Attachment 'ratio_mumd.py'
Download 1 # FLAG plot for ms/mud
2 # check whether numpy library is present
3 try:
4 import numpy
5 except ImportError:
6 print ("numpy library not found. If you want the FLAG-logo to be added to the")
7 print ("plot, please install this library")
8 import numpy as np
9 ################################################################################
10 # Please edit the following blocks #############################################
11 ################################################################################
12 def te(*args):
13 err = 0.
14 for v in args:
15 err += v**2
16 return np.sqrt(err)
17
18 PRELIM = 0
19 # layout specifications
20 titlestring = "$\\rm m_u/m_d$" # plot title
21 plotnamestring = "ratio_mumd" # filename for plot
22 plotxticks = ([[0.4, 0.5, 0.6]])# locations for x-ticks
23 yaxisstrings = [ # x,y-location for y-strings
24 [0.3,18.5,"$\\rm N_f=2+1+1$"],
25 [0.3,8.0,"$\\rm N_f=2+1$"]]
26 xlimits = [0.35,1.02] # plot's xlimits
27 logo = 'upper left' # either of 'upper right'
28 # 'upper left'
29 # 'lower left'
30 # 'lower right'
31 tpos = 0.76 # x-position for the data labels
32
33
34 # the following blocks contain the list of
35 # lattice results that will be plotted, one block for 2, 2+1 and 2+1+1,
36 # respectively
37 #
38 # column item
39 # 0 central value
40 # 1 position on the y-axis
41 # 2 neg. error
42 # 3 pos. error
43 # 4 Collaboration string
44 # 5 this column contains layout parameters for the plot-symbol and
45 # and the collaboration text:
46 # column item
47 # 0 marker style (see bottom of this file for a full list)
48 # 1 marker face color r=red, b=blue, k=black, w=white
49 # g=green
50 # 2 marker color (errorbar and frame), color coding as
51 # for face color
52 # 3 color intensity 0=full, 1=soso, 2=bleak
53 dat2p1p1=[
54 [0.470 , 0.0 , 0.0 , 0.056 , 0.056 , "ETM 14" , ['s','w','r',0,tpos]],
55 [0.513 , te(0.018,0.024,0.006), te(0.018,0.024,0.006), 0.018 , 0.018 , "RM123 17" , ['s','g','g',0,tpos]],
56 [0.4556, te(0.0055,0.0067,0.0013) , te(0.0055,0.0114,0.0013) , 0.0055, 0.0055, "MILC 17" , ['s','l','g',0,tpos]],
57 [0.4529, te(0.0048,0.0067), te(0.0048,0.0150) , 0.0048, 0.0048, "MILC 18" , ['s','l','g',0,tpos]]
58 ]
59
60 dat2p1=[
61 [0.43 , te(0.01,0.08) , te(0.01,0.08) , 0.01 , 0.01 , "MILC 04, HPQCD/MILC/UKQCD 04", ['s','w','r',0,tpos]],
62 [0.42 , te(0.01,0.04) , te(0.01,0.04) , 0.01 , 0.01 , "MILC 09" , ['s','w','r',0,tpos]],
63 [0.432 , te(0.001,0.009,0.039) , te(0.001,0.009,0.039) , 0.001 , 0.001 , "MILC 09A" , ['s','w','r',0,tpos]],
64 [0.4818, te(0.0096,0.086) , te(0.0096,0.086) , 0.0096, 0.0096, "Blum 10" , ['s','w','r',0,tpos]],
65 [0.448 , te(0.006,0.029) , te(0.006,0.029) , 0.006 , 0.006 , "BMW 10A, 10B" , ['s','w','r',0,tpos]],
66 [0.401 , te(0.013,0.045) , te(0.013,0.045) , 0.013 , 0.013 , "Laiho 11" , ['s','w','r',0,tpos]],
67 [0.698 , 0.0 , 0.0 , 0.051 , 0.051 , "PACS-CS 12" , ['s','w','r',0,tpos]],
68 [0.52 , 0.0 , 0.0 , 0.05 , 0.05 , "QCDSF/UKQCD 15" , ['s','w','r',0,tpos]],
69 [0.4582, te(0.0038,0.0082,0.0001,0.0110), te(0.0038,0.0012,0.0001,0.0110), 0.0038, 0.0038, "MILC 16" , ['s','l','g',0,tpos]],
70 [0.485 , te(0.011,0.008,0.014) , te(0.011,0.008,0.014) , 0.011 , 0.011 , "BMW 16" , ['s','g','g',0,tpos]]
71 ]
72
73 datapheno=[
74 [0.48, 0.1,0.1,0,0, "PDG",['^','k','k',0,tpos]]
75 ]
76 # dat2p1=[
77 # [27.4, 0.42, 0.42, 0.1, 0.1, "MILC 04, HPQCD/MILC/UKQCD 04",['s','w','r',0,tpos]],
78 # [28.8, 1.65, 1.65, 0.4, 0.4, "RBC/UKQCD 08" ,['s','w','r',0,tpos]],
79 # [28.8, 0, 0, 0.4, 0.4, "PACS-CS 08" ,['s','w','r',0,tpos]],
80 # [27.2, 0.316, 0.316, 0.1, 0.1, "MILC 09" ,['s','w','g',0,tpos]],
81 # [27.41, 0.229, 0.229, 0.05, 0.05, "MILC 09A" ,['s','g','g',0,tpos]],
82 # [31.2, 0, 0, 2.7, 2.7, "PACS-CS 09" ,['s','w','r',0,tpos]],
83 # [28.31, 1.79, 1.79, 0.29, 0.29, "Blum 10" ,['s','w','r',0,tpos]],
84 # [26.8, 1.36, 1.36, 0.8, 0.8, "RBC/UKQCD 10A" ,['s','l','g',0,tpos]],
85 # [27.53, 0.215, 0.215, 0.2, 0.2, "BMW 10A, 10B" ,['s','g','g',0,tpos]],
86 # [28.4, 1.39, 1.39, 0.5, 0.5, "Laiho 11" ,['s','l','g',0,tpos]],
87 # [26.8, 0, 0, 2., 2., "PACS-CS 12" ,['s','w','r',0,tpos]],
88 # [27.36, 0.39, 0.39, 0.380131, 0.380131, "RBC/UKQCD 12" ,['s','l','g',0,tpos]],
89 # [27.34, 0.21, 0.21, 0.0, 0.0, "RBC/UKQCD 14B" ,['s','g','g',0,tpos]]
90 # ]
91 # dat2=[
92 # [27.2, 0, 0, 3.2, 3.2, "QCDSF/UKQCD 06" ,['s','w','r',0,tpos]],
93 # [27.3, 1.24, 1.24, 0.3, 0.3, "ETM 07" ,['s','w','r',0,tpos]],
94 # [28.1, 0.0, 0, 0.38, 0.38, "RBC 07" ,['s','w','r',0,tpos]],
95 # [27.3, 0.9, 0.9, 0.5, 0.5, "ETM 10B" ,['s','g','g',0,tpos]],
96 # [27.63, 0.13, 0.13, 0.0, 0.0, "ETM 14D",['s','w','r',0,tpos]]
97 # ]
98 # datapheno=[
99 # [25.9, 0,0,0,0, "Weinberg 77" ,['o','b','b',0,tpos]],
100 # [24.4, 1.5,1.5,0,0, "Leutwyler 96",['o','b','b',0,tpos]],
101 # [26.6, 1.6,1.6,0,0, "Kaiser 98" ,['o','b','b',0,tpos]],
102 # [23.4, 5.8,5.8,0,0, "Narison 06" ,['o','b','b',0,tpos]],
103 # [23.5, 1.5,1.5,0,0, "Oller 07" ,['o','b','b',0,tpos]],
104 # [27.5, 0.3,0.3,0,0, "PDG" ,['^','k','k',0,tpos]],
105 # ]
106
107 # The color coding for the FLAG-average (below) is as for the data itself;
108 # the additional list at the end is the RGB-code for the errorband.
109 # Please note that the order inside the list FLAGaverage (if there is more
110 # than one) # is significant, the last item will be plotted last and will
111 # therefore be plotted on top of all others.
112
113 FLAGaverage=[ # there should be as many entries for average as there are data sets
114 # in the case where no average is provided for a given data set
115 # just replace the central value by "NaN"
116 #
117 # with respect to the above there is another column at the end specifying
118 # the type of FLAG-band
119 # 0 -> dashed lines marking the edge of the interval
120 # 1 -> grey area bounded by solid black lines
121 [np.nan,1.,1.,0.,0., "",['^','k','k',0,tpos],1],
122 #[0,0,0,0.,0., "dummy",['s','k','k',0,0],0],
123 [0.485 , te(0.011,0.008,0.014), te(0.011,0.008,0.014), 0.011 , 0.011, "FLAG average for $\\rm N_f=2+1$",['s','k','k',0,tpos],1],
124 [0.513 , te(0.018,0.024,0.006), te(0.018,0.024,0.006), 0.018 , 0.018, "FLAG average for $\\rm N_f=2+1+1$",['s','k','k',0,tpos],1]]
125
126 # The follwing list should contain the list names of the previous DATA-blocks
127 datasets=[datapheno,dat2p1,dat2p1p1]
128
129 ################################################################################
130 # DO NOT EDIT THE FOLLOWING ####################################################
131 ################################################################################
132
133
134 # Now that all the relevant has been specified, generate the plot.
135 # Please make sure that you have a directory called "plots" in you current
136 # working directory. That's where all plots will be stored
137 #execfile('FLAGplot.py')
138 exec(compile(open('FLAGplot.py').read(), 'FLAGplot.py', 'exec'))
139
140 # additional documentation:
141 # '.' point marker
142 # ',' pixel marker
143 # 'o' circle marker
144 # 'v' triangle_down marker
145 # '^' triangle_up marker
146 # '<' triangle_left marker
147 # '>' triangle_right marker
148 # '1' tri_down marker
149 # '2' tri_up marker
150 # '3' tri_left marker
151 # '4' tri_right marker
152 # 's' square marker
153 # 'p' pentagon marker
154 # '*' star marker
155 # 'h' hexagon1 marker
156 # 'H' hexagon2 marker
157 # '+' plus marker
158 # 'x' x marker
159 # 'D' diamond marker
160 # 'd' thin_diamond marker
161 # '|' vline marker
162 # '_' hline marker
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