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This commit is contained in:
@@ -0,0 +1,7 @@
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The directory contains input files for a simple H-He model
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of an O-star at Teff=35,000 K, log g = 4.
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The model is computed in three staps:
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- hhe35lt - LTE model, computed from scratch,
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- hhe35nc - NLTE model with continua only,
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- hhe35nl - NLTE model with lines.
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@@ -0,0 +1,4 @@
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$TLUSTY/RTlusty hhe35lt
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$TLUSTY/RTlusty hhe35nc hhe35lt
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$TLUSTY/RTlusty hhe35nl hhe35nc
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File diff suppressed because one or more lines are too long
@@ -0,0 +1,33 @@
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35000. 4.0 ! TEFF, GRAV
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T T ! LTE, LTGRAY
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'' ! no change of general optional parameters
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*-----------------------------------------------------------------
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* frequencies
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50 ! NFREAD
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*-----------------------------------------------------------------
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* data for atoms
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*
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8 ! NATOMS
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* mode abn modpf
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2 0 0
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2 0 0
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0 0 0
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0 0 0
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0 0 0
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1 0 0
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1 0 0
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1 0 0
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*-----------------------------------------------------------------
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* data for ions
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*
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*iat iz nlevs ilast ilvlin nonstd typion filei
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*
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1 0 9 0 100 0 ' H 1' './data/h1.dat'
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1 1 1 1 0 0 ' H 2' ' '
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2 0 14 0 100 0 'He 1' './data/he1.dat'
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2 1 14 0 100 0 'He 2' './data/he2.dat'
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2 2 1 1 0 0 'He 3' ' '
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0 0 0 -1 0 0 ' ' ' '
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*
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* end
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@@ -0,0 +1,33 @@
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35000. 4.0 ! TEFF, GRAV
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F F ! LTE, LTGRAY
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'' ! no change of general optional parameters
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*-----------------------------------------------------------------
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* frequencies
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50 ! NFREAD
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*-----------------------------------------------------------------
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* data for atoms
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*
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8 ! NATOMS
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* mode abn modpf
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2 0 0
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2 0 0
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0 0 0
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0 0 0
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0 0 0
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1 0 0
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1 0 0
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1 0 0
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*-----------------------------------------------------------------
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* data for ions
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*
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*iat iz nlevs ilast ilvlin nonstd typion filei
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*
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1 0 9 0 100 0 ' H 1' './data/h1.dat'
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1 1 1 1 0 0 ' H 2' ' '
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2 0 14 0 100 0 'He 1' './data/he1.dat'
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2 1 14 0 100 0 'He 2' './data/he2.dat'
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2 2 1 1 0 0 'He 3' ' '
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0 0 0 -1 0 0 ' ' ' '
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*
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* end
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@@ -0,0 +1,33 @@
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35000. 4.0 ! TEFF, GRAV
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F F ! LTE, LTGRAY
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'' ! no change of general optional parameters
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*-----------------------------------------------------------------
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* frequencies
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50 ! NFREAD
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*-----------------------------------------------------------------
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* data for atoms
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*
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8 ! NATOMS
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* mode abn modpf
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2 0 0
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2 0 0
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0 0 0
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0 0 0
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0 0 0
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1 0 0
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1 0 0
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1 0 0
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*-----------------------------------------------------------------
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* data for ions
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*
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*iat iz nlevs ilast ilvlin nonstd typion filei
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*
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1 0 9 0 0 0 ' H 1' './data/h1.dat'
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1 1 1 1 0 0 ' H 2' ' '
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2 0 14 0 0 0 'He 1' './data/he1.dat'
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2 1 14 0 0 0 'He 2' './data/he2.dat'
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2 2 1 1 0 0 'He 3' ' '
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0 0 0 -1 0 0 ' ' ' '
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*
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* end
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@@ -0,0 +1,642 @@
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"""Utility programs for examining output from Tlusty
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At the moment, it contains the following routines:
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1) pconv - for ploting the convergence log contasined in the output
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file from Tlusty (fort.9);
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2) pmodel - extracting values of column mass and a selected state parameter
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from the Tlusty output file fort.7m (coindensed model) or fort.12
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(b-factors for NLTE models);
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3) pmodels - similar to pmodel, but with an option to plot selected state
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parameter for one or more Tlusty models, and a possibility of
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plotting differences of between individual models
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4) pmods - a plot of a range pf state parameters for one or more Tlusty models
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Examples:
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--------
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To plot a convergence log of the last computed model:
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>>> import matplotlib.pyplot as plt
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>>> import tlusty as tl
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>>> plt.ion()
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>>> tl.pconv()
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a convergence log for a previously computed model, say, hhe35lt:
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>>> tl.pconv('hhe35lt')
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To extract log(column mass) and temperature of the same model
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>>> (m35,t35) = tl.pmodel('hhe35lt')
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which can then be plotted or used for some other purpose.
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To plot the temperature as a function of log(m) for the last computed
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model, do
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>>> tl.pmodels()
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and to plot the temperature for three models, hhe35lt','hhe35nc, and
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hhe35nl, and then differences from the first model, do
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>>> tl.pmodels(['hhe35lt','hhe35nc','hhe35nl'])
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>>> tl.pmodels(['hhe35lt','hhe35nc','hhe35nl'],diff=True)
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To plot level populations for the first five levels of hydrogen for the
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model hhe35nl, do
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>>> tl.pmods('hhe35nl',[3,4,5,6,7])
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"""
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# Tlusty输出分析工具程序
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# 当前包含以下功能:
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# 1) pconv - 绘制Tlusty输出文件(fort.9)的收敛日志
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# 2) pmodel - 从Tlusty输出文件(fort.7m或fort.12)提取列质量及指定状态参数
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# 3) pmodels - 类似pmodel,支持多模型对比及差异分析
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# 4) pmods - 绘制多个Tlusty模型的多状态参数
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# 5) pflux - 绘制辐射通量或通量差异
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import matplotlib.pyplot as plt # 导入绘图库
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import numpy as np # 导入数值计算库
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import sys # 系统相关功能
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###################################################
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def pconv(relcfile='fort'):
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""""
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绘制Tlusty输出文件(单位9)的收敛日志
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类似旧IDL程序PCONV.PRO,生成2x3子图:
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第一行显示温度(或电离态)的相对变化
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第二行显示所有状态参数的最大相对变化
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左列显示各深度的相对变化值
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中列显示相对变化的对数
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右列显示每迭代步的最大变化值
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右侧子图最能反映整体收敛情况
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标题会显示运行时间(若存在fort.69文件)
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参数:
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relcfile: str, 可选 - 模型核心文件名(自动添加.9后缀)
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默认值:'fort'(对应fort.9)
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返回:无
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"""
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relcfile = relcfile+'.9'
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try:
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f = open(relcfile)
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lines = f.readlines()
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except:
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print('Error: Could not open %s' % relcfile)
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return()
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idep,itnu,delt,delp,delm = [],[],[],[],[]
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i = 3
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while i < len(lines):
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xlin = lines[i]
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xlin = xlin.replace('D','E',5)
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xlin = xlin.strip()
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val = xlin.split()
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itnu.append(float(val[0]))
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idep.append(float(val[1]))
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delt.append(float(val[2]))
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delp.append(float(val[4]))
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delm.append(float(val[6]))
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i += 1
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niter = int(itnu[-1])
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nd = int(idep[0])
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xtit1 = 'depth index'
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xtit2 = 'iteration'
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ytit1 = 'rel.change'
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ytit2 = 'log(rel.change)'
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ftit1 = 'temperature'
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ftit2 = 'max.population'
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ftit3 = 'max in state vector'
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if max(delt) == 0:
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delt=delp
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ftit1 = ftit2
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print(delt[0],delt[-1])
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fig, axes = plt.subplots(2,3)
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axes[0, 0].set_xlabel(xtit1)
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axes[0, 0].set_ylabel(ytit1)
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axes[0, 0].set_title(ftit1)
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axes[0, 1].set_xlabel(xtit1)
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axes[0, 1].set_ylabel(ytit2)
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# axes[0, 1].set_title(ftit1)
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axes[1, 0].set_xlabel(xtit1)
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axes[1, 0].set_ylabel(ytit1)
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axes[1, 0].set_title(ftit3)
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axes[1, 1].set_xlabel(xtit1)
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axes[1, 1].set_ylabel(ytit2)
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axes[1, 1].set_title(ftit3)
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i=0
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tmaxt, tmaxm, tmaxi = [], [], []
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while i < niter:
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i0, i1 = i*nd, (i+1)*nd-1
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axes[0, 0].plot(idep[i0:i1],delt[i0:i1])
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axes[0, 1].plot(idep[i0:i1],np.log10(np.abs(delt[i0:i1])))
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axes[1, 0].plot(idep[i0:i1],delm[i0:i1])
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axes[1, 1].plot(idep[i0:i1],np.log10(np.abs(delm[i0:i1])))
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tmaxt.append(max(np.log10(np.abs(delt[i0:i1]))))
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tmaxm.append(max(np.log10(np.abs(delm[i0:i1]))))
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i+=1
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tmaxi.append(i)
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axes[0, 2].set_xlabel(xtit2)
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axes[0, 2].set_ylabel('max(rel.changei)')
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axes[0, 2].set_title(ftit1)
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# axes[0, 2].plot(tmaxi,tmaxt,'ko',ls=':',ms=10)
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axes[0, 2].plot(tmaxi,tmaxt,'ko',ls='--')
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axes[1, 2].set_xlabel(xtit2)
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axes[1, 2].set_ylabel('max(rel.change')
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axes[1, 2].set_title(ftit3)
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# axes[1, 2].plot(tmaxi,tmaxm,'ko',ls=':',ms=10)
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axes[1, 2].plot(tmaxi,tmaxm,'ko',ls='--')
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# overall title
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# contains the cores name of the model, and also shows the total
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# execution time used by Tlusty to generate the model form file
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# [core name].69 (if it exists)
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timfile = relcfile[0:-2]+'.69'
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try:
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ft = open(timfile)
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linti = ft.readlines()
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titlt = 'time = '+ linti[-1].split()[2] +' s'
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except:
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print('Error: Could not open %s' % relcfile)
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titlt=' '
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titl=relcfile + ': ' + titlt
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fig.suptitle(titl)
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fig.tight_layout()
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plt.show()
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# Next lines permit one to run the routine from the command line
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#if __name__ == "__main__":
|
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# import sys
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# if len(sys.argv)==4:
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# doit(sys.argv[1],sys.argv[2],sys.argv[3])
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# else:
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# print (__doc__)
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# return()
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####################################################
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def pmodel(modfile='fort', ind=0):
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"""
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从Tlusty的压缩模型大气文件(单元7)中提取列质量和一个状态参数,也可从类似输出文件(单元12)提取b因子。
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功能类似旧IDL程序PMODEL.PRO(或MODELS11.PRO)。
|
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|
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参数:
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-----------
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modfile: str, 可选
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模型大气文件的核心名称。若名称不含小数点".",则自动添加".7"
|
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默认值:'fort',即文件名默认为'fort.7'
|
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ind: int, 可选 - 状态参数的索引
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默认0,即温度
|
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状态参数索引说明:
|
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0 - 温度(K)
|
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1 - 电子密度(cm⁻³)
|
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2 - 质量密度(g/cm³)
|
||||
3 - 总粒子数密度(仅含分子模型)
|
||||
后续索引 - 能级布居数
|
||||
|
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返回:
|
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-----------
|
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dm: array
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列质量的对数(log10)
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par: array
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所选状态参数的值(温度为原始值,其他为对数)
|
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"""
|
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# 判断文件名格式并补充后缀
|
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if modfile.count('.') == 0:
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modfile += '.7' # 补充默认后缀".7"
|
||||
|
||||
# 尝试打开文件
|
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try:
|
||||
f = open(modfile)
|
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lines = f.readlines() # 读取所有行
|
||||
except:
|
||||
print(f'错误:无法打开 {modfile}') # 异常处理
|
||||
return ()
|
||||
|
||||
# 读取输入参数的深度数量和参数数量
|
||||
x = lines[0] # 第一行数据
|
||||
nd = int(x.split()[0]) # 总深度层数
|
||||
npa = abs(int(x.split()[1])) # 状态参数数量
|
||||
|
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# 设置每行读取的深度数量(根据文件类型)
|
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ndrow = 6
|
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if modfile.count('.12') > 0:
|
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ndrow = 8 # 若为b因子文件则调整
|
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|
||||
# 计算需要读取的行数
|
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nr = nd // ndrow
|
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if nd % ndrow != 0:
|
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nr += 1 # 处理余数
|
||||
|
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# 读取深度数据
|
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dm = [] # 初始化列质量列表
|
||||
i = 0
|
||||
while i < nr:
|
||||
x = lines[i+1] # 从第二行开始读取深度数据
|
||||
x = x.replace('D','E',6) # 替换指数符号
|
||||
val = x.split() # 分割数值
|
||||
j = 0
|
||||
while j < ndrow:
|
||||
k = ndrow * i + j
|
||||
if k < nd:
|
||||
dm.append(float(val[j])) # 存储深度值
|
||||
j += 1
|
||||
i += 1
|
||||
|
||||
# 读取状态参数数据
|
||||
nrx = npa // 5 # 每行参数数量
|
||||
if npa % 5 != 0:
|
||||
nrx += 1 # 处理余数
|
||||
|
||||
par = [] # 初始化状态参数列表
|
||||
i = nr + 1 # 从深度数据后开始读取参数
|
||||
id = 0
|
||||
while id < nd:
|
||||
xpar = [] # 临时参数列表
|
||||
j = 0
|
||||
while j < nrx:
|
||||
x = lines[i] # 读取当前行
|
||||
x = x.replace('D','E',6) # 替换指数符号
|
||||
val = x.split() # 分割数值
|
||||
k = 0
|
||||
while k < 5:
|
||||
if 5*j + k < npa:
|
||||
xpar.append(float(val[k])) # 存储参数值
|
||||
k += 1
|
||||
j += 1
|
||||
i += 1
|
||||
par.append(xpar[ind]) # 保存指定索引的参数值
|
||||
id += 1
|
||||
|
||||
# 数据处理与绘图
|
||||
dm = np.log10(dm) # 转换为列质量对数
|
||||
par = np.array(par) # 转换为数组
|
||||
if ind > 0:
|
||||
par = np.log10(par) # 非温度参数取对数
|
||||
|
||||
# 创建绘图
|
||||
fig, ax = plt.subplots()
|
||||
ax.set_xlabel('log mass') # X轴标签
|
||||
ax.set_title(modfile) # 标题
|
||||
|
||||
# 根据参数类型设置Y轴标签和绘图
|
||||
if ind == 0:
|
||||
ax.set_ylabel('temperature') # 温度标签
|
||||
ax.plot(dm, par) # 绘制温度曲线
|
||||
else:
|
||||
ax.set_ylabel('log n') # 密度/布居数标签
|
||||
ax.plot(dm, np.log10(par)) # 绘制对数曲线
|
||||
plt.show() # 显示图形
|
||||
# return (dm, par) # 返回数据数组
|
||||
|
||||
####################################################
|
||||
|
||||
|
||||
def pmodels(modfiles=['fort'], ind=0, diff=False):
|
||||
"""
|
||||
类似pmodel函数,但支持多模型对比和差异分析
|
||||
可绘制一个或多个Tlusty模型的某个状态参数,并可显示与首个模型的差异
|
||||
参数:
|
||||
-----------
|
||||
modfiles: list of str, 可选
|
||||
模型文件的核心名称列表。若名称不含小数点".",则自动添加".7"
|
||||
默认值:['fort'](对应fort.7)
|
||||
ind: int, 可选 - 状态参数的索引
|
||||
默认0(温度)
|
||||
diff: bool, 可选
|
||||
若为True,绘制指定状态参数与首个模型的差异
|
||||
默认False(绘制实际参数值)
|
||||
状态参数索引说明:
|
||||
0 - 温度(K)
|
||||
1 - 电子密度(cm⁻³)
|
||||
2 - 质量密度(g/cm³)
|
||||
3 - 总粒子数密度(仅含分子模型)
|
||||
后续索引 - 能级布居数
|
||||
返回:
|
||||
-----------
|
||||
无(直接绘图)
|
||||
"""
|
||||
imod = 0 # 初始化模型计数器
|
||||
for modfile in modfiles: # 遍历所有模型文件
|
||||
if modfile.count('.') == 0: # 自动补充后缀".7"
|
||||
modfile += '.7'
|
||||
|
||||
# 尝试打开文件
|
||||
try:
|
||||
f = open(modfile)
|
||||
lines = f.readlines()
|
||||
except:
|
||||
print(f'错误:无法打开 {modfile}')
|
||||
return()
|
||||
|
||||
# 读取输入参数的深度数量和参数数量
|
||||
x = lines[0] # 第一行数据
|
||||
nd = int(x.split()[0]) # 总深度层数
|
||||
npa = abs(int(x.split()[1])) # 状态参数数量
|
||||
|
||||
# 设置每行读取的深度数量(根据文件类型)
|
||||
ndrow = 6
|
||||
if modfile.count('.12') > 0:
|
||||
ndrow = 8 # 若为b因子文件则调整
|
||||
|
||||
# 计算需要读取的行数
|
||||
nr = nd // ndrow
|
||||
if nd % ndrow != 0:
|
||||
nr += 1 # 处理余数
|
||||
|
||||
# 读取深度数据
|
||||
dm = [] # 初始化列质量列表
|
||||
i = 0
|
||||
while i < nr:
|
||||
x = lines[i+1] # 从第二行开始读取深度数据
|
||||
x = x.replace('D','E',6) # 替换指数符号
|
||||
val = x.split() # 分割数值
|
||||
j = 0
|
||||
while j < ndrow:
|
||||
k = ndrow * i + j
|
||||
if k < nd:
|
||||
dm.append(float(val[j])) # 存储深度值
|
||||
j += 1
|
||||
i += 1
|
||||
|
||||
# 读取状态参数数据
|
||||
nrx = npa // 5 # 每行参数数量
|
||||
if npa % 5 != 0:
|
||||
nrx += 1 # 处理余数
|
||||
|
||||
par = [] # 初始化状态参数列表
|
||||
i = nr + 1 # 从深度数据后开始读取参数
|
||||
id = 0
|
||||
while id < nd:
|
||||
xpar = [] # 临时参数列表
|
||||
j = 0
|
||||
while j < nrx:
|
||||
x = lines[i] # 读取当前行
|
||||
x = x.replace('D','E',6) # 替换指数符号
|
||||
val = x.split() # 分割数值
|
||||
k = 0
|
||||
while k < 5:
|
||||
if 5*j + k < npa:
|
||||
xpar.append(float(val[k])) # 存储参数值
|
||||
k += 1
|
||||
j += 1
|
||||
i += 1
|
||||
par.append(xpar[ind]) # 保存指定索引的参数值
|
||||
id += 1
|
||||
|
||||
# 数据处理与绘图
|
||||
dm = np.log10(dm) # 转换为列质量对数
|
||||
if ind != 0:
|
||||
par = np.log10(par) # 非温度参数取对数
|
||||
|
||||
# 初始化绘图(首个模型)
|
||||
if imod == 0:
|
||||
fig, ax = plt.subplots() # 创建图形
|
||||
ax.set_xlabel('log mass') # X轴标签
|
||||
titl = modfile[:-2] # 标题初始化
|
||||
dm0 = dm.copy() # 存储首个模型的深度数据
|
||||
par0 = par.copy() # 存储首个模型的参数值
|
||||
|
||||
if diff: # 差异模式
|
||||
par = np.array(par) - np.array(par0) # 计算差异
|
||||
else: # 后续模型
|
||||
titl += f', {modfile[:-2]}' # 更新标题
|
||||
|
||||
if diff: # 差异模式处理
|
||||
# 线性插值到首个模型的深度网格
|
||||
pari = np.interp(dm0, dm, par)
|
||||
par = pari - par0 # 计算与首个模型的差异
|
||||
|
||||
# 设置Y轴标签
|
||||
if ind == 0:
|
||||
ax.set_ylabel('temperature') # 温度标签
|
||||
else:
|
||||
ax.set_ylabel('log n') # 密度/布居数标签
|
||||
|
||||
# 绘制数据
|
||||
if not diff:
|
||||
ax.plot(dm, par) # 绘制实际参数曲线
|
||||
else:
|
||||
ax.plot(dm0, par) # 绘制差异曲线
|
||||
|
||||
imod += 1 # 增加模型计数器
|
||||
|
||||
ax.set_title(titl) # 设置最终标题
|
||||
plt.show() # 显示图形
|
||||
|
||||
#####################################################################
|
||||
|
||||
|
||||
def pmods(modfiles, ind):
|
||||
"""
|
||||
类似pmodels函数,但支持同时绘制多个状态参数
|
||||
可绘制一个或多个Tlusty模型的多个状态参数曲线
|
||||
参数:
|
||||
-----------
|
||||
modfiles: list of str
|
||||
模型文件的核心名称列表。若名称不含小数点".",则自动添加".7"
|
||||
ind: list of int
|
||||
需要绘制的状态参数索引列表
|
||||
状态参数索引说明:
|
||||
0 - 温度(K)
|
||||
1 - 电子密度(cm⁻³)
|
||||
2 - 质量密度(g/cm³)
|
||||
3 - 总粒子数密度(仅含分子模型)
|
||||
后续索引 - 能级布居数
|
||||
返回:
|
||||
-----------
|
||||
无(直接绘图)
|
||||
"""
|
||||
imod = 0 # 初始化模型计数器
|
||||
for modfile in modfiles: # 遍历所有模型文件
|
||||
if modfile.count('.') == 0: # 自动补充后缀".7"
|
||||
modfile += '.7'
|
||||
|
||||
# 尝试打开文件
|
||||
try:
|
||||
f = open(modfile)
|
||||
lines = f.readlines()
|
||||
except:
|
||||
print(f'错误:无法打开 {modfile}')
|
||||
return()
|
||||
|
||||
# 读取输入参数的深度数量和参数数量
|
||||
x = lines[0] # 第一行数据
|
||||
nd = int(x.split()[0]) # 总深度层数
|
||||
npa = abs(int(x.split()[1])) # 状态参数数量
|
||||
|
||||
# 设置每行读取的深度数量(根据文件类型)
|
||||
ndrow = 6
|
||||
if modfile.count('.12') > 0:
|
||||
ndrow = 8 # 若为b因子文件则调整
|
||||
|
||||
# 计算需要读取的行数
|
||||
nr = nd // ndrow
|
||||
if nd % ndrow != 0:
|
||||
nr += 1 # 处理余数
|
||||
|
||||
# 读取深度数据
|
||||
dm = [] # 初始化列质量列表
|
||||
i = 0
|
||||
while i < nr:
|
||||
x = lines[i+1] # 从第二行开始读取深度数据
|
||||
x = x.replace('D','E',6) # 替换指数符号
|
||||
val = x.split() # 分割数值
|
||||
j = 0
|
||||
while j < ndrow:
|
||||
k = ndrow * i + j
|
||||
if k < nd:
|
||||
dm.append(float(val[j])) # 存储深度值
|
||||
j += 1
|
||||
i += 1
|
||||
|
||||
# 读取所有状态参数数据
|
||||
nrx = npa // 5 # 每行参数数量
|
||||
if npa % 5 != 0:
|
||||
nrx += 1 # 处理余数
|
||||
|
||||
totpar = [] # 存储所有参数的二维数组
|
||||
i = nr + 1 # 从深度数据后开始读取参数
|
||||
id = 0
|
||||
while id < nd:
|
||||
xpar = [] # 临时参数列表
|
||||
j = 0
|
||||
while j < nrx:
|
||||
x = lines[i] # 读取当前行
|
||||
x = x.replace('D','E',6) # 替换指数符号
|
||||
val = x.split() # 分割数值
|
||||
k = 0
|
||||
while k < 5:
|
||||
if 5*j + k < npa:
|
||||
xpar.append(float(val[k])) # 存储参数值
|
||||
k += 1
|
||||
j += 1
|
||||
i += 1
|
||||
totpar.append(xpar) # 存储所有参数的当前层数据
|
||||
id += 1
|
||||
|
||||
# 数据处理
|
||||
pararr = np.log10(np.array(totpar)) # 转换为对数形式
|
||||
dm = np.log10(dm) # 转换为列质量对数
|
||||
|
||||
# 初始化绘图(首个模型)
|
||||
if imod == 0:
|
||||
fig, ax = plt.subplots() # 创建图形
|
||||
ax.set_xlabel('log mass') # X轴标签
|
||||
ax.set_ylabel('log n') # Y轴标签
|
||||
titl = modfile[:-2] # 标题初始化
|
||||
|
||||
# 绘制指定状态参数
|
||||
for indx in ind: # 遍历所有需要绘制的参数索引
|
||||
ax.plot(dm, pararr[:, indx]) # 绘制对应参数曲线
|
||||
|
||||
# 更新标题
|
||||
if imod != 0:
|
||||
titl += f', {modfile[:-2]}' # 添加模型名称
|
||||
|
||||
imod += 1 # 增加模型计数器
|
||||
|
||||
ax.set_title(titl) # 设置最终标题
|
||||
plt.show() # 显示图形
|
||||
|
||||
|
||||
|
||||
def pflux(modfiles=['fort'], rel=False, ilogx=False):
|
||||
"""
|
||||
绘制Tlusty输出文件(单元14)的出射通量,或多个模型的通量相对差异
|
||||
也可用于绘制Synspec生成的合成光谱
|
||||
参数:
|
||||
-----------
|
||||
modfiles: list of str, 可选
|
||||
模型文件的核心名称列表。若名称不含小数点".",则自动添加".14"
|
||||
默认值:['fort'](对应fort.14)
|
||||
rel: bool, 可选
|
||||
若为True,绘制指定模型的通量相对于首个模型的百分比差异:
|
||||
rel(i) = (flux(i)-flux(0))/flux(0)*100%
|
||||
默认False(绘制实际通量值)
|
||||
ilogx: bool, 可选
|
||||
若为True,设置X轴(波长)为对数坐标
|
||||
默认False(线性坐标)
|
||||
返回:
|
||||
-----------
|
||||
无(直接绘图)
|
||||
"""
|
||||
imod = 0 # 初始化模型计数器
|
||||
for modfile in modfiles: # 遍历所有模型文件
|
||||
if modfile.count('.') == 0: # 自动补充后缀".14"
|
||||
modfile += '.14'
|
||||
|
||||
# 读取波长和通量数据
|
||||
try:
|
||||
wl, fl = np.loadtxt(modfile, unpack=True) # 加载文件数据
|
||||
except:
|
||||
print(f'错误:无法打开 {modfile}')
|
||||
return()
|
||||
|
||||
# 初始化绘图(首个模型)
|
||||
if imod == 0:
|
||||
fig, ax = plt.subplots() # 创建图形
|
||||
ax.set_xlabel('波长') # X轴标签
|
||||
titl = modfile[:-3] # 标题初始化
|
||||
wl0 = wl.copy() # 存储首个模型的波长数据
|
||||
fl0 = fl.copy() # 存储首个模型的通量数据
|
||||
|
||||
if rel: # 相对差异模式
|
||||
fl = (fl - fl0)/fl0 * 100 # 计算初始差异
|
||||
else: # 后续模型
|
||||
titl += f', {modfile[:-3]}' # 更新标题
|
||||
|
||||
if rel: # 相对差异模式处理
|
||||
# 线性插值到首个模型的波长网格
|
||||
fli = np.interp(wl0, wl, fl)
|
||||
fl = (fli - fl0)/fl0 * 100 # 计算相对差异
|
||||
|
||||
# 绘制数据
|
||||
if not rel:
|
||||
if ilogx:
|
||||
ax.semilogx(wl, fl) # 对数坐标X轴
|
||||
else:
|
||||
ax.plot(wl, fl) # 线性坐标X轴
|
||||
else:
|
||||
if ilogx:
|
||||
ax.semilogx(wl0, fl) # 对数坐标X轴 + 相对差异
|
||||
else:
|
||||
ax.plot(wl0, fl) # 线性坐标X轴 + 相对差异
|
||||
|
||||
imod += 1 # 增加模型计数器
|
||||
|
||||
ax.set_title(titl) # 设置最终标题
|
||||
plt.show() # 显示图形
|
||||
|
||||
if __name__ == "__main__":
|
||||
|
||||
file = sys.argv[1]
|
||||
pconv(file)
|
||||
Reference in New Issue
Block a user