import gradio as gr import pandas as pd import json from tempfile import NamedTemporaryFile import NDfilter import NDplot ## 核素筛选 def process_filters(Z_min, Z_max, Z_oe_idx, N_min, N_max, N_oe_idx, A_min, A_max, A_oe_idx, hl_enable_idx, hl_min, hl_min_unit, hl_max, hl_max_unit, dm_enable_idx, decay_modes): filtered_data = NDfilter.nuclidesFilterZNA(nuclides_data, Z_min, Z_max, Z_oe_idx, N_min, N_max, N_oe_idx, A_min, A_max, A_oe_idx) # 根据母核半衰期进行筛选 if hl_enable_idx == 1: hl_min_sec = HLunit_convert(hl_min, hl_min_unit) hl_max_sec = HLunit_convert(hl_max, hl_max_unit) filtered_data = NDfilter.nuclidesFilterHalflife(filtered_data, hl_min_sec, hl_max_sec) # 根据衰变模式进行筛选 if dm_enable_idx > 0 and decay_modes: filtered_data = NDfilter.nuclidesFilterDecayModes(filtered_data, dm_enable_idx, decay_modes) # 结果处理 if len(filtered_data) == 0: result_text = "没有找到符合条件的核素" result_file_path = None else: result_text = f"找到 {len(filtered_data)} 个符合条件的核素" with NamedTemporaryFile(suffix=".json", delete=False, mode='w') as file: json.dump(filtered_data, file, indent=2) result_file_path = file.name return result_text, result_file_path ## 核素查找 def process_search(mode_idx, nom, z, n, a, preview_mode, file_type): result = None if mode_idx == 0: result = NDfilter.nuclidesSearchingNom(nuclides_data, nom.replace(" ", "")) elif mode_idx == 1: if not (z == None or n == None): result = NDfilter.nuclidesSearchingZN(nuclides_data, z, n) elif mode_idx == 2: if not (z == None or a == None): result = NDfilter.nuclidesSearchingZA(nuclides_data, z, a) elif mode_idx == 3: if not (n == None or a == None): result = NDfilter.nuclidesSearchingNA(nuclides_data, n, a) ## 结果处理 if result == None: result_text = "没有找到此核素" result_dataframe = None result_file_path = None else: ## 文本 name = result["name"] result_text = f"{name}" if len(result["levels"]) == 0: result_text = result_text + "\n此核素无数据" result_text = result_text + "\n\nnndc页面：\n\ngetdataset:\n" + f"https://www.nndc.bnl.gov/nudat3/getdataset.jsp?nucleus={name}&unc=NDS" ## temp with open ("data/haveDecayPage.json",'r', encoding='utf-8') as file: haveDecayPage = json.load(file) if haveDecayPage[name]: result_text = result_text + "\n\ndecaysearchdirect:\n" + f"https://www.nndc.bnl.gov/nudat3/decaysearchdirect.jsp?nuc={name}&unc=NDS" ## 预览表格 if preview_mode == 0: result_dataframe = NDfilter.nuclideData_dict2dataframeCompact(result) elif preview_mode == 1: result_dataframe = NDfilter.nuclideData_dict2dataframe(result) ## 文件 if file_type == 0: with NamedTemporaryFile(suffix=".json", delete=False, mode='w') as file: json.dump(result, file, indent=2) result_file_path = file.name elif file_type == 1: if preview_mode == 1: tmpDataframe = result_dataframe else: tmpDataframe = NDfilter.nuclideData_dict2dataframe(result) with NamedTemporaryFile(suffix=".csv", delete=False, mode='w') as file: tmpDataframe.to_csv(file, index=False) result_file_path = file.name else: result_file_path = None return result_text, result_dataframe, result_file_path ## 核素图绘制 def process_plot(plot_mode, text_mode, have_legend_idx, file_type3, using_filter, Z_min=0, Z_max=118, N_min=0, N_max=177): if have_legend_idx == 0: have_legend = True else: have_legend = False area = ((0,0),(118,177)) if using_filter == 1: area = ((Z_min,N_min), (Z_max, N_max)) result_fig = NDplot.nucildesChartPlotPLT(plot_mode, area, text_mode, have_legend) with NamedTemporaryFile(suffix=".svg", delete=False, mode='wb') as file: result_fig.savefig(file, format="svg") preview_svg_path = file.name if file_type3 == "png": with NamedTemporaryFile(suffix=".png", delete=False, mode='wb') as file: result_fig.savefig(file, format="png") result_file_path = file.name elif file_type3 == "svg": result_file_path = preview_svg_path else: result_file_path = None return result_fig, result_file_path ## 半衰期单位转换 def HLunit_convert(hl, hl_unit): if hl_unit == "Stable": hl_sec = None else: hl_sec = hl * HL_UNITS[hl_unit] return hl_sec ## 处理查找页面输入组件激活情况 def update_inputs2(mode_idx): if mode_idx == 0: # 核素名称模式 return [gr.Textbox(interactive=True), gr.Number(interactive=False, value=None), gr.Number(interactive=False, value=None), gr.Number(interactive=False, value=None)] elif mode_idx == 1: # Z+N模式 return [gr.Textbox(interactive=False, value=None), gr.Number(interactive=True), gr.Number(interactive=True), gr.Number(interactive=False, value=None)] elif mode_idx == 2: # Z+A模式 return [gr.Textbox(interactive=False, value=None), gr.Number(interactive=True), gr.Number(interactive=False, value=None), gr.Number(interactive=True)] elif mode_idx == 3: # N+A模式 return [gr.Textbox(interactive=False, value=None), gr.Number(interactive=False, value=None), gr.Number(interactive=True), gr.Number(interactive=True)] else: return [gr.Textbox(interactive=False, value=None), gr.Number(interactive=False, value=None), gr.Number(interactive=False, value=None), gr.Number(interactive=False, value=None)] def update_inputs3(using_filter): if using_filter == 0: return [gr.Number(interactive=False, value=None)] * 4 elif using_filter == 1: return [gr.Number(interactive=True)] * 4 else: return [gr.Number(interactive=False, value=None)] * 4 ## 导入数据集 nuclides_data_path = "data/nndc_nudat_data_export.json" with open (nuclides_data_path,'r', encoding='utf-8') as file: nuclides_data = json.load(file) ## 半衰期单位转换字典 HL_UNITS = {"fs": 1e-15, "ps": 1e-12, "ns": 1e-9, "us": 1e-6, "ms": 1e-3, "s": 1, "m": 60, "h": 3600, "d": 86400, "y": 31557600, "ky": 31557600e3, "My": 31557600e6, "Gy": 31557600e9} with gr.Blocks(title="核数据工具") as demo: gr.Markdown(""" ## 核数据工具 可能是用来处理核数据的相关工具？？ 目前功能有：核素筛选、核素查找、核素图绘制。 """) with gr.Tab("核素筛选"): gr.Markdown(""" ## 核素筛选 可以通过质子数(Z)、中子数(N)、质量数(A)以及母核半衰期、衰变模式等进行筛选 """) with gr.Row(): with gr.Column(scale=1): gr.Markdown("根据质子数(Z)、中子数(N)、质量数(A)进行筛选") with gr.Column(scale=4): with gr.Row(): with gr.Column(min_width=240): gr.Markdown("质子数(Z)") Z_min = gr.Number(label="最小值", precision=0) Z_max = gr.Number(label="最大值", precision=0) Z_oe = gr.Dropdown(["任意", "奇Z", "偶Z"], label="奇偶", type="index", interactive=True) with gr.Column(min_width=240): gr.Markdown("中子数(N)") N_min = gr.Number(label="最小值", precision=0) N_max = gr.Number(label="最大值", precision=0) N_oe = gr.Dropdown(["任意", "奇N", "偶N"], label="奇偶", type="index", interactive=True) with gr.Column(min_width=240): gr.Markdown("质量数(A)") A_min = gr.Number(label="最小值", precision=0) A_max = gr.Number(label="最大值", precision=0) A_oe = gr.Dropdown(["任意", "奇A", "偶A"], label="奇偶", type="index", interactive=True) with gr.Row(): with gr.Column(scale=1): gr.Markdown("根据母核半衰期进行筛选") with gr.Column(scale=4): with gr.Row(): hl_enable = gr.Radio(["不使用", "使用"], value="不使用", type="index", show_label=False) hl_min = gr.Number(label="最小值", minimum=0.) hl_min_unit = gr.Dropdown(["fs", "ps", "ns", "us", "ms", "s", "m", "h", "d", "y", "ky", "My", "Gy", "Stable"], value="fs", interactive=True) hl_max = gr.Number(label="最大值", minimum=0.) hl_max_unit = gr.Dropdown(["fs", "ps", "ns", "us", "ms", "s", "m", "h", "d", "y", "ky", "My", "Gy", "Stable"], value="Stable", interactive=True) with gr.Row(): with gr.Column(scale=1): gr.Markdown("根据衰变模式进行筛选") with gr.Column(scale=4): with gr.Row(): dm_enable_idx = gr.Radio(["不使用", "筛选包含所有以下所选衰变模式的核素(and)", "筛选包含任意以下所选衰变模式的核素(or)"], value="不使用", type="index", interactive=True, show_label=False) with gr.Row(): decayModes = gr.CheckboxGroup(['B-', 'N', '2N', 'B-N', 'P', 'B-A', 'B-2N', 'B-3N', '2P', 'EC', 'A', 'B-4N', 'EC+B+', 'ECA', 'ECP', 'IT', 'EC2P', 'EC3P', 'ECAP', '3P', '2B-', 'ECSF', '14C', 'B-SF', '24NE', 'SF', '20O', '20NE', '25NE', '28MG', 'NE', '22NE', 'SI', 'MG', '34SI'], label="decayModes", interactive=True) with gr.Row(): submit_btn = gr.Button("筛选", variant="primary") reset_btn = gr.Button("重置条件", variant="primary") with gr.Row(): result_text = gr.Textbox(label="筛选结果", interactive=False, show_copy_button=True) result_file = gr.File(label="结果文件", interactive=False) inputs = [ Z_min, Z_max, Z_oe, N_min, N_max, N_oe, A_min, A_max, A_oe, hl_enable, hl_min, hl_min_unit, hl_max, hl_max_unit, dm_enable_idx, decayModes ] submit_btn.click( fn=process_filters, inputs=inputs, outputs=[result_text, result_file] ) reset_btn.click( fn=lambda: [None,None,"任意"]*3 + ["不使用", None, "fs", None, "Stable"] + ["不使用", []], outputs=inputs ) with gr.Tab("核素查找"): gr.Markdown("## 核素查找") with gr.Row(): with gr.Column(scale=3): searchingMode = gr.Radio(["核素名称", "质子数(Z)、中子数(N)", "质子数(Z)、质量数(A)", "中子数(N)、质量数(A)"], value="核素名称", label="查找模式", interactive=True, type="index") gr.Markdown("### 根据核素名称查找") nuclide_in = gr.Textbox(value=None, info="请输入由质量数及元素名称所组成的核素名称，示例：232Th、232TH、th232、232-Th、th-232等。\n只要不太离谱就能识别……大概？") gr.Markdown("### 根据质子数(Z)、中子数(N)、质量数(A)查找") with gr.Row(): Z_in = gr.Number(value=0, label="质子数(Z)", precision=0, interactive=False) N_in = gr.Number(value=0, label="中子数(N)", precision=0, interactive=False) A_in = gr.Number(value=0, label="质量数(A)", precision=0, interactive=False) previewMode = gr.Radio(["紧凑", "常规"], value="紧凑", type="index", label="预览模式") outputFileType = gr.Radio(["json", "csv"], value="json", type="index", label="导出文件格式") with gr.Row(): submit_btn2 = gr.Button("查找", variant="primary") reset_btn2 = gr.Button("重置条件", variant="primary") with gr.Column(scale=2): result_text2 = gr.Textbox(interactive=False, show_label=False) preview_df = gr.Dataframe(label="数据预览", interactive=False) result_file2 = gr.File(interactive=False) searchingMode.change( fn=update_inputs2, inputs=searchingMode, outputs=[nuclide_in, Z_in, N_in, A_in] ) inputs2 = [ searchingMode, nuclide_in, Z_in, N_in, A_in, previewMode, outputFileType ] submit_btn2.click( fn=process_search, inputs=inputs2, outputs=[result_text2, preview_df, result_file2] ) reset_btn2.click( fn=lambda: [None]*4, outputs=[nuclide_in, Z_in, N_in, A_in] ) with gr.Tab("核素图绘制"): gr.Markdown(""" ## 核素图绘制 可根据半衰期、衰变模式、合成方法等分类模式绘制核素图。 部分代码参考了Ming-Hao-Zhang的[Nuclei-Chart-Generator](https://github.com/Ming-Hao-Zhang/Nuclei-Chart-Generator) """) with gr.Row(): with gr.Column(scale=3): img_preview = gr.Plot(label="图片预览") with gr.Column(scale=2): plot_mode = gr.Radio(["寿命", "衰变模式", "合成方法"], value="寿命", label="核素分类模式", type="index") text_mode = gr.Radio(["无", "元素名称", "核素名称", "详细信息"], value="无", label="显示信息", type="index") have_legend_idx = gr.Radio(["显示图例", "隐藏图例"], value="显示图例", label="图例", type="index") file_type3 = gr.Radio(["svg", "png"], value="svg", label="导出格式", info="png为位图格式，svg为矢量图格式。\n显示详细信息时，受分辨率限制，png格式将会失真。如需高清晰度图像，请使用svg。") with gr.Accordion(open=False, label="更多选项") as filter3: gr.Markdown("根据质子数(Z)、中子数(N)筛选 (未启用)") using_filter = gr.Radio(["不使用", "使用"], value="不使用", show_label=False, type='index', interactive=False) with gr.Row(): with gr.Column(min_width=120): gr.Markdown("质子数(Z)") Z_min = gr.Number(label="最小值", precision=0, interactive=False) Z_max = gr.Number(label="最大值", precision=0, interactive=False) with gr.Column(min_width=120): gr.Markdown("中子数(N)") N_min = gr.Number(label="最小值", precision=0, interactive=False) N_max = gr.Number(label="最大值", precision=0, interactive=False) with gr.Row(): submit_btn3 = gr.Button("绘制", variant="primary") reset_btn3 = gr.Button("重置条件", variant="primary") result_file3 = gr.File(interactive=False) using_filter.change( fn=update_inputs3, inputs=using_filter, outputs=[Z_min, Z_max, N_min, N_max] ) filter3.collapse( fn=lambda: "不使用", outputs= using_filter ) inputs3 = [plot_mode, text_mode, have_legend_idx, file_type3, using_filter, Z_min, Z_max, N_min, N_max] submit_btn3.click( fn=process_plot, inputs=inputs3, outputs=[img_preview, result_file3] ) reset_btn3.click( fn=lambda: ["寿命", "无", "显示图例", "svg", "不使用"] + [None]*4, outputs=inputs3 ) demo.launch()