties_found.append("密度")
|
||||
if compound_data['melting_point_src']:
|
||||
properties_found.append("熔点")
|
||||
if compound_data['boiling_point_src']:
|
||||
properties_found.append("沸点")
|
||||
st.success(f"查询成功！（找到{', '.join(properties_found)}信息）")
|
||||
else:
|
||||
st.success("查询成功！（未找到物理性质信息）")
|
||||
|
||||
else:
|
||||
# 未查询到，检查是否为SMILES
|
||||
if query:
|
||||
mol_weight = calculate_molecular_weight_from_smiles(query)
|
||||
if mol_weight:
|
||||
compound_data = {
|
||||
'name': "未知化合物",
|
||||
'formula': "从SMILES计算",
|
||||
'molecular_weight': mol_weight,
|
||||
'melting_point': None,
|
||||
'density_src': None,
|
||||
'melting_point_src': None,
|
||||
'boiling_point_src': None,
|
||||
'smiles': query,
|
||||
"inchi": None,
|
||||
'found': False
|
||||
}
|
||||
st.session_state.compound_data = compound_data
|
||||
st.warning("⚠️ 未在数据库中找到，但已从SMILES计算分子量")
|
||||
else:
|
||||
st.error("❌ 未找到该化合物，且SMILES格式无效")
|
||||
st.session_state.compound_data = None
|
||||
|
||||
with col2:
|
||||
st.subheader("化合物信息")
|
||||
|
||||
if st.session_state.compound_data:
|
||||
data = st.session_state.compound_data
|
||||
|
||||
# 显示基本信息
|
||||
info_col1, info_col2 = st.columns(2)
|
||||
|
||||
with info_col1:
|
||||
st.metric("物质名称", data['name'])
|
||||
try:
|
||||
molecular_weight_value = float(data['molecular_weight'])
|
||||
st.metric("分子量 (g/mol)", f"{molecular_weight_value:.3f}")
|
||||
except (ValueError, TypeError):
|
||||
st.metric("分子量 (g/mol)", "数据格式错误")
|
||||
|
||||
with info_col2:
|
||||
st.metric("化学式", data['formula'])
|
||||
if data.get("cid"):
|
||||
st.markdown("### 其他数据")
|
||||
st.page_link(f"https://pubchem.ncbi.nlm.nih.gov/compound/{data['cid']}",label="**访问PubChem**")
|
||||
st.image(f"https://pubchem.ncbi.nlm.nih.gov/image/imgsrv.fcgi?cid={data['cid']}&t=s","结构式")
|
||||
|
||||
# 添加熔沸点信息的展开区域
|
||||
if data.get('melting_point_src') or data.get('boiling_point_src'):
|
||||
with st.expander("熔沸点信息", expanded=False):
|
||||
col1, col2 = st.columns(2)
|
||||
with col1:
|
||||
if data.get('melting_point_src'):
|
||||
st.markdown("### 熔点数据")
|
||||
melting_data = data['melting_point_src']
|
||||
if isinstance(melting_data, list):
|
||||
for i, mp in enumerate(melting_data, 1):
|
||||
st.write(f"{i}. {mp}")
|
||||
else:
|
||||
st.write(melting_data)
|
||||
with col2:
|
||||
if data.get('boiling_point_src'):
|
||||
st.markdown("### 沸点数据")
|
||||
boiling_data = data['boiling_point_src']
|
||||
if isinstance(boiling_data, list):
|
||||
for i, bp in enumerate(boiling_data, 1):
|
||||
st.write(f"{i}. {bp}")
|
||||
else:
|
||||
st.write(boiling_data)
|
||||
|
||||
# 判断是否为液体
|
||||
melting_data = data['melting_point_src']
|
||||
if isinstance(melting_data, list) and len(melting_data) > 0:
|
||||
import re
|
||||
melting_point = re.search(r'\d*\.\d+', melting_data[0])
|
||||
if melting_point:
|
||||
melting_point = float(melting_point.group())
|
||||
|
||||
# 检测值变化并执行计算
|
||||
def handle_change(field_name, new_value, current_value):
|
||||
try:
|
||||
# 确保都转换为浮点数
|
||||
new_value = float(new_value) if new_value is not None else 0.0
|
||||
current_value = float(current_value) if current_value is not None else 0.0
|
||||
|
||||
if abs(new_value - current_value) > 1e-6: # 避免浮点数比较问题
|
||||
# 同步计算 - 确保数据类型正确
|
||||
try:
|
||||
calc_data = {
|
||||
'molecular_weight': float(data['molecular_weight']),
|
||||
'density_select': float(st.session_state.get('density_select', 0)) if (show_density and st.session_state.get('density_select')) else None
|
||||
}
|
||||
except (ValueError, TypeError):
|
||||
st.error("化合物数据格式错误，无法进行计算")
|
||||
return
|
||||
|
||||
mmol_calc = mass_calc = volume_calc = 0.0
|
||||
|
||||
if field_name == 'mmol':
|
||||
mmol_calc, mass_calc, volume_calc = sync_calculations(
|
||||
calc_data, new_value, None, None, 'mmol'
|
||||
)
|
||||
elif field_name == 'mass':
|
||||
mmol_calc, mass_calc, volume_calc = sync_calculations(
|
||||
calc_data, None, new_value, None, 'mass'
|
||||
)
|
||||
elif field_name == 'volume':
|
||||
mmol_calc, mass_calc, volume_calc = sync_calculations(
|
||||
calc_data, None, None, new_value, 'volume'
|
||||
)
|
||||
elif field_name == 'density':
|
||||
# 密度变化时，如果已有质量，重新计算体积；如果已有体积，重新计算质量
|
||||
current_mass = st.session_state.mass_val
|
||||
current_volume = st.session_state.volume_val
|
||||
|
||||
if current_mass > 0:
|
||||
# 根据质量重新计算体积
|
||||
mmol_calc, mass_calc, volume_calc = sync_calculations(
|
||||
calc_data, None, current_mass, None, 'mass'
|
||||
)
|
||||
elif current_volume > 0:
|
||||
# 根据体积重新计算质量
|
||||
mmol_calc, mass_calc, volume_calc = sync_calculations(
|
||||
calc_data, None, None, current_volume, 'volume'
|
||||
)
|
||||
else:
|
||||
return # 没有质量或体积数据，无需重新计算
|
||||
|
||||
# 更新session state
|
||||
st.session_state.mmol_val = float(mmol_calc) if mmol_calc is not None else 0.0
|
||||
st.session_state.mass_val = float(mass_calc) if mass_calc is not None else 0.0
|
||||
st.session_state.volume_val = float(volume_calc) if volume_calc is not None else 0.0
|
||||
st.session_state.last_changed = field_name
|
||||
|
||||
# 强制刷新页面以更新输入框的值
|
||||
if field_name != 'density': # 密度变化时不需要rerun，因为已经在密度输入处理中rerun了
|
||||
st.rerun()
|
||||
except (ValueError, TypeError) as e:
|
||||
st.error(f"数值转换错误: {str(e)}")
|
||||
return
|
||||
|
||||
# 密度显示选项
|
||||
show_density = False
|
||||
if data['density_src']:
|
||||
show_density = st.checkbox("显示密度信息", value=False)
|
||||
|
||||
if show_density:
|
||||
import re
|
||||
|
||||
# 初始化密度值在session state中
|
||||
if 'density_select' not in st.session_state:
|
||||
st.session_state.density_select = None
|
||||
if 'density_input_value' not in st.session_state:
|
||||
st.session_state.density_input_value = 0.0
|
||||
|
||||
density_data = data['density_src']
|
||||
# print(density_data)
|
||||
|
||||
# 如果密度是列表且长度>1，让用户选择
|
||||
if isinstance(density_data, list) and len(density_data) > 1:
|
||||
st.markdown("**选择密度数据：**")
|
||||
|
||||
# 为每个密度选项提取数值并显示
|
||||
density_options = []
|
||||
density_values = []
|
||||
|
||||
for i, density_str in enumerate(density_data):
|
||||
# 使用正则表达式提取密度数值
|
||||
match = re.search(r'\d*\.\d+', str(density_str))
|
||||
if match:
|
||||
extracted_value = float(match.group())
|
||||
density_options.append(f"{extracted_value:.3f}: {density_str}")
|
||||
density_values.append(extracted_value)
|
||||
else:
|
||||
density_options.append(f"0.000: {density_str} (无法提取数值)")
|
||||
density_values.append(None)
|
||||
|
||||
# 用户选择密度
|
||||
selected_index = st.selectbox(
|
||||
"选择要使用的密度数据:",
|
||||
range(len(density_options)),
|
||||
format_func=lambda x: density_options[x],
|
||||
key="density_selector"
|
||||
)
|
||||
|
||||
# 获取选中的密度值
|
||||
if density_values[selected_index] is not None:
|
||||
selected_density_value = density_values[selected_index]
|
||||
st.session_state.density_select = selected_density_value
|
||||
|
||||
# 显示并允许用户修改密度值
|
||||
st.markdown("**密度值 (可修改)：**")
|
||||
new_density = st.number_input(
|
||||
"密度 (g/mL)",
|
||||
min_value=0.0,
|
||||
value=float(st.session_state.density_select),
|
||||
step=0.001,
|
||||
format="%.3f",
|
||||
key="density_input",
|
||||
help="选择的密度值，可以手动修改"
|
||||
)
|
||||
|
||||
# 检测密度值变化
|
||||
if abs(new_density - st.session_state.density_input_value) > 1e-6:
|
||||
st.session_state.density_select = new_density
|
||||
st.session_state.density_input_value = new_density
|
||||
# 更新compound_data中的密度值用于计算
|
||||
st.session_state.compound_data['density_select'] = new_density
|
||||
handle_change('density', 1, 0)
|
||||
st.rerun()
|
||||
|
||||
else:
|
||||
st.error("所选密度数据无法提取有效数值")
|
||||
|
||||
# 如果密度是单个值或列表长度为1
|
||||
else:
|
||||
try:
|
||||
if isinstance(density_data, list):
|
||||
density_str = str(density_data[0])
|
||||
else:
|
||||
density_str = str(density_data)
|
||||
|
||||
# 提取密度数值
|
||||
match = re.search(r'\d*\.\d+', density_str)
|
||||
if match:
|
||||
density_value = float(match.group())
|
||||
st.session_state.density_select = density_value
|
||||
|
||||
# 显示并允许用户修改密度值
|
||||
st.markdown("**密度值 (可修改)：**")
|
||||
new_density = st.number_input(
|
||||
"密度 (g/mL)",
|
||||
min_value=0.0,
|
||||
value=float(st.session_state.density_select),
|
||||
step=0.001,
|
||||
format="%.3f",
|
||||
key="density_input_single",
|
||||
help="提取的密度值，可以手动修改"
|
||||
)
|
||||
|
||||
# 检测密度值变化
|
||||
if abs(new_density - st.session_state.density_input_value) > 1e-6:
|
||||
st.session_state.density_select = new_density
|
||||
st.session_state.density_input_value = new_density
|
||||
# 更新compound_data中的密度值用于计算
|
||||
st.session_state.compound_data['density_select'] = new_density
|
||||
handle_change('density', 1, 0)
|
||||
st.rerun()
|
||||
else:
|
||||
st.error("无法从密度数据中提取有效数值")
|
||||
except (ValueError, TypeError):
|
||||
st.error("密度数据格式错误")
|
||||
|
||||
st.markdown("---")
|
||||
|
||||
# 计算器部分
|
||||
st.subheader("用量计算器")
|
||||
|
||||
# 初始化值
|
||||
if 'mmol_val' not in st.session_state:
|
||||
st.session_state.mmol_val = 0.0
|
||||
if 'mass_val' not in st.session_state:
|
||||
st.session_state.mass_val = 0.0
|
||||
if 'volume_val' not in st.session_state:
|
||||
st.session_state.volume_val = 0.0
|
||||
if 'last_changed' not in st.session_state:
|
||||
st.session_state.last_changed = None
|
||||
|
||||
# 创建响应式列布局
|
||||
density_select = st.session_state.get('density_select')
|
||||
if show_density and density_select is not None:
|
||||
calc_col1, calc_col2, calc_col3 = st.columns([1, 1, 1])
|
||||
else:
|
||||
calc_col1, calc_col2 = st.columns([1, 1])
|
||||
calc_col3 = None
|
||||
|
||||
|
||||
with calc_col1:
|
||||
st.markdown("**物质的量**")
|
||||
new_mmol = st.number_input(
|
||||
"用量 (mmol)",
|
||||
min_value=0.0,
|
||||
value=float(st.session_state.mmol_val),
|
||||
step=0.1,
|
||||
format="%.3f",
|
||||
key="mmol_input",
|
||||
help="输入或计算得到的物质的量，单位：毫摩尔"
|
||||
)
|
||||
|
||||
|
||||
# 检测mmol变化
|
||||
if st.session_state.last_changed != 'mmol':
|
||||
handle_change('mmol', new_mmol, st.session_state.mmol_val)
|
||||
|
||||
with calc_col2:
|
||||
st.markdown("**质量**")
|
||||
new_mass = st.number_input(
|
||||
"质量 (g)",
|
||||
min_value=0.0,
|
||||
value=float(st.session_state.mass_val),
|
||||
step=0.001,
|
||||
format="%.3f",
|
||||
key="mass_input",
|
||||
help="输入或计算得到的质量，单位：克"
|
||||
)
|
||||
|
||||
# 检测mass变化
|
||||
if st.session_state.last_changed != 'mass':
|
||||
handle_change('mass', new_mass, st.session_state.mass_val)
|
||||
|
||||
if calc_col3 is not None:
|
||||
with calc_col3:
|
||||
st.markdown("**体积**")
|
||||
new_volume = st.number_input(
|
||||
"体积 (mL)",
|
||||
min_value=0.0,
|
||||
value=float(st.session_state.volume_val),
|
||||
step=0.01,
|
||||
format="%.3f",
|
||||
key="volume_input",
|
||||
help="输入或计算得到的体积，单位：毫升"
|
||||
)
|
||||
|
||||
# 检测volume变化
|
||||
if st.session_state.last_changed != 'volume':
|
||||
handle_change('volume', new_volume, st.session_state.volume_val)
|
||||
|
||||
# 重置last_changed状态
|
||||
st.session_state.last_changed = None
|
||||
|
||||
|
||||
# 清零按钮
|
||||
if st.button("清零所有数值", type="secondary"):
|
||||
st.session_state.mmol_val = 0.0
|
||||
st.session_state.mass_val = 0.0
|
||||
st.session_state.volume_val = 0.0
|
||||
st.session_state.last_changed = None
|
||||
st.rerun()
|
||||
st.session_state.mmol_val = 0.0
|
||||
st.session_state.mass_val = 0.0
|
||||
st.session_state.volume_val = 0.0
|
||||
st.rerun()
|
||||
|
||||
else:
|
||||
st.info("请在左侧输入要查询的化学物质")
|
||||
@ -1,3 +1,5 @@
|
||||
streamlit>=1.28.0
|
||||
pubchempy>=1.0.4
|
||||
rdkit>=2022.9.5
|
||||
requests>=2.25.0
|
||||
Pillow>=8.0.0
|
||||
molmass
|
||||
Reference in New Issue
Block a user