Removed unused generator calls in workflow.

chipathlon/workflow.py

@@ -225,66 +225,6 @@ class Workflow(object):
             self.peak_call_gen.generate(run)
         return
 
-    # When generating actual modules, IF results already exist for that job:
-    # 1. Skip the module.add_jobs call
-    # 2. Add the download gridfs job
-    # 3. Find the module job dependencies with module.get_dependent_jobs,
-    #       and remove them from the dax directly.
-    # This will trickle through each step, that way if a single workflow
-    # path has both align & remove_duplicates output, it will remove the
-    # job that was going to download the alignment output.
-    #
-    # NOTE: Make sure to use outputs and NOT module_outputs when checking for file existence!
-    #       BUT, make sure to use module_outputs and NOT outputs when getting dependent jobs.
-
-    def _add_module(self, generator, rewrite=None):
-        rewrite = rewrite if rewrite is not None else self.rewrite
-        remove_jobs = []
-        required_jobs = []
-        for markers, inputs, additional_inputs, outputs, ref_genome in generator.generate():
-            module_outputs = {mod_file_name : outputs[mod_file_name]["file_name"] for mod_file_name in outputs}
-
-            results = self._get_existing_results(outputs, ref_genome, generator.module.get_final_outputs(markers))
-            module_outputs = {mod_file_name : outputs[mod_file_name]["file_name"] for mod_file_name in outputs}
-            if not rewrite and all([result is not None for result in results]):
-                for result in results:
-                    self._download_from_gridfs(result["gridfs_id"], result["file_name"])
-                for job_name in generator.module.get_dependent_jobs(self.dax, self.jobs, self.files, markers, inputs, additional_inputs, module_outputs):
-                    remove_jobs.append(job_name)
-            else:
-                generator.module.add_jobs(self.dax, self.jobs, self.files, markers, inputs, additional_inputs, module_outputs)
-                self._save_results(outputs, ref_genome)
-                for job_name in generator.module.get_dependent_jobs(self.dax, self.jobs, self.files, markers, inputs, additional_inputs, module_outputs):
-                    required_jobs.append(job_name)
-        self._remove_unused_jobs(remove_jobs, required_jobs)
-        return
-
-    def _add_download(self):
-        download_gen = DownloadGenerator(self.files, self.modules["download"], self.run_data, self.debug)
-        for markers, inputs, additional_inputs, outputs, ref_genome in download_gen.generate():
-            # The output returned from the generator is more complex than
-            # what the module needs
-            module_outputs = {mod_file_name : outputs[mod_file_name]["file_name"] for mod_file_name in outputs}
-
-            download_gen.module.add_jobs(self.dax, self.jobs, self.files, markers, inputs, additional_inputs, module_outputs)
-            self._save_results(outputs, ref_genome)
-        return
-
-    def _add_align(self):
-        align_gen = AlignGenerator(self.files, self.modules["align"], self.run_data, self.debug)
-        self._add_module(align_gen)
-        return
-
-    def _add_remove_duplicates(self):
-        remove_duplicates_gen = RemoveDuplicatesGenerator(self.files, self.modules["remove_duplicates"], self.run_data, self.debug)
-        self._add_module(remove_duplicates_gen)
-        return
-
-    def _add_peak_calling(self):
-        peak_call_gen = PeakCallGenerator(self.files, self.modules["peak_call"], self.run_data, self.debug)
-        self._add_module(peak_call_gen, True)
-        return
-
     def _create_setup(self):
         """
             Creates the base structure for job submission.  Everything is contained