reaction cord

cord/main.py

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+from matplotlib import pyplot as plt
+import pandas as pd
+import numpy as np
+import io
+import streamlit as st
+# import scienceplots
+
+# plt.style.use(['nature', 'no-latex',"cjk-sc-font"])
+plt.rcParams['font.family'] = 'sans-serif'
+plt.rcParams['font.sans-serif'] = ['SimHei']  # 设置中文字体
+plt.rcParams['axes.unicode_minus'] = False  # 解决负号显示问题
+
+def cubic_bezier_with_zero_derivatives(p0, p1, t_array, influence_factor):
+    """
+    创建三次贝塞尔曲线，确保起点和终点的导数为0
+    
+    参数:
+    p0: 起点 [x0, y0]
+    p1: 终点 [x1, y1]
+    t_array: 参数数组 (0到1)
+    influence_factor: 影响因子，控制控制点的位置
+    
+    返回:
+    x_array, y_array: 贝塞尔曲线上的点
+    """
+    x0, y0 = p0
+    x1, y1 = p1
+    
+    # 计算控制点，确保起点和终点导数为0
+    # 控制点位置基于影响因子和两点间距离
+    dx = x1 - x0
+    
+    # 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）
+    p1_control = [x0 + dx * influence_factor[0], y0]
+    
+    # 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）
+    p2_control = [x1 - dx * influence_factor[1], y1]
+    
+    # 计算贝塞尔曲线
+    x_bezier = ((1-t_array)**3 * x0 + 
+                3*(1-t_array)**2 * t_array * p1_control[0] + 
+                3*(1-t_array) * t_array**2 * p2_control[0] + 
+                t_array**3 * x1)
+    
+    y_bezier = ((1-t_array)**3 * y0 + 
+                3*(1-t_array)**2 * t_array * p1_control[1] + 
+                3*(1-t_array) * t_array**2 * p2_control[1] + 
+                t_array**3 * y1)
+    
+    return x_bezier, y_bezier
+
+# @st.cache_resource
+def plot_reaction_coordinate(changed=None, _lines=None):
+    """
+    绘制反应坐标图
+    """
+    # if changed is not None:
+    #     if _lines is None:
+    #         raise ValueError("Lines must be provided when changing a slider.")
+    #     lines = _lines
+    #     i = changed//2
+    #     x,y = lines[i].get_data()
+    #     p1=x[0],y[0]
+    #     p2=x[-1],y[-1]
+    #     print(INFLU_FACTORS[i*2+1:i*2+3])
+    #     line = cubic_bezier_with_zero_derivatives(p1,p2, np.linspace(0, 1, 300), INFLU_FACTORS[i*2+1:i*2+3])
+    #     # lines[i].set_data([],[])
+    #     lines[i].set_data(line[0], line[1])
+    #     return
+    
+    
+    
+    lines = []
+    fig,ax1 = plt.subplots(figsize=(9, 6))
+
+    last=(-1,-1)
+    
+    maxy = data["Energy"].max()
+    miny = data["Energy"].min()
+    varyy = maxy - miny
+    
+    for i in range(data.shape[0]):
+        line:pd.Series = data.loc[i]
+        if last == (-1,-1):
+            last = (1, line["Energy"])
+            if not pd.isna(line["Name"]):
+                ax1.annotate(str(line["Name"]), (1, line["Energy"]+varyy*0.03), ha='center')
+        else:
+            p1 = last[0]+2,line["Energy"]
+            x,y = cubic_bezier_with_zero_derivatives(last,p1, np.linspace(0, 1, 300), INFLU_FACTORS[(i*2-2):i*2])
+            l = ax1.plot(x, y, "-", color="black")[0]
+            lines.append(l)
+            if not pd.isna(line["Name"]):
+                p = p1[0],p1[1]+varyy*0.03
+                ax1.annotate(str(line["Name"]), p, ha='center')
+            last = p1
+        
+        
+
+    ax1.set_xlabel("Reaction Coordinate")
+    ax1.xaxis.set_ticks([])
+    ax1.set_ylabel("Energy (Hartree)")
+    ax1.set_ylim(miny-varyy*0.1, maxy+varyy*0.1)
+    return fig,lines
+
+# 创建图形和坐标轴
+
+def callback_gen(x):
+    def callback():
+        global INFLU_FACTORS
+        INFLU_FACTORS[x-1] = st.session_state.get(f'slider_{x}', 0.5)
+        plot_reaction_coordinate(changed=x, _lines=lines)
+
+    return callback
+
+def on_save():
+    global out_file
+    # for slider in slides:
+    # slider.ax.set_visible(False)
+    plt.draw()
+    plt.tight_layout()
+    out_file = io.BytesIO()
+    fig.savefig(out_file, format=st.session_state.get("export_format", ".tiff")[1:], dpi=300, bbox_inches='tight')
+    out_file.seek(0)
+    return out_file.getvalue()
+
+@st.cache_resource
+def load_data(file):
+    # 读取数据文件
+    if file is not None:
+        try:
+            data = pd.read_excel(file) if file.name.endswith((".xlsx", ".xls")) else pd.read_csv(file)
+        except Exception as e:
+            st.error(f"Error reading file: {e}")
+            exit()
+    else:
+        exit()
+
+    num_factors = data.shape[0] * 2
+    INFLU_FACTORS = [0.5] * data.shape[0] * 2  # 动态创建数组
+
+
+    return data, INFLU_FACTORS
+
+
+out_file = io.BytesIO()
+st.set_page_config(
+    page_title="反应坐标绘制",
+    page_icon=":chart_with_upwards_trend:",
+    layout="centered",
+    initial_sidebar_state="expanded"
+)
+st.title("反应坐标绘制")
+st.write("---")
+col1,col2 = st.columns([0.7,0.3],gap="medium")
+
+with col1:
+    file = st.file_uploader("上传能量文件", type=["xlsx", "xls", "csv"])
+    data, INFLU_FACTORS = load_data(file)
+
+    fig,lines = plot_reaction_coordinate()
+    stfig = st.pyplot(fig,False)
+    st.selectbox("导出文件拓展名",[".tiff",".pdf",".png",".pgf"],key="export_format")
+    st.download_button(
+            label="Download Plot",
+            data=on_save(),
+            file_name="reaction_coordinate"+st.session_state.get("export_format", ".tiff"),
+            # mime="image/tiff"
+        )
+with col2:
+    st.write("调整滑块以改变反应坐标图曲线形状。")
+    for i in range(data.shape[0]):
+        if i!=0:
+            st.slider(
+                f'{data.loc[i,"Name"]} 左',
+                0.0, 1.0, value=INFLU_FACTORS[i*2-1],
+                key=f'slider_{i*2}',
+                on_change=callback_gen(i*2)
+            )
+        if i!= data.shape[0] - 1:
+            st.slider(
+                f'{data.loc[i,"Name"]} 右',
+                0.0, 1.0, value=INFLU_FACTORS[i*2],
+                key=f'slider_{i*2+1}',
+                on_change=callback_gen(i*2+1)
+            )
+
+st.write("---")
+st.dataframe(data)

cord/pyproject.toml

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+[project]
+name = "tmp2"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.10"
+dependencies = [
+    "matplotlib>=3.10.5",
+    "openpyxl>=3.1.5",
+    "pandas>=2.3.1",
+    "streamlit>=1.47.1",
+]