How to use the pyclowder.files.upload_to_dataset function in pyclowder

if os.path.exists(merged_txt):
                            # Check if contents
                            with open(merged_txt, 'r') as contents:
                                for entry in contents.readlines():
                                    if entry.strip() == file_path:
                                        already_merged = True
                                        break
                        if not already_merged:
                            clip_las(file_path, tuples, out_path=out_file, merged_path=merged_out)
                            with open(merged_txt, 'a') as contents:
                                contents.write(file_path+"\n")

                        # Upload the individual plot shards for optimizing las2height later
                        found_in_dest = check_file_in_dataset(connector, host, secret_key, target_dsid, out_file, remove=self.overwrite)
                        if not found_in_dest or self.overwrite:
                            fileid = upload_to_dataset(connector, host, secret_key, target_dsid, out_file)
                            uploaded_file_ids.append(host + ("" if host.endswith("/") else "/") + "files/" + fileid)
                        self.created += 1
                        self.bytes += os.path.getsize(out_file)

                        # Upload the merged result if necessary
                        found_in_dest = check_file_in_dataset(connector, host, secret_key, target_dsid, merged_out, remove=self.overwrite)
                        if not found_in_dest or self.overwrite:
                            fileid = upload_to_dataset(connector, host, secret_key, target_dsid, merged_out)
                            uploaded_file_ids.append(host + ("" if host.endswith("/") else "/") + "files/" + fileid)
                        self.created += 1
                        self.bytes += os.path.getsize(merged_out)

                        # Trigger las2height extractor
                        submit_extraction(connector, host, secret_key, target_dsid, "terra.3dscanner.las2height")

timestamp[:4], timestamp[5:7], timestamp[8:10], leaf_dataset))
                    target_dsid = build_dataset_hierarchy_crawl(host, secret_key, self.clowder_user, self.clowder_pass, self.clowderspace,
                                                                season_name, experiment_name, plot_display_name,
                                                                timestamp[:4], timestamp[5:7], timestamp[8:10], leaf_ds_name=leaf_dataset)

                    out_file = self.sensors.create_sensor_path(timestamp, plot=plotname, subsensor=sensor_name, filename=filename)
                    if not os.path.exists(os.path.dirname(out_file)):
                        os.makedirs(os.path.dirname(out_file))

                    if filename.endswith(".tif") and (not file_exists(out_file) or self.overwrite):
                        """If file is a geoTIFF, simply clip it and upload it to Clowder"""
                        clip_raster(file_path, tuples, out_path=out_file, compress=True)

                        found_in_dest = check_file_in_dataset(connector, host, secret_key, target_dsid, merged_out, remove=self.overwrite)
                        if not found_in_dest or self.overwrite:
                            fileid = upload_to_dataset(connector, host, secret_key, target_dsid, merged_out)
                            uploaded_file_ids.append(host + ("" if host.endswith("/") else "/") + "files/" + fileid)
                        self.created += 1
                        self.bytes += os.path.getsize(merged_out)

                    elif filename.endswith(".las"):
                        """If file is LAS, we can merge with any existing scan+plot output safely"""
                        merged_out = os.path.join(os.path.dirname(out_file), target_scan+"_merged.las")
                        merged_txt = merged_out.replace(".las", "_contents.txt")

                        already_merged = False
                        if os.path.exists(merged_txt):
                            # Check if contents
                            with open(merged_txt, 'r') as contents:
                                for entry in contents.readlines():
                                    if entry.strip() == file_path:
                                        already_merged = True