<?xml version="1.0" encoding="utf-8"?>
<tool id="scanpy_run_dpt" name="Scanpy DPT" version="@TOOL_VERSION@+galaxy6">
  <description>diffusion pseudotime inference</description>
  <macros>
    <import>scanpy_macros2.xml</import>
  </macros>
  <expand macro="requirements"/>
  <command detect_errors="exit_code"><![CDATA[
ln -s '${input_obj_file}' input.h5 &&
PYTHONIOENCODING=utf-8 scanpy-cli dpt
    --n-dcs $n_dcs
    --root '${root_attr}' '${root_value}'
#if $n_branchings > 0
    --n-branchings ${n_branchings}
    --min-group-size ${min_group_size}
#end if
#if $use_graph
    --use-graph '${use_graph}'
#end if
#if $key_added
    --key-added '${key_added}'
#end if
    @INPUT_OPTS@
    @OUTPUT_OPTS@
]]></command>

  <inputs>
    <expand macro="input_object_params"/>
    <expand macro="output_object_params"/>

    <param name="n_dcs" argument="--n-dcs" type="integer" min="2" value="10"
           label="Number of diffusion components to use"/>
    <param name="n_branchings" argument="--n-branchings" min="0" type="integer" value="0"
           label="Number of branchings to detect"/>
    <param name="min_group_size" argument="--min-group-size" type="float" min="0" max="1" value="0"
           label="The fraction of total cells under which further splitting is skipped during recursive splitting of branches"
           help="Ignored when `Number of branchings to detect` is 0"/>
    <param name="root_attr" argument="--root {attr} value" type="text"
           label="Name of attribute that defines clustering"/>
    <param name="root_value" argument="--root attr {value}" type="text"
           label="Name of the clustering that defines the root cell type"/>
    <param name="use_graph" argument="--use-graph" value="neighbors" type="text"
           label="Name of the slot that holds the KNN graph"/>
    <param name="key_added" argument="--key-added" type="text" optional="true"
           label="Additional suffix to the name of the slot to save the calculated trajectory"/>
  </inputs>

  <outputs>
    <expand macro="output_data_obj" description="Diffussion pseudotime inference"/>
  </outputs>

  <tests>
    <test>
      <param name="input_obj_file" value="diffmap.h5"/>
      <param name="input_format" value="anndata"/>
      <param name="output_format" value="anndata"/>
      <param name="n_dcs" value="10"/>
      <param name="root_attr" value="leiden"/>
      <param name="root_value" value="1"/>
      <param name="use_graph" value="neighbors"/>
      <output name="output_h5" file="paga.h5" ftype="h5" compare="sim_size"/>
    </test>
  </tests>

  <help><![CDATA[
================================================
Calculate Diffusion Pseudotime (`scanpy.tl.dpt`)
================================================

Calculate diffusion pseudotime from single cell KNN graphs.

This requires to run `Scanpy DiffusionMap` and `Scanpy FindCluster`, first.

It yields `dpt_pseudotime`, diffusion pseudotime as an attribute for each cell.

@HELP@

@VERSION_HISTORY@
]]></help>
  <expand macro="citations">
    <citation type="doi">10.1186/s13059-019-1663-x</citation>
  </expand>
</tool>