NDplot

.gitignore

@@ -0,0 +1,2 @@
+__pycache__/*
+.vscode/*

NDfilter.py

@@ -6,6 +6,7 @@ import pandas as pd
 
 ## 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}
+nuclides_data_path = "data/nndc_nudat_data_export.json"
 
 def nuclidesFilterZNA(nuclides_data, Z_min=None, Z_max=None, Z_oe_idx=0, N_min=None, N_max=None, N_oe_idx=0, A_min=None, A_max=None, A_oe_idx=0):
     filtered = {}
@@ -186,14 +187,59 @@ def nuclideData_dict2dataframe(nuclideData_dict):
     a = nuclideData_dict["a"]
     data = []
     for level in nuclideData_dict["levels"]:
-        if level["halflife"]["value"] == "STABLE":
-            data.append((nom, z, n, a, level["energy"]["value"], level["energy"]["unit"], level["spinParity"], level["massExcess"]["value"], level["massExcess"]["unit"], level["massExcess"]["uncertainty"], None, None, None, None, None))
+        ## 自旋宇称
+        spinParity = None
+        if "spinParity" in level:
+            spinParity = level["spinParity"]
+
+        ## 质量过剩
+        massExcess = None
+        massExcess_unit = None
+        massExcess_unc =  None
+        if not "massExcess" in level:
+            pass
+        else:
+            massExcess = level["massExcess"]["unit"]
+            massExcess_unit = level["massExcess"]["value"]
+            massExcess_unc = level["massExcess"]["uncertainty"]
+
+        ## 半衰期
+        hl = None
+        hl_unit = None
+        hl_unc =  None
+        if not "halflife" in level:
+            pass
+        elif level["halflife"]["value"] == "STABLE":
+            pass
         else:
             hl = level["halflife"]["value"]
             hl_unit = level["halflife"]["unit"]
-            hl_unc = level["halflife"]["uncertainty"]["value"]
+            if level["halflife"]["uncertainty"]["type"] == "asymmetric":
+                hl_unc = "+" + str(level["halflife"]["uncertainty"]["upperLimit"]) + " -" + str(level["halflife"]["uncertainty"]["lowerLimit"])
+            elif level["halflife"]["uncertainty"]["type"] == "approximation":
+                hl_unc = "≈"
+            elif level["halflife"]["uncertainty"]["type"] == "limit":
+                if level["halflife"]["uncertainty"]["limitType"] == "lower":
+                    if level["halflife"]["uncertainty"]["isInclusive"] == True:
+                        hl_unc = "≥"
+                    else:
+                        hl_unc = ">"
+                elif level["halflife"]["uncertainty"]["limitType"] == "upper":
+                    if level["halflife"]["uncertainty"]["isInclusive"] == True:
+                        hl_unc = "≤"
+                    else:
+                        hl_unc = "<"
+            else:
+                hl_unc = level["halflife"]["uncertainty"]["value"]
+
+        ## 衰变模式
+        if not "decayModes" in level:
+            data.append((nom, z, n, a, level["energy"]["value"], level["energy"]["unit"], spinParity, massExcess, massExcess_unit, massExcess_unc, hl, hl_unit, hl_unc, None, None))
+        elif len(level["decayModes"]["observed"]) == 0:
+            data.append((nom, z, n, a, level["energy"]["value"], level["energy"]["unit"], spinParity, massExcess, massExcess_unit, massExcess_unc, hl, hl_unit, hl_unc, None, None))
+        else:
             for decayMode in level["decayModes"]["observed"]:
-                data.append((nom, z, n, a, level["energy"]["value"], level["energy"]["unit"], level["spinParity"], level["massExcess"]["value"], level["massExcess"]["unit"], level["massExcess"]["uncertainty"], hl, hl_unit, hl_unc, decayMode["mode"], decayMode["value"]))
+                data.append((nom, z, n, a, level["energy"]["value"], level["energy"]["unit"], spinParity, massExcess, massExcess_unit, massExcess_unc, hl, hl_unit, hl_unc, decayMode["mode"], decayMode["value"]))
 
     nuclideDataframe = pd.DataFrame(data, columns=["Nuclide", "Z", "N", "A", "E(level)", "E(level) unit", "Spin Parity", "Mass Excess", "Mass Excess unit", "Mass Excess uncertainty", "Halflife", "Halflife unit", "Halflife uncertainty", "Decay Mode", "Branch Ratio"])
 
@@ -202,18 +248,143 @@ def nuclideData_dict2dataframe(nuclideData_dict):
 def nuclideData_dict2dataframeCompact(nuclideData_dict):
     data = []
     for level in nuclideData_dict["levels"]:
-        if level["halflife"]["value"] == "STABLE":
-            data.append((str(level["energy"]["value"])+" "+level["energy"]["unit"], level["spinParity"], level["massExcess"]["formats"]["NDS"]+" "+level["massExcess"]["unit"], "STABLE", None))
+        ## 自旋宇称
+        spinParity = None
+        if "spinParity" in level:
+            spinParity = level["spinParity"]
+
+        ## 质量过剩
+        massExcess = None
+        if not "massExcess" in level:
+            pass
+        else:
+            massExcess = level["massExcess"]["formats"]["NDS"]+" "+level["massExcess"]["unit"]
+
+        ## 半衰期
+        hl = None
+        if not "halflife" in level:
+            pass
+        elif level["halflife"]["value"] == "STABLE":
+            hl = "STABLE"
+        else:
+            hl = level["halflife"]["formats"]["NDS"]+" "+level["halflife"]["unit"]
+
+        ## 衰变模式
+        if not "decayModes" in level:
+            data.append((str(level["energy"]["value"])+" "+level["energy"]["unit"], spinParity, massExcess, hl, None))
+        elif len(level["decayModes"]["observed"]) == 0:
+            data.append((str(level["energy"]["value"])+" "+level["energy"]["unit"], spinParity, massExcess, hl, None))
         else:
             decayModes = []
             for decayMode in level["decayModes"]["observed"]:
                 decayModes.append((decayMode["mode"], decayMode["value"]))
             decayModeDF = pd.DataFrame(decayModes, columns=["Decay Mode", "Branch Ratio"])
-            data.append((str(level["energy"]["value"])+" "+level["energy"]["unit"], level["spinParity"], level["massExcess"]["formats"]["NDS"]+" "+level["massExcess"]["unit"], level["halflife"]["formats"]["NDS"]+" "+level["halflife"]["unit"], decayModeDF))
+            data.append((str(level["energy"]["value"])+" "+level["energy"]["unit"], spinParity, massExcess, hl, decayModeDF))
 
     nuclideDataframe = pd.DataFrame(data, columns=["E(level)", "Spin Parity", "Mass Excess", "Halflife", "Decay Modes"])
 
     return nuclideDataframe
 
-###
-#nuclidesFilter(1)
+def nuclidesClassifyHalflife(data_path):
+    with open (data_path,'r', encoding='utf-8') as file:
+        nuclides_data = json.load(file)
+
+    classified = []
+    for nom, data in nuclides_data.items():
+        z = data["z"]
+        n = data["n"]
+        hl_type = "UN"
+
+        if len(data["levels"]) == 0:
+            hl_type = "UN"
+        elif not "halflife" in data["levels"][0]:
+            hl_type = "UN"
+        elif data["levels"][0]["halflife"]["value"] == "STABLE":
+            hl_type = "ST"
+        elif not data["levels"][0]["halflife"]["unit"] in HL_UNITS:
+            hl_type = "SU"
+        else:
+            hl_sec = data["levels"][0]["halflife"]["value"] * HL_UNITS[data["levels"][0]["halflife"]["unit"]]
+            if hl_sec < 1e-7:
+                hl_type = "l100ns"
+            elif hl_sec < 1e-6:
+                hl_type = "100ns"
+            elif hl_sec < 1e-5:
+                hl_type = "1us"
+            elif hl_sec < 1e-4:
+                hl_type = "10us"
+            elif hl_sec < 1e-3:
+                hl_type = "100us"
+            elif hl_sec < 1e-2:
+                hl_type = "1ms"
+            elif hl_sec < 1e-1:
+                hl_type = "10ms"
+            elif hl_sec < 1:
+                hl_type = "100ms"
+            elif hl_sec < 10:
+                hl_type = "1s"
+            elif hl_sec < 100:
+                hl_type = "10s"
+            elif hl_sec < 1e3:
+                hl_type = "100s"
+            elif hl_sec < 1e4:
+                hl_type = "1ks"
+            elif hl_sec < 1e5:
+                hl_type = "10ks"
+            elif hl_sec < 1e7:
+                hl_type = "100ks"
+            elif hl_sec < 1e10:
+                hl_type = "10Ms"
+            elif hl_sec < 1e15:
+                hl_type = "1e10s"
+            else:
+                hl_type = "1e15s"
+        
+        classified.append({"z":z, "n":n, "type":hl_type})
+
+    return classified
+
+def nuclidesClassifyDecayMode(data_path):
+    with open (data_path,'r', encoding='utf-8') as file:
+        nuclides_data = json.load(file)
+
+    classified = []
+    for nom, data in nuclides_data.items():
+        z = data["z"]
+        n = data["n"]
+        dm_type = "UNKNOWN"
+
+        if len(data["levels"]) == 0:
+            dm_type = "UNKNOWN"
+        elif not "decayModes" in data["levels"][0]:
+            dm_type = "UNKNOWN"
+            if "halflife" in data["levels"][0]:
+                if data["levels"][0]["halflife"]["value"] == "STABLE":
+                    dm_type = "STABLE"
+        else:
+            decay_modes = data["levels"][0]["decayModes"]["observed"] + data["levels"][0]["decayModes"]["predicted"]
+            if len(decay_modes) == 0:
+                dm_type = "UNKNOWN"
+            else:
+                ## 据分支比排序
+                dms1 = []
+                dms2 = []
+                dmsd = {}
+                dmsd1 = []
+                for decay_mode in decay_modes:  
+                    if not "value" in decay_mode:
+                        dms2.append(decay_mode)
+                    else:
+                        dmsd[decay_mode["mode"]] = decay_mode
+                        dmsd1.append((decay_mode["value"], decay_mode["mode"]))
+                dmsdf = pd.DataFrame(dmsd1, columns=["value", "mode"])
+                dmsdf.sort_values(by="value", ascending=False, inplace=True)
+                for mode in dmsdf["mode"]:
+                    dms1.append(dmsd[mode])
+                dms = dms1 + dms2
+                dm_type = dms[0]["mode"]
+        classified.append({"z":z, "n":n, "type":dm_type})
+
+    return classified
+
+##test

NDplot.py

@@ -0,0 +1,468 @@
+import copy
+import json
+import math
+import re
+import numpy as np
+import pandas as pd
+import matplotlib.pyplot as plt
+#import matplotlib.colors as mcolors
+from matplotlib.patches import Patch
+
+## the synthesis methods: Mass Spectroscopy, Radioactive Decay, Light Particles, Fission, Fusion, Spallation, Projectile Fragmentation, and Transfer/Deep Inelastic Scattering
+colors_synthesisMethods = {
+    "MS" : (0, 0, 0),
+    "RD" : (0, 255, 255),
+    "LP" : (255, 165, 0),
+    "FI" : (255, 255, 0),
+    "FU" : (255, 0, 0),
+    "SP" : (0, 0, 255),
+    "PF" : (0, 127, 0),
+    "UN" : (127, 0, 127)
+}
+
+names_synthesisMethods = {
+    "MS" : "Mass Spectroscopy",
+    "RD" : "Radioactive Decay",
+    "LP" : "Light Particles",
+    "FI" : "Fission",
+    "FU" : "Fusion",
+    "SP" : "Spallation",
+    "PF" : "Projectile Fragmentation",
+    "UN" : "Transfer/Deep Inelastic"
+}
+
+colors_halflife = {
+    "l100ns": (247, 189, 222),
+    "100ns" : (255, 198, 165),
+    "1us"   : (255, 231, 198),
+    "10us"  : (255, 255, 156),
+    "100us" : (255, 255, 16),
+    "1ms"   : (231, 247, 132),
+    "10ms"  : (214, 239, 57),
+    "100ms" : (173, 222, 99),
+    "1s"    : (82, 181, 82),
+    "10s"   : (99, 189, 181),
+    "100s"  : (99, 198, 222),
+    "1ks"   : (0, 165, 198),
+    "10ks"  : (8, 154, 148),
+    "100ks" : (0, 132, 165),
+    "10Ms"  : (49, 82, 165),
+    "1e10s" : (41, 0, 107),
+    "1e15s" : (0, 0, 0),
+    "ST"    : (0, 0, 0),
+    "SU"    : (255, 148, 115),
+    "UN"    : (224, 224, 224)
+}
+
+legends_halflife = {
+    "l100ns": "<100ns",
+    "100ns" : "100ns ~ 1us",
+    "1us"   : "1us ~ 10us",
+    "10us"  : "10us ~ 100us",
+    "100us" : "100us ~ 1ms",
+    "1ms"   : "1ms ~ 10ms",
+    "10ms"  : "10ms ~ 100ms",
+    "100ms" : "100ms ~ 1s",
+    "1s"    : "1s ~ 10s",
+    "10s"   : "10s ~ 100s",
+    "100s"  : "100s ~ 1ks",
+    "1ks"   : "1ks ~ 10ks",
+    "10ks"  : "10ks ~ 100ks",
+    "100ks" : "100ks ~ 10Ms",
+    "10Ms"  : "10Ms ~ 1e10s",
+    "1e10s" : "1e10s ~ 1e15s",
+    "1e15s" : ">1e15s",
+    "ST"    : "STABLE",
+    "SU"    : "SpecialUnit",
+    "UN"    : "UNKNOWN"
+}
+
+colors_DecayModes = {
+    "P"     : (255, 148, 115),
+    "N"     : (156, 123, 189),
+    "A"     : (255, 255, 66),
+    "B-"    : (231, 140, 198),
+    "EC+B+" : (99, 198, 222),
+    "EC"    : (0, 132, 165),
+    "SF"    : (82, 181, 82),
+    "STABLE": (0, 0, 0),
+    "UNKNOWN":(224, 224, 224)
+}
+
+legends_DecayModes = {
+    "P"     : "Proton",
+    "N"     : "Neutron",
+    "A"     : "Alaph",
+    "B-"    : "Beta-",
+    "EC+B+" : "Beta+ ElectronCapture",
+    "EC"    : "ElectronCapture",
+    "SF"    : "SpontaneousFission",
+    "STABLE": "STABLE",
+    "UNKNOWN":"UNKNOWN"
+}
+
+nuclides_data_path = "data/nndc_nudat_data_export.json"
+data_synthesisMethods_path = "data/Nuclides_synthesisMethods.json"
+ElementsList_path = "data/ElementsList.json"
+data_NuclidesClassifiedHalflife_path = "data/NuclidesClassifiedHalflife.json"
+data_NuclidesClassifiedDecayModes_path = "data/NuclidesClassifiedDecayModes.json"
+
+## 使用matplotlib绘图
+## 入参为核素分类模式、所绘制核素区域、显示信息、有无图例
+## area部分待完善
+def nucildesChartPlotPLT(plot_mode=0, area=((0,0),(118,177)), text_mode=0, have_legend=True):
+    ## 确定绘制核素区域
+    z_min, n_min = area[0]
+    z_max, n_max = area[1]
+    area_ysize = z_max - z_min + 1
+    area_xsize = n_max - n_min + 1
+
+    ## 计算坐标时使用的单位为像素，而matplotlib的方法使用的单位为英寸，执行前须进行单位转换
+    nbwidth = 40
+    nbheight = 40
+    dpi = 100
+
+    ## 根据显示信息确定绘图大小
+    if text_mode == 0:
+        resize_ratio = 5
+        ticks_step = 10
+        fontsize_label = 75
+        fontsize_ticks = 50
+    elif text_mode == 1:
+        resize_ratio = 5
+        ticks_step = 10
+        fontsize_label = 75
+        fontsize_ticks = 50
+    elif text_mode == 2:
+        resize_ratio = 10
+        ticks_step = 10
+        fontsize_label = 150
+        fontsize_ticks = 100
+    elif text_mode == 3:
+        resize_ratio = 10
+        ticks_step = 10
+        fontsize_label = 150
+        fontsize_ticks = 100
+    else:
+        resize_ratio = 1
+        ticks_step = 10
+        fontsize_label = 15
+        fontsize_ticks = 10
+
+    ## 确定绘制范围
+    ## 据质子数、中子数取整十
+    ## 对于默认的(118,177)，绘制范围为(130, 200)
+    x_min = math.floor(n_min / 10) * 10
+    x_max = math.ceil(n_max / 10) * 10
+    y_min = math.floor(z_min / 10) * 10
+    y_max = math.ceil(z_max / 10) * 10
+
+    fig = plt.figure(figsize=(10*resize_ratio*(x_max-x_min)/200, 6*resize_ratio*(y_max-y_min)/130), dpi=dpi)
+    ax = plt.gca()
+
+
+    ## 核素区域绘制，默认白色背景
+    bg_color = (255, 255, 255)
+    color_data = np.full((area_ysize, area_xsize, 3), bg_color)
+
+    dx = nbwidth  * resize_ratio
+    dy = nbheight * resize_ratio
+    xposg = np.arange(0, area_xsize*dx + dx, dx)
+    yposg = np.arange(0, area_ysize*dy + dy, dy)
+
+    xgrid = np.tile(xposg.reshape(1, -1), (area_ysize + 1, 1))
+    ygrid = np.tile(yposg.reshape(-1, 1), (1, area_xsize + 1))
+
+    xgridI = xgrid / dpi
+    ygridI = ygrid / dpi
+
+    ## 根据核素分类模式上色
+    color_data = nucildesChartPlotPLTColor(copy.deepcopy(color_data), plot_mode, z_min, n_min ,z_max, n_max)
+
+    ## 停用imshow转用pcolormesh以便控制各网格大小以及绘制边框
+    #ax.imshow(color_data, origin="lower", extent=[n_min-0.5, n_max+0.5, z_min-0.5, z_max+0.5])
+    ax.pcolormesh(xgridI, ygridI, color_data.astype(np.uint8), edgecolors="white", linewidth=4*resize_ratio/dpi)
+
+
+    ## 绘制坐标轴
+    ax.set_xlim(((x_min-5)*dx/dpi, (x_max+20)*dx/dpi))
+    ax.set_ylim(((y_min-5)*dy/dpi, (y_max+10)*dy/dpi))
+    ax.set_xlabel("Neutron number", fontsize=fontsize_label, font='Times New Roman')
+    ax.set_ylabel("Proton number" , fontsize=fontsize_label, font='Times New Roman')
+
+    ## 刻度绘制，同样取整十 (ticks_step = 10)
+    xticks = np.arange(x_min, x_max + 20 + ticks_step, ticks_step)
+    yticks = np.arange(y_min, y_max + 10 + ticks_step, ticks_step)
+    xtickspos = (xticks * dx + np.ones(len(xticks)) * 0.5 * dx) / dpi
+    ytickspos = (yticks * dy + np.ones(len(yticks)) * 0.5 * dy) / dpi
+    ax.set_xticks(xtickspos, xticks, fontsize=fontsize_ticks)
+    ax.set_yticks(ytickspos, yticks, fontsize=fontsize_ticks)
+
+    ## 图例添加
+    ## 默认大小匹配全图绘制
+    if have_legend:
+        legend_handles = legendHandlesGet(plot_mode)
+        if len(legend_handles) < 13:
+            fontsize_legend = fontsize_ticks
+        else:
+            fontsize_legend = fontsize_ticks * 0.6
+        plt.legend(handles=legend_handles, loc="lower right", fontsize=fontsize_legend)
+
+    ## 添加显示信息
+    if not text_mode == 0:
+        color_weight = np.array((0.299, 0.587, 0.114))
+        text_data = nucildesChartPlotPLTText(plot_mode, z_min, n_min ,z_max, n_max)
+
+        ## 显示元素名称
+        if text_mode == 1:
+            for tdata in text_data:
+                ## 根据方块颜色选择文本颜色(黑或白)
+                base_color = color_data[tdata["pos"][1]][tdata["pos"][0]]
+                if np.dot(color_weight, base_color) > 128:
+                    text_color = "black"
+                else:
+                    text_color = "white"
+
+                txposi = (tdata["pos"][0] + 0.5) * dx / dpi
+                typosi = (tdata["pos"][1] + 0.5) * dy / dpi
+                ax.text(txposi, typosi, tdata["text01"], ha="center", va="center", color=text_color, fontsize=6)
+
+        ## 显示核素名称
+        elif text_mode == 2:
+            for tdata in text_data:
+                ## 根据方块颜色选择文本颜色(黑或白)
+                base_color = color_data[tdata["pos"][1]][tdata["pos"][0]]
+                if np.dot(color_weight, base_color) > 128:
+                    text_color = "black"
+                else:
+                    text_color = "white"
+
+                txposi = (tdata["pos"][0] + 0.5) * dx / dpi
+                typosi = (tdata["pos"][1] + 0.5) * dy / dpi
+                ax.text(txposi, typosi, tdata["text02"], ha="center", va="center", color=text_color, fontsize=6)
+
+        ## 显示详细信息
+        elif text_mode == 3:
+            for tdata in text_data:
+                ## 根据方块颜色选择文本颜色(黑或白)
+                base_color = color_data[tdata["pos"][1]][tdata["pos"][0]]
+                if np.dot(color_weight, base_color) > 128:
+                    text_color = "black"
+                else:
+                    text_color = "white"
+
+                txposi = (tdata["pos"][0] + 0.5) * dx / dpi
+                typosi = (tdata["pos"][1] + 0.85) * dy / dpi
+                text = tdata["text02"] + "\n" + tdata["text03"]
+                ax.text(txposi, typosi, text, ha="center", va="top", ma="center", color=text_color, fontsize=2.4)
+                
+        
+    
+    #fig.savefig("test.svg", format="svg")
+    #fig.savefig("test.png", format="png")
+    #plt.show()
+
+    return fig
+
+def nucildesChartPlotPLTColor(color_data, mode, z_min, n_min ,z_max, n_max):
+    ## 据半衰期上色
+    ## 默认使用基态数据
+    ## nndc上的nudat3绘制时若基态无数据则会使用激发态的数据，此处与其不同 比如：137Pm、154Lu、161Ta 等
+    if mode == 0:
+        ## 自NDfilter.nuclidesClassifyHalflife()
+        with open(data_NuclidesClassifiedHalflife_path, "r", encoding="utf8") as file:
+            data = json.load(file)
+
+        for row in data:
+            if (row["z"] >= z_min and row["z"] <= z_max) and (row["n"] >= n_min and row["n"] <= n_max):
+                ypos = row["z"] - z_min
+                xpos = row["n"] - n_min
+                if row["type"] in colors_halflife:
+                    color_data[ypos][xpos] = np.array(colors_halflife[row["type"]])
+
+    ## 据衰变模式上色
+    elif mode == 1:
+        ## 自NDfilter.nuclidesClassifyDecayMode()
+        with open(data_NuclidesClassifiedDecayModes_path, "r", encoding="utf8") as file:
+            data = json.load(file)
+
+        for row in data:
+            if (row["z"] >= z_min and row["z"] <= z_max) and (row["n"] >= n_min and row["n"] <= n_max):
+                ypos = row["z"] - z_min
+                xpos = row["n"] - n_min
+                if row["type"] in colors_DecayModes:
+                    color_data[ypos][xpos] = np.array(colors_DecayModes[row["type"]])
+                elif row["type"] in ("2B-", "β⁻"):
+                    color_data[ypos][xpos] = np.array(colors_DecayModes["B-"])
+                elif row["type"] in ("2P", "3P"):
+                    color_data[ypos][xpos] = np.array(colors_DecayModes["P"])
+                elif row["type"] in ("2N"):
+                    color_data[ypos][xpos] = np.array(colors_DecayModes["N"])
+                else:
+                    color_data[ypos][xpos] = np.array(colors_DecayModes["UNKNOWN"])
+
+    ## 据合成方法上色
+    elif mode == 2:
+        with open(data_synthesisMethods_path, "r", encoding="utf8") as file:
+            data = json.load(file)
+
+        for row in data:
+            if (row["z"] >= z_min and row["z"] <= z_max) and (row["n"] >= n_min and row["n"] <= n_max):
+                ypos = row["z"] - z_min
+                xpos = row["n"] - n_min
+                if row["type"] in colors_synthesisMethods:
+                    color_data[ypos][xpos] = np.array(colors_synthesisMethods[row["type"]])
+
+    return color_data
+
+def legendHandlesGet(plot_mode):
+    handles = []
+    if plot_mode == 0:
+        for hl_tag in colors_halflife:
+            if hl_tag == "ST":
+                pass
+            elif hl_tag == "1e15s":
+                handles.append(Patch(facecolor=np.array(colors_halflife[hl_tag])/255., label=">1e15s or Stable"))
+            else:
+                handles.append(Patch(facecolor=np.array(colors_halflife[hl_tag])/255., label=legends_halflife[hl_tag]))
+
+    elif plot_mode == 1:
+        for decay_mode in colors_DecayModes:
+            handles.append(Patch(facecolor=np.array(colors_DecayModes[decay_mode])/255., label=legends_DecayModes[decay_mode]))
+
+    elif plot_mode == 2:
+        for synthesis_method in colors_synthesisMethods:
+            handles.append(Patch(facecolor=np.array(colors_synthesisMethods[synthesis_method])/255., label=names_synthesisMethods[synthesis_method]))
+
+    return handles
+
+def nucildesChartPlotPLTText(plot_mode, z_min, n_min ,z_max, n_max):
+    with open(ElementsList_path, "r", encoding="utf8") as file:
+        elements_list = json.load(file)
+
+    text_data = []
+    if plot_mode == 0 or plot_mode == 1:
+        with open(nuclides_data_path, "r", encoding="utf8") as file:
+            data = json.load(file)
+
+        ## 填充半衰期及衰变模式信息
+        ## 对于衰变模式多于三种的，只显示其前三种(仿nndc)
+        ## 对于过长的数字，将会对其进行截断
+        for nom, ndata in data.items():
+            if (ndata["z"] >= z_min and ndata["z"] <= z_max) and (ndata["n"] >= n_min and ndata["n"] <= n_max):
+                ypos = ndata["z"] - z_min
+                xpos = ndata["n"] - n_min
+                text01 = elements_list[str(ndata["z"])]
+                text02 = str(ndata["z"]+ndata["n"]) + text01
+
+                hlt = ""
+                dmst = []
+                if len(ndata["levels"]) == 0:
+                    hlt = ""
+                    dmst = []
+                else:
+                    if not "halflife" in ndata["levels"][0]:
+                        hlt = ""
+                    elif not "value" in ndata["levels"][0]["halflife"]:
+                        hlt = ""
+                    elif ndata["levels"][0]["halflife"]["value"] == "STABLE":
+                        hlt = "STABLE"
+                    else:
+                        hlv = ndata["levels"][0]["halflife"]["value"]
+                        if hlv > 1e4:
+                            hlt = f"{hlv:.2e}"
+                        else:
+                            hlt = str(hlv)
+
+                        if ndata["levels"][0]["halflife"]["unit"] == "m":
+                            hlt = hlt + " min"
+                        else:
+                            hlt = hlt + " " + ndata["levels"][0]["halflife"]["unit"]
+
+                    if not "decayModes" in ndata["levels"][0]:
+                        dmst = []
+                    else:
+                        decay_modes = ndata["levels"][0]["decayModes"]["observed"] + ndata["levels"][0]["decayModes"]["predicted"]
+                        if len(decay_modes) == 0:
+                            dmst = []
+                        else:
+                            ## 据分支比排序
+                            dms1 = []
+                            dms2 = []
+                            dmsd = {}
+                            dmsd1 = []
+                            for decay_mode in decay_modes:  
+                                if not "value" in decay_mode:
+                                    dms2.append(decay_mode)
+                                else:
+                                    dmsd[decay_mode["mode"]] = decay_mode
+                                    dmsd1.append((decay_mode["value"], decay_mode["mode"]))
+                            dmsdf = pd.DataFrame(dmsd1, columns=["value", "mode"])
+                            dmsdf.sort_values(by="value", ascending=False, inplace=True)
+                            for mode in dmsdf["mode"]:
+                                dms1.append(dmsd[mode])
+                            dms = dms1 + dms2
+                            ###
+                            for decay_mode in dms:
+                                text = decay_mode["mode"]
+                                if not "value" in decay_mode:
+                                    text = text + " ?"
+                                else:
+                                    dmv = decay_mode["value"]
+                                    dmt = str(dmv)
+                                    if len(dmt) > 7:
+                                        if re.search(rf"([eE])", dmt) == None:
+                                            if dmv > 1e-3:
+                                                dmt = dmt[:7]
+                                            else:
+                                                match00 = re.fullmatch(rf"(0+)(\.)(0+)([1-9]+)", dmt)
+                                                if not match00 == None:
+                                                    ne = match00.group(4)
+                                                    if len(ne) < 3:
+                                                        dmt = f"{dmv:e}"
+                                                    else:
+                                                        dmt = f"{dmv:.2e}"
+                                    if decay_mode["uncertainty"]["type"] == "limit":
+                                        if decay_mode["uncertainty"]["limitType"] == "lower":
+                                            if decay_mode["uncertainty"]["isInclusive"] == True:
+                                                text = text + " ≥ " + dmt + "%"
+                                            else:
+                                                text = text + " > " + dmt + "%"
+                                        elif decay_mode["uncertainty"]["limitType"] == "upper":
+                                            if decay_mode["uncertainty"]["isInclusive"] == True:
+                                                text = text + " ≤ " + dmt + "%"
+                                            else:
+                                                text = text + " < " + dmt + "%"
+                                    else:
+                                        text = text + " = " + dmt + "%"
+                                dmst.append(text)
+                text03 = hlt + "\n"
+                if not len(dmst) > 0:
+                    pass
+                elif len(dmst) <= 3:
+                    for dmt in dmst:
+                        text03 = text03 + "\n" + dmt
+                else:
+                    for idx in range(0, 3):
+                        text03 = text03 + "\n" + dmst[idx]
+                
+                text_data.append({"pos":(xpos, ypos), "text01":text01, "text02":text02, "text03":text03})
+
+    ## 填充合成方法信息
+    elif plot_mode == 2:       
+        with open(data_synthesisMethods_path, "r", encoding="utf8") as file:
+            data = json.load(file)
+
+        for row in data:
+            if (row["z"] >= z_min and row["z"] <= z_max) and (row["n"] >= n_min and row["n"] <= n_max):
+                ypos = row["z"] - z_min
+                xpos = row["n"] - n_min
+                text01 = elements_list[str(row["z"])]
+                text02 = str(row["z"]+row["n"]) + text01
+                text03 = row["type"]
+                text_data.append({"pos":(xpos, ypos), "text01":text01, "text02":text02, "text03":text03})
+                
+    return text_data
+
+
+## test

app.py

@@ -1,256 +1,349 @@
-import gradio as gr
-import pandas as pd
-import json
-from tempfile import NamedTemporaryFile
-
-import NDfilter
-
-## 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}" + "\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
-
-    return result_text, result_dataframe, 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_inputs(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)]
-        
-
-
-## 导入数据集
-file_path = "data/nndc_nudat_data_export.json"
-with open (file_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。
-                """)
-    
-    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()
-
-        searchingMode.change(
-            fn=update_inputs,
-            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
-                    TO DO
-                    """)
-
-
-
-
+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()

data/ElementsList.json

@@ -0,0 +1 @@
+{"0": "n", "1": "H", "2": "He", "3": "Li", "4": "Be", "5": "B", "6": "C", "7": "N", "8": "O", "9": "F", "10": "Ne", "11": "Na", "12": "Mg", "13": "Al", "14": "Si", "15": "P", "16": "S", "17": "Cl", "18": "Ar", "19": "K", "20": "Ca", "21": "Sc", "22": "Ti", "23": "V", "24": "Cr", "25": "Mn", "26": "Fe", "27": "Co", "28": "Ni", "29": "Cu", "30": "Zn", "31": "Ga", "32": "Ge", "33": "As", "34": "Se", "35": "Br", "36": "Kr", "37": "Rb", "38": "Sr", "39": "Y", "40": "Zr", "41": "Nb", "42": "Mo", "43": "Tc", "44": "Ru", "45": "Rh", "46": "Pd", "47": "Ag", "48": "Cd", "49": "In", "50": "Sn", "51": "Sb", "52": "Te", "53": "I", "54": "Xe", "55": "Cs", "56": "Ba", "57": "La", "58": "Ce", "59": "Pr", "60": "Nd", "61": "Pm", "62": "Sm", "63": "Eu", "64": "Gd", "65": "Tb", "66": "Dy", "67": "Ho", "68": "Er", "69": "Tm", "70": "Yb", "71": "Lu", "72": "Hf", "73": "Ta", "74": "W", "75": "Re", "76": "Os", "77": "Ir", "78": "Pt", "79": "Au", "80": "Hg", "81": "Tl", "82": "Pb", "83": "Bi", "84": "Po", "85": "At", "86": "Rn", "87": "Fr", "88": "Ra", "89": "Ac", "90": "Th", "91": "Pa", "92": "U", "93": "Np", "94": "Pu", "95": "Am", "96": "Cm", "97": "Bk", "98": "Cf", "99": "Es", "100": "Fm", "101": "Md", "102": "No", "103": "Lr", "104": "Rf", "105": "Db", "106": "Sg", "107": "Bh", "108": "Hs", "109": "Mt", "110": "Ds", "111": "Rg", "112": "Cn", "113": "Nh", "114": "Fl", "115": "Mc", "116": "Lv", "117": "Ts", "118": "Og"}