SPEX Reference manual (PDF) - SRON

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32 Syntax overview eV, keV, Å, as well as in units of Rydberg (ryd), Joules (j), Hertz (hz) and nanometers (nm). obin [instrument #i1:] [region #i2:] #i3: - Here #i3: is the same as #i1: in the first command. However, here one can specify the instrument range #i1: and the region range #i2: as well, so that the binning is done only for one given data set. obin [instrument #i1:] [region #i2:] #r1: [unit #a] - This command is the same as the above, except that here one can specify the range over which the binning should occur in the units specified by #a. These units can be eV, Å, keV, as well as in units of Rydberg (ryd), Joules (j), Hertz (hz) and nanometers (nm). Examples obin 1:10000 - Optimally bins the data channels 1:10000. obin 1:4000 unit ev - Does the same as the above, but now the data range to be binned is given in eV, from 1−4000 eV, instead of in data channels. obin instrument 1 region 1 1:19 unit a - Bins the data from instrument 1 and region 1 between 1 and 19 Å. 2.21 Par: Input and output of model parameters Overview This command is used as an interface to set or display the parameters of the spectral model. Each model parameter (like temperature T, abundance, normalization etc.) has a set of attributes, namely its value, status, range and coupling. This is illustrated by the following example. Assume we have a spectral model consisting of a thermal plasma. Consider the silicon abundance (acronym in the model: 14). It can have a value (for example 2.0, meaning twice the solar abundance). Its status is a logical variable, true (thawn) if the parameter can be adjusted during the spectral fitting proces or false (frozen) if it should be kept fixed during the spectral fit. The range is the allowed range that the parameter can have during the spectral fit, for example 0–1000 (minimum – maximum values). This is useful to set to constrain a spectral search to a priori ”reasonable” values (e.g. abundances should be non-negative) or ”safe” values (SPEX could crash for negative temperatures for example). Finally the coupling allows you to couple parameters, for example if the Si abundance is coupled to the Fe abundance, a change in the Fe abundance (either defined by the user or in a spectral fitting process) will result automatically in an adjustment of the Si abundance. This is a useful property in practical cases where for example a spectrum has strong Fe lines and weaker lines from other species, but definitely non-solar abundances. In this case, one may fit the Fe abundance, but the statistics for the other elements may not be sufficient to determine their abundance accurately; however a priori insight might lead you to think that it is the global metallicity that is enhanced, and therefore you would expect the Si abundance to be enhanced in the same way as Fe. With the par command, you can set for each parameter individually or for a range of parameters in the same command, their attributes (value, status, rangeand coupling). Also, you candisplay the parameters on the screen or write them on a SPEX command file, which allows you to start another run with the current set of parameters. When setting parameters, you can also specify the sector (range) and component (range). For your first call, it is assumed that you refer to sector 1, component 1, first parameter. In all subsequent calls of the parameter command, it is assumed that you refer to the same sector(s) and component(s) as your last call, unless specified differently. This is illustrated by the following example. Suppose you have the following model: power law (component 1), blackbody (component 2) and RGS line broadening (lpro, component 3). If you type in the commands in that order, this is what happens: • par val 2 – sets the norm (= first parameter) of the power law to value 2 • par gam val 3 – sets the photon index of the power law to value 3
2.21 Par: Input and output of model parameters 33 • par 2 t val 2.5 – sets the temperature of the blackbody to 2.5 keV • par norm val 10 – sets the norm of the blackbody to 10 • par 1:2 norm v 5 – sets the norm of both the PL and BB to 5 • par val 4.2 – sets the norm of both the PL and BB to 4.2 • par 3 file avalue myprofile.dat – sets for the LPRO component the file name with the broadening kernel to myprofile.dat. Note that the command ’value’ changes here to ’avalue’ to indicate that the parameter is an ascii string. Instrument normalisations can be thawned by entering the instrument number as a negative sector number. For example, freeing the instrument normalisation of instrument 2 is done with the command par -2 1 norm stat thawn. The second value in the command (1) is the region number. Therefore, freeing the normalisation of the third region of the fourth instrument is done with the command: par -4 3 norm stat thawn. Syntax The following syntax rules apply: par [#i1:] [#i2:] [#a1:] avalue #a2 - Assign the value #a2 to the parameters specified by the (range of) name(s) #a1 of component range #i2: of sectors #i1:. The sector (range), component (range) and parameter name (range) are optional. If #a2 should be an empty text string, specify the value ”none” (without quotes, and all four characters in lowercase). If they are not specified, the sector(s), component(s) and parameter(s) of the last call are used. This command containing the word ”avalue” holds for input of text strings. For the input of real numbers ”avalue” is replaced by ”value” and #a2. par [#i1:] [#i2:] [#a:] value #r-Assign the value #rto the parametersspecified bythe (range of) name(s) #a of component range #i2: of sectors #i1:. The sector (range), component (range) and parameter name (range) are optional. If not specified, the sector(s), component(s) and parameter(s) of the last call are used. par [#i1:] [#i2:] [#a:] status #l - As above but for the status of a (range of) parameters; #l = T (true, thawn) means a parameter that can be adjusted during a spectral fit, #l = F (false, froze, fixed) means a parameter that will remain fixed during the spectral fitting. par [#i1:] [#i2:] [#a:] range #r1 #r2 - As above but fore the allowed range of the parameter. #r1 denotes the lower limit and #r2 denotes the upper limit. Both should be specified. par [#i1:] [#i2:] [#a1:] couple [#i3:] [#i4:] #a2: - Here #i1:, #i2:, #a1: are the sector(s), component(s) and parameter(s) that are to be coupled. The parameter (s) to which they are coupled are specified by #a2: and the optional #i3:, #i4:. If ranges are used, take care that the number of sectors, components and parameters on the right and left match. par [#i1:] [#i2:] [#a1:] couple [#i3:] [#i4:] #a2: factor #r - As above, but couple using a scaling factor #r. par [#i1:] [#i2:] #a: decouple- Decouples the parameter(s) #a: of (optional) components #i2: of of (optional) sector(s) #i1:. Inverse operation of the couple command. par show [free] - Shows on the display screen all parameters of all components. If the optional keyword free is given, shows only parameters with fit status ”T” (true, thawn), i.e., the free parameters in a spectral fit. par write #a [overwrite]- Writes all parametersto a SPEXcommand file #a. #a should be specified without extension, SPEX automatically adds the .com extension. If the optional overwrite command is given, then the file #a will be overwritten with the new values. Examples par val 10 - Sets the value of the current parameter to 10. par t val 4 - Sets the parameter named ”t” to 4. par 06:28 value 0.3 - Sets the parameters named 06:28 (for example the abundances of C (Z = 6), N
Page 1: SPEX Reference Manual Jelle Kaastra
Page 4 and 5: 4 CONTENTS 2.29 System . . . . . .
Page 6 and 7: 6 CONTENTS 6.6 Rgsvprof . . . . . .
Page 8 and 9: 8 Introduction 1.2.2 Sky sectors Fi
Page 10 and 11: 10 Introduction
Page 12 and 13: 12 Syntax overview Table 2.2: Abund
Page 14 and 15: 14 Syntax overview tcl: the continu
Page 16 and 17: 16 Syntax overview Examples calc -
Page 18 and 19: 18 Syntax overview data delete inst
Page 20 and 21: 20 Syntax overview dem mult #i - Do
Page 22 and 23: 22 Syntax overview distance show -
Page 24 and 25: 24 Syntax overview Examples elim 0.
Page 26 and 27: 26 Syntax overview There is yet ano
Page 28 and 29: 28 Syntax overview ignore 1:8 unit
Page 30 and 31: 30 Syntax overview written to this
Page 34 and 35: 34 Syntax overview (Z = 7), ... Ni
Page 36 and 37: 36 Syntax overview plot view x1 #r
Page 38 and 39: 38 Syntax overview plot model lw #i
Page 40 and 41: 40 Syntax overview 2.25 Shiftplot:
Page 42 and 43: 42 Syntax overview 2.27 Step: Grid
Page 44 and 45: 44 Syntax overview system exe #a -
Page 46 and 47: 46 Syntax overview Update: several
Page 48 and 49: 48 Syntax overview Also the totals
Page 50 and 51: 50 Spectral Models Table 3.1: Avail
Page 52 and 53: 52 Spectral Models nr name chemical
Page 54 and 55: 54 Spectral Models (cf. Rybicky & L
Page 56 and 57: 56 Spectral Models 3.6.5 Abundances
Page 58 and 59: 58 Spectral Models 3.8 dabs: dust a
Page 60 and 61: 60 Spectral Models 3.11 Dem: Differ
Page 62 and 63: 62 Spectral Models • ... • last
Page 64 and 65: 64 Spectral Models f9 - Transmissio
Page 66 and 67: 66 Spectral Models 3.22 Neij: Non-E
Page 68 and 69: 68 Spectral Models Warning: By defa
Page 70 and 71: 70 Spectral Models seeing equal con
Page 72 and 73: 72 Spectral Models • type=4: b 1
Page 74 and 75: 74 Spectral Models v - Velocity bro
Page 76 and 77: 76 Spectral Models For more informa
Page 78 and 79: 78 More about spectral models Slab
Page 80 and 81: 80 More about spectral models depth
Page 82 and 83:
82 More about spectral models grid
Page 84 and 85:
84 More about spectral models The e
Page 86 and 87:
86 More about plotting Table 5.1: A
Page 88 and 89:
88 More about plotting 5.5 Plot tex
Page 90 and 91:
90 More about plotting Table 5.4: S
Page 92 and 93:
92 More about plotting Table 5.5: x
Page 94 and 95:
94 More about plotting the plot wil
Page 96 and 97:
96 More about plotting
Page 98 and 99:
98 Auxilary programs Property Spect
Page 100 and 101:
100 Auxilary programs Property Resp
Page 102 and 103:
102 Auxilary programs 15. Optional:
Page 104 and 105:
104 Auxilary programs 6.3 RGS fluxc
Page 106 and 107:
106 Auxilary programs This redistri
Page 108 and 109:
108 Auxilary programs 6.6.1 Theory
Page 110 and 111:
110 Response matrices models. Since
Page 112 and 113:
112 Response matrices Table 7.1: We
Page 114 and 115:
114 Response matrices Table 7.2: Sc
Page 116 and 117:
116 Response matrices since the lar
Page 118 and 119:
118 Response matrices Figure 7.1: D
Page 120 and 121:
120 Response matrices Figure 7.3: R
Page 122 and 123:
122 Response matrices 7.4 Model bin
Page 124 and 125:
124 Response matrices In this secti
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126 Response matrices The resulting
Page 128 and 129:
128 Response matrices where w 1 and
Page 130 and 131:
130 Response matrices spectrumextra
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132 Response matrices may be helpfu
Page 134 and 135:
134 Response matrices 1. The OGIP r
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136 Response matrices Table 7.9: Se
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138 Response matrices could be the
Page 140 and 141:
140 Response matrices Table 7.13: R
Page 142 and 143:
142 Response matrices Figure 7.8: B
Page 144 and 145:
144 Response matrices Figure 7.9: B
Page 146 and 147:
146 Installation and testing
Page 148 and 149:
148 Acknowledgements
Page 150 and 151:
150 BIBLIOGRAPHY [1989] Kaastra, J.
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