# HG changeset patch
# User bgruening
# Date 1378285804 14400
# Node ID 99091a5d5c843e941367b4b5359d546e84fa3bdc
Uploaded
diff -r 000000000000 -r 99091a5d5c84 EDeN_feature.xml
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/EDeN_feature.xml Wed Sep 04 05:10:04 2013 -0400
@@ -0,0 +1,273 @@
+
+
+
+ openbabel
+ EDEN_SCRIPT_PATH
+
+
+
+ ## pre-processing step if we have a molecule type we need to convert it to the gSpan format at first
+
+ #import tempfile, os
+ #set $temp_gspan = tempfile.NamedTemporaryFile( delete=False )
+ #silent $temp_gspan.close()
+ #set $temp_gspan = $temp_gspan.name
+
+ #if $file_type_opts.file_type_opts_selector == 'sdf':
+ obabel -i sdf -o sdf $infile | \$EDEN_SCRIPT_PATH/mol2gspan.py --infile - --outfile $temp_gspan
+ #set $file_type = 'GRAPH'
+ #elif $file_type_opts.file_type_opts_selector == 'smi':
+ obabel -i smi -o sdf $infile | \$EDEN_SCRIPT_PATH/mol2gspan.py --infile - --outfile $temp_gspan
+ #set $file_type = 'GRAPH'
+ #else:
+ #set $temp_gspan = $infile
+ #set $file_type = $file_type_opts.file_type_opts_selector
+ #end if
+ ;
+
+ EDeN --action FEATURE
+
+ --input_data_file_name $temp_gspan
+ --model_file_name $outfile
+
+ ## if we have an molecule datatype the file_type is set to GRAPH, after convertion to the gSpan Graph format
+ --file_type $file_type
+
+ --binary_file_type ## create a binary sparse vector as output
+ --kernel_type $kernel_type
+ --graph_type $graph_type
+
+ $no_normalization
+ $min_kernel
+
+ --hash_bit_size $hash_bit_size
+ --radius $radius
+ --distance $distance
+ --vertex_degree_threshold $vertex_degree_threshold
+
+ $no_normalization
+ $min_kernel
+
+ --kernel_type $kernel_type ##NSPDK | WDK | PBK | USPK | DDK | NSDDK | ANSDDK | SK [NSPDK]
+ --graph_type $graph_type ##DIRECTED | UNDIRECTED [UNDIRECTED]
+
+ #if $file_type_opts.file_type_opts_selector == 'SEQUENCE':
+
+ --sequence_degree $sequence_degree
+ $sequence_token
+ $sequence_multi_line
+ $sequence_pairwise_interaction
+
+ #end if
+
+ --tree_lambda $tree_lambda
+ --radius_two $radius_two
+
+
+ ### Adds rescaled features from nearest neighbors ###
+
+ #if $smooth_opts.smooth_opts_selector == 'smooth':
+ --smooth
+ --smooth_param $smooth_opts.smoother_param
+
+ --row_index_file_name $row_index_file_name
+ --col_index_file_name $col_index_file_name
+ --num_hash_functions $smooth_opts.num_hash_functions
+ --num_repeat_hash_functions $smooth_opts.num_repeat_hash_functions
+ --max_size_bin $smooth_opts.max_size_bin
+ --eccess_neighbour_size_factor $smooth_opts.eccess_neighbour_size_factor
+ --num_nearest_neighbours $smooth_opts.num_nearest_neighbours
+ $smooth_opts.shared_neighborhood
+ $smooth_opts.no_neighborhood_cache
+ $smooth_opts.no_minhash_cache
+ #end if
+
+ ;
+ rm $temp_gspan
+
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+#if $smooth_opts.smooth_opts_selector == 'smooth':
+ #for $element in str( $smooth_opts.row_index ).split(','):
+ #set $element = $element.strip().split('-')
+ #if len($element) == 2:
+ #for $index in range( int($element[0]), int($element[1]) ):
+ ## the following writes the value at the beginning of each line
+ ## #echo $index# inserts a line break automatically, but do not write it
+ ## to the beginning of the line
+ #echo '%s\n' % $index
+ #end for
+ #else:
+ #echo '%s\n' % $element[0]
+ #end if
+ #end for
+ #end if
+
+#if $smooth_opts.smooth_opts_selector == 'smooth':
+ #for $element in str( $smooth_opts.col_index ).split(','):
+ #set $element = $element.strip().split('-')
+ #if len($element) == 2:
+ #for $index in range( int($element[0]), int($element[1]) ):
+ ## the following writes the value at the beginning of each line
+ ## #echo $index# inserts a line break automatically, but do not write it
+ ## to the beginning of the line
+ #echo '%s\n' % $index
+ #end for
+ #else:
+ #echo '%s\n' % $element[0]
+ #end if
+ #end for
+ #end if
+
+
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+
+
+
+
+.. class:: infomark
+
+**What it does**
+
+The linear model is induced using the accelerated stochastic gradient descent technique by Léon Bottou and Yann LeCun.
+When the target information is 0, a self-training algorithm is used to impute a positive or negative class to the unsupervised instances.
+If the target information is imbalanced a minority class resampling technique is used to rebalance the training set.
+
+This tool is part of the EDeN (Explicit Decomposition with Neighborhoods) suite, developed by Fabrizio Costa.
+
+
+
diff -r 000000000000 -r 99091a5d5c84 EDeN_nearest_neighbor.xml
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/EDeN_nearest_neighbor.xml Wed Sep 04 05:10:04 2013 -0400
@@ -0,0 +1,60 @@
+
+
+
+
+
+ EDeN --action NEAREST_NEIGHBOR
+
+ --input_data_file_name $infile
+ --file_type "SPARSE_VECTOR"
+ --binary_file_type
+
+ --target_file_name $target_infile
+ ##--model_file_name [model] ????????????????????
+
+ --kernel_type $kernel_type
+ --graph_type $graph_type
+
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+.. class:: infomark
+
+**What it does**
+
+Nearest neighbors are efficiently identified with a locality sensitive hashing technique.
+
+This tool is part of the EDeN (Explicit Decomposition with Neighborhoods) suite, developed by Fabrizio Costa.
+
+
+
diff -r 000000000000 -r 99091a5d5c84 EDeN_test.xml
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/EDeN_test.xml Wed Sep 04 05:10:04 2013 -0400
@@ -0,0 +1,57 @@
+
+
+
+
+
+ EDeN --action TEST
+
+ --input_data_file_name $infile
+ --model_file_name $model_outfile
+
+ --file_type "SPARSE_VECTOR"
+ --binary_file_type
+
+ --kernel_type $kernel_type
+ --graph_type $graph_type
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+
+.. class:: infomark
+
+**What it does**
+
+The linear model is induced using the accelerated stochastic gradient descent technique by Léon Bottou and Yann LeCun.
+When the target information is 0, a self-training algorithm is used to impute a positive or negative class to the unsupervised instances.
+If the target information is imbalanced a minority class resampling technique is used to rebalance the training set.
+
+This tool is part of the EDeN (Explicit Decomposition with Neighborhoods) suite, developed by Fabrizio Costa.
+
+
+
diff -r 000000000000 -r 99091a5d5c84 EDeN_train.xml
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/EDeN_train.xml Wed Sep 04 05:10:04 2013 -0400
@@ -0,0 +1,87 @@
+
+
+
+
+
+ EDeN --action TRAIN
+
+ --input_data_file_name $infile
+ --file_type "SPARSE_VECTOR"
+ --binary_file_type
+
+ ## TODO: we need a tool that creates such a file, maybe from the metadata of an SDF file
+ ## target_file_name is a file with 1 or -1 one in each row, indicating the class
+ --target_file_name $target_infile
+ --model_file_name $model_outfile
+
+ --lambda $lambda ##??? notation?
+ --epochs $epoch
+
+ --sparsification_num_iterations $sparsification_num_iterations
+ --topological_regularization_num_neighbors $topological_regularization_num_neighbors
+ --topological_regularization_decay_rate $topological_regularization_decay_rate
+
+ --num_iterations $num_iterations
+ --threshold $threshold
+ --only_positive $only_positive
+ --only_negative $only_negative
+
+ --random_seed $random_seed
+
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+
+
+.. class:: infomark
+
+**What it does**
+
+The linear model is induced using the accelerated stochastic gradient descent technique by Léon Bottou and Yann LeCun.
+When the target information is 0, a self-training algorithm is used to impute a positive or negative class to the unsupervised instances.
+If the target information is imbalanced a minority class resampling technique is used to rebalance the training set.
+
+This tool is part of the EDeN (Explicit Decomposition with Neighborhoods) suite, developed by Fabrizio Costa.
+
+
+REFERENCES
+==========
+
+The code for Stochastic Gradient Descent SVM is adapted from http://leon.bottou.org/projects/sgd. Léon Bottou and Yann LeCun, ''Large Scale Online Learning'', Advances in Neural Information Processing Systems 16, Edited by Sebastian Thrun, Lawrence Saul and Bernhard Schölkopf, MIT Press, Cambridge, MA, 2004.
+
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+
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+
diff -r 000000000000 -r 99091a5d5c84 README.rst
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/README.rst Wed Sep 04 05:10:04 2013 -0400
@@ -0,0 +1,40 @@
+Galaxy wrappres and definitions for EDeN
+========================================
+
+
+
+History
+=======
+
+
+
+
+Installation
+============
+
+Doing this automatically via the Galaxy Tool Shed is probably simplest.
+
+
+Licence (MIT)
+=============
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in
+all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+THE SOFTWARE.
+
+NOTE: This is the licence for the EDeN wrappers **only**. EDeN
+and associated data files are available and licenced separately.
diff -r 000000000000 -r 99091a5d5c84 datatypes_conf.xml
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/datatypes_conf.xml Wed Sep 04 05:10:04 2013 -0400
@@ -0,0 +1,10 @@
+
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diff -r 000000000000 -r 99091a5d5c84 eden.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/eden.py Wed Sep 04 05:10:04 2013 -0400
@@ -0,0 +1,40 @@
+"""
+EDeN filetypes
+"""
+
+from galaxy.datatypes.data import Binary
+
+
+class Gspan( Binary ):
+ """Class describing an gSpan file"""
+ file_ext = "gspan"
+
+ def set_peek( self, dataset, is_multi_byte=False ):
+ if not dataset.dataset.purged:
+ dataset.peek = "gSpan"
+ dataset.blurb = data.nice_size( dataset.get_size() )
+ else:
+ dataset.peek = 'file does not exist'
+ dataset.blurb = 'file purged from disk'
+ def display_peek( self, dataset ):
+ try:
+ return dataset.peek
+ except:
+ return "Binary gSpan file (%s)" % ( data.nice_size( dataset.get_size() ) )
+
+class SparseVector( Binary ):
+ """Class describing an SparseVector file"""
+ file_ext = "sparse"
+
+ def set_peek( self, dataset, is_multi_byte=False ):
+ if not dataset.dataset.purged:
+ dataset.peek = "SparseVector"
+ dataset.blurb = data.nice_size( dataset.get_size() )
+ else:
+ dataset.peek = 'file does not exist'
+ dataset.blurb = 'file purged from disk'
+ def display_peek( self, dataset ):
+ try:
+ return dataset.peek
+ except:
+ return "Binary SparseVector file (%s)" % ( data.nice_size( dataset.get_size() ) )
diff -r 000000000000 -r 99091a5d5c84 mol2gspan.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/mol2gspan.py Wed Sep 04 05:10:04 2013 -0400
@@ -0,0 +1,43 @@
+#!/usr/bin/env python
+
+import os, sys
+import argparse
+
+def main(args ):
+
+ begin = True
+ iid = 0
+ graph_counter = 1
+
+ for line in args.infile:
+ if line.rstrip():
+ if line.strip().endswith('END'):
+ begin = False
+ elif line.strip() == '$$$$':
+ graph_counter += 1
+ iid = 0
+ else:
+ # found header line, like: 21 21 0 0 0 0 0 0 0 0999 V2000
+ if len(line.split()) >= 5 and line.split()[-1] == 'V2000':
+ args.outfile.write('t # id %s\n' % graph_counter)
+ begin=True
+ continue
+ # connection or coordinate/atom table
+ if len(line.split()) >= 4 and begin:
+ # coordinate/atom table
+ if line.split()[3].isalpha():
+ args.outfile.write( 'v %s %s \n' % (iid, line.split()[3]) )
+ iid += 1
+ else:
+ #connection table
+ id, node, edge, trash = line.split(None, 3)
+ args.outfile.write( 'e %s %s %s\n' % ( int(id) - 1 , int(node) -1, edge ) )
+
+if __name__ == "__main__":
+ parser = argparse.ArgumentParser()
+ parser.add_argument('--infile', nargs='?', type=argparse.FileType('r'),
+ default=sys.stdin, help="Specify one or more input files")
+ parser.add_argument('--outfile', type=argparse.FileType('w'),
+ default=sys.stdout, help="Specify one output file")
+ args = parser.parse_args()
+ main( args )
diff -r 000000000000 -r 99091a5d5c84 mol2gspan.xml
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/mol2gspan.xml Wed Sep 04 05:10:04 2013 -0400
@@ -0,0 +1,32 @@
+
+ converter
+
+ openbabel
+ EDEN_SCRIPT_PATH
+
+
+ obabel -i smi -o sdf $infile | \$EDEN_SCRIPT_PATH/mol2gspan.py --infile - --outfile $outfile
+
+
+
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+
+
+
+
+.. class:: infomark
+
+**What it does**
+
+That converter will convert arbitratry molecule files to the gSpan format.
+
+
+
diff -r 000000000000 -r 99091a5d5c84 test-data/3_molecules.gspan
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/3_molecules.gspan Wed Sep 04 05:10:04 2013 -0400
@@ -0,0 +1,129 @@
+t # id 1
+v 0 O
+v 1 O
+v 2 O
+v 3 O
+v 4 C
+v 5 C
+v 6 C
+v 7 C
+v 8 C
+v 9 C
+v 10 C
+v 11 C
+v 12 C
+v 13 H
+v 14 H
+v 15 H
+v 16 H
+v 17 H
+v 18 H
+v 19 H
+v 20 H
+e 0 4 1
+e 0 11 1
+e 1 10 1
+e 1 20 1
+e 2 10 2
+e 3 11 2
+e 4 5 1
+e 4 6 2
+e 5 7 2
+e 5 10 1
+e 6 8 1
+e 6 13 1
+e 7 9 1
+e 7 14 1
+e 8 9 2
+e 8 15 1
+e 9 16 1
+e 11 12 1
+e 12 17 1
+e 12 18 1
+e 12 19 1
+t # id 2
+v 0 O
+v 1 O
+v 2 O
+v 3 O
+v 4 C
+v 5 C
+v 6 C
+v 7 C
+v 8 C
+v 9 C
+v 10 C
+v 11 C
+v 12 C
+v 13 H
+v 14 H
+v 15 H
+v 16 H
+v 17 H
+v 18 H
+v 19 H
+v 20 H
+e 0 4 1
+e 0 11 1
+e 1 10 1
+e 1 20 1
+e 2 10 2
+e 3 11 2
+e 4 5 1
+e 4 6 2
+e 5 7 2
+e 5 10 1
+e 6 8 1
+e 6 13 1
+e 7 9 1
+e 7 14 1
+e 8 9 2
+e 8 15 1
+e 9 16 1
+e 11 12 1
+e 12 17 1
+e 12 18 1
+e 12 19 1
+t # id 3
+v 0 O
+v 1 O
+v 2 O
+v 3 O
+v 4 C
+v 5 C
+v 6 C
+v 7 C
+v 8 C
+v 9 C
+v 10 C
+v 11 C
+v 12 C
+v 13 H
+v 14 H
+v 15 H
+v 16 H
+v 17 H
+v 18 H
+v 19 H
+v 20 H
+e 0 4 1
+e 0 11 1
+e 1 10 1
+e 1 20 1
+e 2 10 2
+e 3 11 2
+e 4 5 1
+e 4 6 2
+e 5 7 2
+e 5 10 1
+e 6 8 1
+e 6 13 1
+e 7 9 1
+e 7 14 1
+e 8 9 2
+e 8 15 1
+e 9 16 1
+e 11 12 1
+e 12 17 1
+e 12 18 1
+e 12 19 1
diff -r 000000000000 -r 99091a5d5c84 test-data/3_molecules.sdf
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/3_molecules.sdf Wed Sep 04 05:10:04 2013 -0400
@@ -0,0 +1,350 @@
+
+ Chemfp
+
+ 21 21 0 0 0 0 0 0 0 0999 V2000
+ 1.2333 0.5540 0.7792 O 0 0 0 0 0 0 0 0 0 0 0 0
+ -0.6952 -2.7148 -0.7502 O 0 0 0 0 0 0 0 0 0 0 0 0
+ 0.7958 -2.1843 0.8685 O 0 0 0 0 0 0 0 0 0 0 0 0
+ 1.7813 0.8105 -1.4821 O 0 0 0 0 0 0 0 0 0 0 0 0
+ -0.0857 0.6088 0.4403 C 0 0 0 0 0 0 0 0 0 0 0 0
+ -0.7927 -0.5515 0.1244 C 0 0 0 0 0 0 0 0 0 0 0 0
+ -0.7288 1.8464 0.4133 C 0 0 0 0 0 0 0 0 0 0 0 0
+ -2.1426 -0.4741 -0.2184 C 0 0 0 0 0 0 0 0 0 0 0 0
+ -2.0787 1.9238 0.0706 C 0 0 0 0 0 0 0 0 0 0 0 0
+ -2.7855 0.7636 -0.2453 C 0 0 0 0 0 0 0 0 0 0 0 0
+ -0.1409 -1.8536 0.1477 C 0 0 0 0 0 0 0 0 0 0 0 0
+ 2.1094 0.6715 -0.3113 C 0 0 0 0 0 0 0 0 0 0 0 0
+ 3.5305 0.5996 0.1635 C 0 0 0 0 0 0 0 0 0 0 0 0
+ -0.1851 2.7545 0.6593 H 0 0 0 0 0 0 0 0 0 0 0 0
+ -2.7247 -1.3605 -0.4564 H 0 0 0 0 0 0 0 0 0 0 0 0
+ -2.5797 2.8872 0.0506 H 0 0 0 0 0 0 0 0 0 0 0 0
+ -3.8374 0.8238 -0.5090 H 0 0 0 0 0 0 0 0 0 0 0 0
+ 3.7290 1.4184 0.8593 H 0 0 0 0 0 0 0 0 0 0 0 0
+ 4.2045 0.6969 -0.6924 H 0 0 0 0 0 0 0 0 0 0 0 0
+ 3.7105 -0.3659 0.6426 H 0 0 0 0 0 0 0 0 0 0 0 0
+ -0.2555 -3.5916 -0.7337 H 0 0 0 0 0 0 0 0 0 0 0 0
+ 1 5 1 0 0 0 0
+ 1 12 1 0 0 0 0
+ 2 11 1 0 0 0 0
+ 2 21 1 0 0 0 0
+ 3 11 2 0 0 0 0
+ 4 12 2 0 0 0 0
+ 5 6 1 0 0 0 0
+ 5 7 2 0 0 0 0
+ 6 8 2 0 0 0 0
+ 6 11 1 0 0 0 0
+ 7 9 1 0 0 0 0
+ 7 14 1 0 0 0 0
+ 8 10 1 0 0 0 0
+ 8 15 1 0 0 0 0
+ 9 10 2 0 0 0 0
+ 9 16 1 0 0 0 0
+ 10 17 1 0 0 0 0
+ 12 13 1 0 0 0 0
+ 13 18 1 0 0 0 0
+ 13 19 1 0 0 0 0
+ 13 20 1 0 0 0 0
+M END
+>
+2244
+
+>
+0.6
+
+>
+1
+11
+10
+3
+15
+17
+13
+5
+16
+7
+14
+9
+8
+4
+18
+6
+12
+2
+
+>
+18
+1 -0.23
+10 -0.15
+11 0.63
+12 0.66
+13 0.06
+14 0.15
+15 0.15
+16 0.15
+17 0.15
+2 -0.65
+21 0.5
+3 -0.57
+4 -0.57
+5 0.08
+6 0.09
+7 -0.15
+8 -0.15
+9 -0.15
+
+>
+3
+
+>
+000008C400000001
+
+>
+39.5952
+
+>
+25.432
+
+>
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+>
+2
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+$$$$
+2244
+ OpenBabel09021316243D
+
+ 21 21 0 0 0 0 0 0 0 0999 V2000
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+ -0.6952 -2.7148 -0.7502 O 0 0 0 0 0 0 0 0 0 0 0 0
+ 0.7958 -2.1843 0.8685 O 0 0 0 0 0 0 0 0 0 0 0 0
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+ -0.7288 1.8464 0.4133 C 0 0 0 0 0 0 0 0 0 0 0 0
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+ -2.0787 1.9238 0.0706 C 0 0 0 0 0 0 0 0 0 0 0 0
+ -2.7855 0.7636 -0.2453 C 0 0 0 0 0 0 0 0 0 0 0 0
+ -0.1409 -1.8536 0.1477 C 0 0 0 0 0 0 0 0 0 0 0 0
+ 2.1094 0.6715 -0.3113 C 0 0 0 0 0 0 0 0 0 0 0 0
+ 3.5305 0.5996 0.1635 C 0 0 0 0 0 0 0 0 0 0 0 0
+ -0.1851 2.7545 0.6593 H 0 0 0 0 0 0 0 0 0 0 0 0
+ -2.7247 -1.3605 -0.4564 H 0 0 0 0 0 0 0 0 0 0 0 0
+ -2.5797 2.8872 0.0506 H 0 0 0 0 0 0 0 0 0 0 0 0
+ -3.8374 0.8238 -0.5090 H 0 0 0 0 0 0 0 0 0 0 0 0
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+ 13 19 1 0 0 0 0
+ 13 20 1 0 0 0 0
+M END
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+000008C400000001
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+>
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+$$$$
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+
+ 21 21 0 0 0 0 0 0 0 0999 V2000
+ 1.2333 0.5540 0.7792 O 0 0 0 0 0 0 0 0 0 0 0 0
+ -0.6952 -2.7148 -0.7502 O 0 0 0 0 0 0 0 0 0 0 0 0
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+ -0.0857 0.6088 0.4403 C 0 0 0 0 0 0 0 0 0 0 0 0
+ -0.7927 -0.5515 0.1244 C 0 0 0 0 0 0 0 0 0 0 0 0
+ -0.7288 1.8464 0.4133 C 0 0 0 0 0 0 0 0 0 0 0 0
+ -2.1426 -0.4741 -0.2184 C 0 0 0 0 0 0 0 0 0 0 0 0
+ -2.0787 1.9238 0.0706 C 0 0 0 0 0 0 0 0 0 0 0 0
+ -2.7855 0.7636 -0.2453 C 0 0 0 0 0 0 0 0 0 0 0 0
+ -0.1409 -1.8536 0.1477 C 0 0 0 0 0 0 0 0 0 0 0 0
+ 2.1094 0.6715 -0.3113 C 0 0 0 0 0 0 0 0 0 0 0 0
+ 3.5305 0.5996 0.1635 C 0 0 0 0 0 0 0 0 0 0 0 0
+ -0.1851 2.7545 0.6593 H 0 0 0 0 0 0 0 0 0 0 0 0
+ -2.7247 -1.3605 -0.4564 H 0 0 0 0 0 0 0 0 0 0 0 0
+ -2.5797 2.8872 0.0506 H 0 0 0 0 0 0 0 0 0 0 0 0
+ -3.8374 0.8238 -0.5090 H 0 0 0 0 0 0 0 0 0 0 0 0
+ 3.7290 1.4184 0.8593 H 0 0 0 0 0 0 0 0 0 0 0 0
+ 4.2045 0.6969 -0.6924 H 0 0 0 0 0 0 0 0 0 0 0 0
+ 3.7105 -0.3659 0.6426 H 0 0 0 0 0 0 0 0 0 0 0 0
+ -0.2555 -3.5916 -0.7337 H 0 0 0 0 0 0 0 0 0 0 0 0
+ 1 5 1 0 0 0 0
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+ 9 16 1 0 0 0 0
+ 10 17 1 0 0 0 0
+ 12 13 1 0 0 0 0
+ 13 18 1 0 0 0 0
+ 13 19 1 0 0 0 0
+ 13 20 1 0 0 0 0
+M END
+$$$$
diff -r 000000000000 -r 99091a5d5c84 tool_dependencies.xml
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/tool_dependencies.xml Wed Sep 04 05:10:04 2013 -0400
@@ -0,0 +1,9 @@
+
+
+
+
+
+
+ $REPOSITORY_INSTALL_DIR/scripts
+
+