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comparison fastpca.xml @ 0:7dbe8bd02431 draft default tip

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"planemo upload for repository https://github.com/galaxycomputationalchemistry/galaxy-tools-compchem/ commit ee29bbfa4e78dca11e2e06d0d35a434c063ab588"
author chemteam
date Thu, 30 Jan 2020 12:58:19 +0000
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-1:000000000000 0:7dbe8bd02431
1 <tool id="fastpca" name="fastpca" version="@VERSION@">
2 <description>- dimensionality reduction of MD simulations</description>
3 <macros>
4 <token name="@VERSION@">0.9.1</token>
5 </macros>
6 <requirements>
7 <requirement type="package" version="@VERSION@">fastpca</requirement>
8 </requirements>
9 <command detect_errors="exit_code"><![CDATA[
10 fastpca
11 -f '$input'
12 -p '$output_proj'
13 #if str($inputs.cov) == 'None':
14 -c '$output_cov'
15 #elif str($inputs.vec) == 'None':
16 -C '$inputs.cov'
17 #end if
18 #if str($inputs.vec) == 'None':
19 -v $output_vec
20 #else:
21 -V '$inputs.vec'
22 #end if
23 #if str($inputs.stats) == 'None':
24 -s '$output_stats'
25 #else:
26 -S '$inputs.stats'
27 #end if
28 -l '$output_val'
29 $norm
30 $periodic
31 $dynamic_shift
32 --verbose
33
34 ]]></command>
35 <inputs>
36 <param format="tabular,xtc" name="input" type="data" label="Input data" help="Either a whitespace-separated tabular file or GROMACS XTC file."/>
37 <section name="inputs" title="Inputs" expanded="true" help="Use these (optional) inputs to project new data onto a previously computed principal space. If not set, the PCA will be computed from scratch and will not be comparable to previous runs." >
38 <param format="tabular" name="cov" type="data" label="Precomputed covariance/correlation matrix" optional="true"/>
39 <param format="tabular" name="vec" type="data" label="Precomputed eigenvectors" optional="true"/>
40 <param format="tabular" name="stats" type="data" label="Precomputed statistics (mean values, sigmas and boundary shifts)" optional="true"/>
41 </section>
42
43 <param name="norm" type="select" label="How to normalize input:" help="Generally, normalization using the covariance matrix is appropriate when the variable scales are similar, and the correlation matrix is used when variables are on different scales." >
44 <option value="">Covariance</option>
45 <option value="-N">Correlation</option>
46 </param>
47 <param name="periodic" type="boolean" label="Compute covariance and PCA on a torus?" truevalue="-P" falsevalue="" value="false" help="Useful for computing PCA on periodic data - for example, dihedral angles."/>
48 <param name="dynamic_shift" type="boolean" label="Use dynamic shifting for periodic projection correction" truevalue="-D" falsevalue="" value="false" help="Default is fale, i.e. simply shift to region of lowest density"/>
49 </inputs>
50 <outputs>
51 <data name="output_proj" format="tabular"/>
52 <data name="output_cov" format="tabular">
53 <filter>inputs["cov"] == None</filter>
54 </data>
55 <data name="output_vec" format="tabular">
56 <filter>inputs["vec"] == None</filter>
57 </data>
58 <data name="output_stats" format="tabular">
59 <filter>inputs["stats"] == None</filter>
60 </data>
61 <data name="output_val" format="tabular"/>
62 </outputs>
63 <tests>
64 <!-- fastpca -f contacts.dat -p proj.dat -c cov.dat -v vec.dat -s stats.dat -l val.dat -N -->
65 <test>
66 <param name="input" value="contacts.dat"/>
67 <param name="norm" value="-N"/>
68 <param name="periodic" value="false"/>
69 <param name="dynamic_shift" value="false"/>
70 <output name="output_proj" file="proj.dat"/>
71 <output name="output_cov" file="cov.dat"/>
72 <output name="output_vec" file="vec.dat"/>
73 <output name="output_stats" file="stats.dat"/>
74 <output name="output_val" file="val.dat"/>
75 </test>
76 <!-- fastpca -f contacts2.dat -p proj2.dat -C cov.dat -V vec.dat -S stats.dat -l val2.dat -N -->
77 <test>
78 <param name="input" value="contacts2.dat"/>
79 <param name="cov" value="cov.dat"/>
80 <param name="stats" value="stats.dat"/>
81 <param name="norm" value="-N"/>
82 <param name="periodic" value="false"/>
83 <param name="dynamic_shift" value="false"/>
84 <output name="output_proj" file="proj2.dat"/>
85 <output name="output_val" file="val2.dat"/>
86 </test>
87 </tests>
88 <help><![CDATA[
89 .. class:: infomark
90
91 **What it does**
92
93 Dimensionality reduction of molecular dynamics trajectories. Data can be input as
94 tabular or GROMACS XTC files. In addition, data can be projected into a previously
95 computed coordinate space by providing precomputed eigenvectors, statistics and
96 a correlation/covariance matrix.
97
98 Data can be normalized using the either the covariance or correlation matrix. Data
99 can also be calculated on a torus, which is useful for periodic data, such as protein
100 dihedral angles.
101
102 _____
103
104
105 .. class:: infomark
106
107 **Input**
108
109 - Tabular or XTC file
110 - If you want to project data into a previously calculated principal space, you can upload precomputed eigenvectors, statistics and correlation/covariance matrix.
111
112 _____
113
114
115 .. class:: infomark
116
117 **Output**
118
119 - Projected data (tabular file) with each column representing a principal component
120 - Eigenvectors, statistics and covariance/correlation matrix
121
122 ]]></help>
123 <citations>
124 <citation type="doi">10.1063/1.4998259</citation>
125 </citations>
126 </tool>
127