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