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|
.. include:: ../../global.inc
.. include:: manual_chapter_numbers.inc
.. _new_manual.on_the_fly.code:
############################################################################################################################################################################################################
|new_manual.on_the_fly.chapter_num|: Esoteric: Python Code for Generating parameters on the fly with :ref:`@files<decorators.files_on_the_fly>`
############################################################################################################################################################################################################
.. seealso::
* :ref:`Manual Table of Contents <new_manual.table_of_contents>`
* :ref:`@files on-the-fly syntax in detail <decorators.files_on_the_fly>`
* Back to |new_manual.on_the_fly.chapter_num|: :ref:`Generating parameters on the fly <new_manual.on_the_fly>`
************************************
Introduction
************************************
| This script takes N pairs of input file pairs (with the suffices .gene and .gwas)
| and runs them against M sets of simulation data (with the suffix .simulation)
| A summary per input file pair is then produced
In pseudo-code:
STEP_1:
::
for n_file in NNN_pairs_of_input_files:
for m_file in MMM_simulation_data:
[n_file.gene,
n_file.gwas,
m_file.simulation] -> n_file.m_file.simulation_res
STEP_2:
::
for n_file in NNN_pairs_of_input_files:
n_file.*.simulation_res -> n_file.mean
| n = CNT_GENE_GWAS_FILES
| m = CNT_SIMULATION_FILES
************************************
Code
************************************
::
from ruffus import *
import os
#88888888888888888888888888888888888888888888888888888888888888888888888888888888888888888
# constants
#88888888888888888888888888888888888888888888888888888888888888888888888888888888888888888
working_dir = "temp_NxM"
simulation_data_dir = os.path.join(working_dir, "simulation")
gene_data_dir = os.path.join(working_dir, "gene")
CNT_GENE_GWAS_FILES = 2
CNT_SIMULATION_FILES = 3
#88888888888888888888888888888888888888888888888888888888888888888888888888888888888888888
# imports
#88888888888888888888888888888888888888888888888888888888888888888888888888888888888888888
import os, sys
from itertools import izip
import glob
#88888888888888888888888888888888888888888888888888888888888888888888888888888888888888888
# Functions
#88888888888888888888888888888888888888888888888888888888888888888888888888888888888888888
#_________________________________________________________________________________________
#
# get gene gwas file pairs
#
#_________________________________________________________________________________________
def get_gene_gwas_file_pairs( ):
"""
Helper function to get all *.gene, *.gwas from the direction specified
in --gene_data_dir
Returns
file pairs with both .gene and .gwas extensions,
corresponding roots (no extension) of each file
"""
gene_files = glob.glob(os.path.join(gene_data_dir, "*.gene"))
gwas_files = glob.glob(os.path.join(gene_data_dir, "*.gwas"))
#
common_roots = set(map(lambda x: os.path.splitext(os.path.split(x)[1])[0], gene_files))
common_roots &=set(map(lambda x: os.path.splitext(os.path.split(x)[1])[0], gwas_files))
common_roots = list(common_roots)
#
p = os.path; g_dir = gene_data_dir
file_pairs = [[p.join(g_dir, x + ".gene"), p.join(g_dir, x + ".gwas")] for x in common_roots]
return file_pairs, common_roots
#_________________________________________________________________________________________
#
# get simulation files
#
#_________________________________________________________________________________________
def get_simulation_files( ):
"""
Helper function to get all *.simulation from the direction specified
in --simulation_data_dir
Returns
file with .simulation extensions,
corresponding roots (no extension) of each file
"""
simulation_files = glob.glob(os.path.join(simulation_data_dir, "*.simulation"))
simulation_roots =map(lambda x: os.path.splitext(os.path.split(x)[1])[0], simulation_files)
return simulation_files, simulation_roots
#88888888888888888888888888888888888888888888888888888888888888888888888888888888888888888
# Main logic
#88888888888888888888888888888888888888888888888888888888888888888888888888888888888888888
#_________________________________________________________________________________________
#
# setup_simulation_data
#
#_________________________________________________________________________________________
#
# mkdir: makes sure output directories exist before task
#
@follows(mkdir(gene_data_dir, simulation_data_dir))
def setup_simulation_data ():
"""
create simulation files
"""
for i in range(CNT_GENE_GWAS_FILES):
open(os.path.join(gene_data_dir, "%03d.gene" % i), "w")
open(os.path.join(gene_data_dir, "%03d.gwas" % i), "w")
#
# gene files without corresponding gwas and vice versa
open(os.path.join(gene_data_dir, "orphan1.gene"), "w")
open(os.path.join(gene_data_dir, "orphan2.gwas"), "w")
open(os.path.join(gene_data_dir, "orphan3.gwas"), "w")
#
for i in range(CNT_SIMULATION_FILES):
open(os.path.join(simulation_data_dir, "%03d.simulation" % i), "w")
#_________________________________________________________________________________________
#
# cleanup_simulation_data
#
#_________________________________________________________________________________________
def try_rmdir (d):
if os.path.exists(d):
try:
os.rmdir(d)
except OSError:
sys.stderr.write("Warning:\t%s is not empty and will not be removed.\n" % d)
def cleanup_simulation_data ():
"""
cleanup files
"""
sys.stderr.write("Cleanup working directory and simulation files.\n")
#
# cleanup gene and gwas files
#
for f in glob.glob(os.path.join(gene_data_dir, "*.gene")):
os.unlink(f)
for f in glob.glob(os.path.join(gene_data_dir, "*.gwas")):
os.unlink(f)
try_rmdir(gene_data_dir)
#
# cleanup simulation
#
for f in glob.glob(os.path.join(simulation_data_dir, "*.simulation")):
os.unlink(f)
try_rmdir(simulation_data_dir)
#
# cleanup working_dir
#
for f in glob.glob(os.path.join(working_dir, "simulation_results", "*.simulation_res")):
os.unlink(f)
try_rmdir(os.path.join(working_dir, "simulation_results"))
#
for f in glob.glob(os.path.join(working_dir, "*.mean")):
os.unlink(f)
try_rmdir(working_dir)
#_________________________________________________________________________________________
#
# Step 1:
#
# for n_file in NNN_pairs_of_input_files:
# for m_file in MMM_simulation_data:
#
# [n_file.gene,
# n_file.gwas,
# m_file.simulation] -> working_dir/n_file.m_file.simulation_res
#
#_________________________________________________________________________________________
def generate_simulation_params ():
"""
Custom function to generate
file names for gene/gwas simulation study
"""
simulation_files, simulation_file_roots = get_simulation_files()
gene_gwas_file_pairs, gene_gwas_file_roots = get_gene_gwas_file_pairs()
#
for sim_file, sim_file_root in izip(simulation_files, simulation_file_roots):
for (gene, gwas), gene_file_root in izip(gene_gwas_file_pairs, gene_gwas_file_roots):
#
result_file = "%s.%s.simulation_res" % (gene_file_root, sim_file_root)
result_file_path = os.path.join(working_dir, "simulation_results", result_file)
#
yield [gene, gwas, sim_file], result_file_path, gene_file_root, sim_file_root, result_file
#
# mkdir: makes sure output directories exist before task
#
@follows(mkdir(working_dir, os.path.join(working_dir, "simulation_results")))
@files(generate_simulation_params)
def gwas_simulation(input_files, result_file_path, gene_file_root, sim_file_root, result_file):
"""
Dummy calculation of gene gwas vs simulation data
Normally runs in parallel on a computational cluster
"""
(gene_file,
gwas_file,
simulation_data_file) = input_files
#
simulation_res_file = open(result_file_path, "w")
simulation_res_file.write("%s + %s -> %s\n" % (gene_file_root, sim_file_root, result_file))
#_________________________________________________________________________________________
#
# Step 2:
#
# Statistical summary per gene/gwas file pair
#
# for n_file in NNN_pairs_of_input_files:
# working_dir/simulation_results/n.*.simulation_res
# -> working_dir/n.mean
#
#_________________________________________________________________________________________
@collate(gwas_simulation, regex(r"simulation_results/(\d+).\d+.simulation_res"), r"\1.mean")
@posttask(lambda : sys.stdout.write("\nOK\n"))
def statistical_summary (result_files, summary_file):
"""
Simulate statistical summary
"""
summary_file = open(summary_file, "w")
for f in result_files:
summary_file.write(open(f).read())
pipeline_run([setup_simulation_data], multiprocess = 5, verbose = 2)
pipeline_run([statistical_summary], multiprocess = 5, verbose = 2)
# uncomment to printout flowchar
#
# pipeline_printout(sys.stdout, [statistical_summary], verbose=2)
# graph_printout ("flowchart.jpg", "jpg", [statistical_summary])
#
cleanup_simulation_data ()
************************************
Resulting Output
************************************
::
>>> pipeline_run([setup_simulation_data], multiprocess = 5, verbose = 2)
Make directories [temp_NxM/gene, temp_NxM/simulation] completed
Completed Task = setup_simulation_data_mkdir_1
Job completed
Completed Task = setup_simulation_data
>>> pipeline_run([statistical_summary], multiprocess = 5, verbose = 2)
Make directories [temp_NxM, temp_NxM/simulation_results] completed
Completed Task = gwas_simulation_mkdir_1
Job = [[temp_NxM/gene/001.gene, temp_NxM/gene/001.gwas, temp_NxM/simulation/000.simulation] -> temp_NxM/simulation_results/001.000.simulation_res, 001, 000, 001.000.simulation_res] completed
Job = [[temp_NxM/gene/000.gene, temp_NxM/gene/000.gwas, temp_NxM/simulation/000.simulation] -> temp_NxM/simulation_results/000.000.simulation_res, 000, 000, 000.000.simulation_res] completed
Job = [[temp_NxM/gene/001.gene, temp_NxM/gene/001.gwas, temp_NxM/simulation/001.simulation] -> temp_NxM/simulation_results/001.001.simulation_res, 001, 001, 001.001.simulation_res] completed
Job = [[temp_NxM/gene/000.gene, temp_NxM/gene/000.gwas, temp_NxM/simulation/001.simulation] -> temp_NxM/simulation_results/000.001.simulation_res, 000, 001, 000.001.simulation_res] completed
Job = [[temp_NxM/gene/000.gene, temp_NxM/gene/000.gwas, temp_NxM/simulation/002.simulation] -> temp_NxM/simulation_results/000.002.simulation_res, 000, 002, 000.002.simulation_res] completed
Job = [[temp_NxM/gene/001.gene, temp_NxM/gene/001.gwas, temp_NxM/simulation/002.simulation] -> temp_NxM/simulation_results/001.002.simulation_res, 001, 002, 001.002.simulation_res] completed
Completed Task = gwas_simulation
Job = [[temp_NxM/simulation_results/000.000.simulation_res, temp_NxM/simulation_results/000.001.simulation_res, temp_NxM/simulation_results/000.002.simulation_res] -> temp_NxM/000.mean] completed
Job = [[temp_NxM/simulation_results/001.000.simulation_res, temp_NxM/simulation_results/001.001.simulation_res, temp_NxM/simulation_results/001.002.simulation_res] -> temp_NxM/001.mean] completed
|
