diff model_prediction.xml @ 0:db511406350a draft

planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/model_prediction.xml	Fri Aug 09 07:11:11 2019 -0400
@@ -0,0 +1,128 @@
+<tool id="model_prediction" name="Model Prediction" version="@VERSION@">
+    <description>predicts on new data using a preffited model</description>
+    <macros>
+        <import>main_macros.xml</import>
+        <import>keras_macros.xml</import>
+    </macros>
+    <expand macro="python_requirements"/>
+    <expand macro="macro_stdio"/>
+    <version_command>echo "@VERSION@"</version_command>
+    <command>
+        <![CDATA[
+        python '$__tool_directory__/model_prediction.py'
+            --inputs '$inputs'
+            --infile_estimator '$infile_estimator'
+            --outfile_predict '$outfile_predict'
+            --infile_weights '$infile_weights'
+            #if $input_options.selected_input == 'seq_fasta'
+            --fasta_path '$input_options.fasta_path'
+            #elif $input_options.selected_input == 'variant_effect'
+            --ref_seq '$input_options.ref_genome_file'
+            --vcf_path '$input_options.vcf_file'
+            #else
+            --infile1 '$input_options.infile1'
+            #end if
+        ]]>
+    </command>
+    <configfiles>
+        <inputs name="inputs" />
+    </configfiles>
+    <inputs>
+        <param name="infile_estimator" type="data" format="zip" label="Choose the dataset containing pipeline/estimator object"/>
+        <param name="infile_weights" type="data" format="h5" optional="true" label="Choose the dataset containing weights for the estimator above" help="Optional. For deep learning only."/>
+        <param argument="method" type="select" label="Select invocation method">
+            <option value="predict" selected="true">predict</option>
+            <option value="predict_proba">predict_proba</option>
+        </param>
+        <conditional name="input_options">
+            <param name="selected_input" type="select" label="Select input data type for prediction">
+                <option value="tabular" selected="true">tabular data</option>
+                <option value="sparse">sparse matrix</option>
+                <option value="seq_fasta">sequnences in a fasta file</option>
+                <option value="variant_effect">reference genome and variant call file</option>
+            </param>
+            <when value="tabular">
+                <param name="infile1" type="data" format="tabular" label="Training samples dataset:"/>
+                <param name="header1" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolfalse" checked="False" label="Does the dataset contain header:" />
+                <conditional name="column_selector_options_1">
+                    <expand macro="samples_column_selector_options" multiple="true"/>
+                </conditional>
+            </when>
+            <when value="sparse">
+                <param name="infile1" type="data" format="txt" label="Select a sparse matrix" help=""/>
+            </when>
+            <when value="seq_fasta">
+                <param name="fasta_path" type="data" format="fasta" label="Dataset containing fasta genomic/protein sequences" help="Sequences will be one-hot encoded to arrays."/>
+                <param name="seq_type" type="select" label="Sequence type">
+                    <option value="FastaDNABatchGenerator">DNA</option>
+                    <option value="FastaRNABatchGenerator">RNA</option>
+                    <option value="FastaProteinBatchGenerator">Protein</option>
+                </param>
+            </when>
+            <when value="variant_effect">
+                <param name="ref_genome_file" type="data" format="fasta" label="Dataset containing reference genomic sequence" help="fasta"/>
+                <param name="blacklist_regions" type="select" label="blacklist regioins" help="A pre-loaded list of blacklisted intervals.Refer to `selene` for details.">
+                    <option value="none" selected="true">None</option>
+                    <option value="hg38">hg38</option>
+                    <option value="hg19">hg19</option>
+                </param>
+                <param name="vcf_file" type="data" format="vcf" label="Dataset containing sequence variations" help="vcf"/>
+                <param name="seq_length" type="integer" value="1000" label="Encoding seqence length" help="A stretch of sequence surrounding the variation position on the reference genome."/>
+                <param name="output_reference" type="boolean" truevalue="booltrue" falsevalue="boolfalse" checked="false" label="Predict the reference sequence?" help="If False, predict on the variant sequence."/>
+            </when>
+        </conditional>
+    </inputs>
+    <outputs>
+        <data format="tabular" name="outfile_predict"/>
+    </outputs>
+    <tests>
+        <test>
+            <param name="infile_estimator" value="best_estimator_.zip" ftype="zip"/>
+            <param name="method" value="predict"/>
+            <param name="infile1" value="regression_X.tabular" ftype="tabular"/>
+            <param name="header1" value="true" />
+            <param name="col1" value="1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17"/>
+            <output name="outfile_predict" file="model_pred01.tabular"/>
+        </test>
+        <test>
+            <param name="infile_estimator" value="keras_model04" ftype="zip"/>
+            <param name="infile_weights" value="train_test_eval_weights02.h5" ftype="h5"/>
+            <param name="method" value="predict"/>
+            <param name="infile1" value="regression_X.tabular" ftype="tabular"/>
+            <param name="header1" value="true" />
+            <param name="col1" value="1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17"/>
+            <output name="outfile_predict" >
+                <assert_contents>
+                    <has_n_columns n="1"/>
+                    <has_text text="66.936"/>
+                    <has_text text="59.94"/>
+                    <has_text text="66.19"/>
+                    <has_text text="56.82"/>
+                    <has_text text="74.907"/>
+                </assert_contents>
+            </output>
+        </test>
+    </tests>
+    <help>
+        <![CDATA[
+**What it does**
+
+Given a fitted estimator and new data sets, this tool outpus the prediction results on the data sets via invoking the estimator's `predict` or `predict_proba` method.
+
+For estimator, this tool supports fitted sklearn estimators (pickled) and trained deep learning models (model skeleton + weights). It predicts on three different dataset inputs,
+
+- tabular
+
+- sparse
+
+- bio-sequences in a fasta file
+
+- reference genome and variant call file
+
+        ]]>
+    </help>
+    <expand macro="sklearn_citation">
+        <expand macro="keras_citation"/>
+        <expand macro="selene_citation"/>
+    </expand>
+</tool>