diff --git a/README.md b/README.md index afad2ca..4c67013 100644 --- a/README.md +++ b/README.md @@ -32,6 +32,7 @@ In the following sections, you can find a list of available recipes for each lan - [Create datasets from Excel files](python/create_datasets_from_excel) 📊 - [Download Croissant from draft dataset](python/download_draft_croissant) - [Create Croissant from the client side](python/create_croissant_client_side) +- [Transfer files from Nextcloud link share to dataset](python/upload_nextcloud) ### Shell 🐚 diff --git a/python/upload_nextcloud/README.md b/python/upload_nextcloud/README.md new file mode 100644 index 0000000..0f37b8f --- /dev/null +++ b/python/upload_nextcloud/README.md @@ -0,0 +1,71 @@ +# Nextcloud Data Transfer Script + +This directory contains a script `transfer.py` to transfer data from a Nextcloud link share into a target dataset. + +## Installation + +You have a few choices. You can use pip, pipx, uv or poetry. +The simplest way to go about this: + +1. Run `pip install git+https://github.com/gdcc/dataverse-recipes.git@main#subdirectory=python/upload_nextcloud` +2. Run `nc-transfer` (the installed package will create this wrapper for you) + +## Usage + +```text +$ transfer.py --help +usage: transfer.py [-h] [--share SHARE] [--subpath SUBPATH] [--instance INSTANCE] [--api-token API_TOKEN] + [--dataset-doi DATASET_DOI] [--skip-existing] [--temp-dir TEMP_DIR] + [--journal-file JOURNAL_FILE] [--verbose] [--env-file ENV_FILE] + +Transfer files from Nextcloud link share to Dataverse + +options: + -h, --help show this help message and exit + --share SHARE (Req.) Nextcloud public share URL (e.g., https://cloud.example.com/s/sHaReToKeN). + Can be set as env var NEXTCLOUD_SHARE_URL. + --subpath SUBPATH (Opt.) Subpath within the Nextcloud share to start the file tree traversal from + --instance INSTANCE (Req.) Dataverse instance URL (e.g., https://demo.dataverse.org). Can be set as + env var DATAVERSE_URL. + --api-token API_TOKEN + (Req.) Dataverse API Token. Superadmin or other with permissions for dataset. Can + be set as env var DATAVERSE_API_TOKEN. + --dataset-doi DATASET_DOI + (Req.) Target dataset DOI (e.g., doi:10.1234/5678). Can be set as env var + DATASET_DOI. + --skip-existing (Opt.) Skip files that have already been uploaded to the dataset (default: exit + with error) + --keep-zips (Opt.) If ZIP files are uploaded, double-ZIP them to avoid unpackaging by Dataverse + --temp-dir TEMP_DIR Temporary directory for downloads (default: system temp) + --journal-file JOURNAL_FILE + Journal file to track progress (default: transfer_journal.txt) + --verbose Enable verbose logging output + --env-file ENV_FILE Path to .env file (default: .env in current directory) +``` + +### Example + +To transfer all files in a link share at `https://cloud.example.org/s/TLbS3JtOJ6NXADe`, follow these steps: + +1. Have your target installation URL and dataset DOI at the ready. For this example, let's assume: + - Installation URL: `https://dataverse.example.org` + - Dataset DOI: `doi:10.1234/foobar/123456` +2. Ensure you have an API Token and appropriate permissions on the dataset. You can create or look up the token at `https://dataverse.example.org/dataverseuser.xhtml?selectTab=apiTokenTab`. +3. To avoid saving secrets in your shell history, use a `.env` file: + ```plain + DATAVERSE_API_TOKEN=1234-5678-9012 + DATAVERSE_URL=https://dataverse.example.org + ``` + You can add more options, see help text above. In case of multiple activities, this shortens the CLI commands. +4. Now start the transfer: + ```shell + $ nc-transfer \ + --share "https://cloud.example.org/s/TLbS3JtOJ6NXADe" \ + --dataset-doi "doi:10.1234/foobar/123456" \ + ``` + +A transfer log will be created to avoid re-transferring files successfully copied. + +Have fun! + + diff --git a/python/upload_nextcloud/poetry.lock b/python/upload_nextcloud/poetry.lock new file mode 100644 index 0000000..eea246e --- /dev/null +++ b/python/upload_nextcloud/poetry.lock @@ -0,0 +1,556 @@ +# This file is automatically @generated by Poetry 2.2.1 and should not be changed by hand. + +[[package]] +name = "anyio" +version = "4.11.0" +description = "High-level concurrency and networking framework on top of asyncio or Trio" +optional = false +python-versions = ">=3.9" +groups = ["main"] +files = [ + {file = "anyio-4.11.0-py3-none-any.whl", hash = "sha256:0287e96f4d26d4149305414d4e3bc32f0dcd0862365a4bddea19d7a1ec38c4fc"}, + {file = "anyio-4.11.0.tar.gz", hash = "sha256:82a8d0b81e318cc5ce71a5f1f8b5c4e63619620b63141ef8c995fa0db95a57c4"}, +] + +[package.dependencies] +exceptiongroup = {version = ">=1.0.2", markers = "python_version < \"3.11\""} +idna = ">=2.8" +sniffio = ">=1.1" +typing_extensions = {version = ">=4.5", markers = "python_version < \"3.13\""} + +[package.extras] +trio = ["trio (>=0.31.0)"] + +[[package]] +name = "attrs" +version = "25.3.0" +description = "Classes Without Boilerplate" +optional = false +python-versions = ">=3.8" +groups = ["main"] +files = [ + {file = "attrs-25.3.0-py3-none-any.whl", hash = "sha256:427318ce031701fea540783410126f03899a97ffc6f61596ad581ac2e40e3bc3"}, + {file = "attrs-25.3.0.tar.gz", hash = "sha256:75d7cefc7fb576747b2c81b4442d4d4a1ce0900973527c011d1030fd3bf4af1b"}, +] + +[package.extras] +benchmark = ["cloudpickle ; platform_python_implementation == \"CPython\"", "hypothesis", "mypy (>=1.11.1) ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pympler", "pytest (>=4.3.0)", "pytest-codspeed", "pytest-mypy-plugins ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pytest-xdist[psutil]"] +cov = ["cloudpickle ; platform_python_implementation == \"CPython\"", "coverage[toml] (>=5.3)", "hypothesis", "mypy (>=1.11.1) ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pytest-xdist[psutil]"] +dev = ["cloudpickle ; platform_python_implementation == \"CPython\"", "hypothesis", "mypy (>=1.11.1) ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pre-commit-uv", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pytest-xdist[psutil]"] +docs = ["cogapp", "furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier"] +tests = ["cloudpickle ; platform_python_implementation == \"CPython\"", "hypothesis", "mypy (>=1.11.1) ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pytest-xdist[psutil]"] +tests-mypy = ["mypy (>=1.11.1) ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pytest-mypy-plugins ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\""] + +[[package]] +name = "certifi" +version = "2025.8.3" +description = "Python package for providing Mozilla's CA Bundle." +optional = false +python-versions = ">=3.7" +groups = ["main"] +files = [ + {file = "certifi-2025.8.3-py3-none-any.whl", hash = "sha256:f6c12493cfb1b06ba2ff328595af9350c65d6644968e5d3a2ffd78699af217a5"}, + {file = "certifi-2025.8.3.tar.gz", hash = "sha256:e564105f78ded564e3ae7c923924435e1daa7463faeab5bb932bc53ffae63407"}, +] + +[[package]] +name = "charset-normalizer" +version = "3.4.3" +description = "The Real First Universal Charset Detector. 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+include = ["transfer.py"] + +[tool.poetry] +packages = [{include = "transfer.py"}] \ No newline at end of file diff --git a/python/upload_nextcloud/transfer.py b/python/upload_nextcloud/transfer.py new file mode 100644 index 0000000..5618206 --- /dev/null +++ b/python/upload_nextcloud/transfer.py @@ -0,0 +1,466 @@ +#!/usr/bin/env python3 +""" +Nextcloud to Dataverse Transfer Tool + +This script downloads files from a Nextcloud link share and uploads them to a Dataverse dataset. +It handles file size limit adjustments, resumable downloads, and maintains a journal for progress tracking. +""" + +import argparse +import zipfile +from zipfile import ZIP_STORED + +import humanize +import json +import logging +import os +import re +import requests +import sys +import tempfile +import xml.etree.ElementTree as ET +from pathlib import Path +from pyDataverse.api import NativeApi +from pyDataverse.models import Datafile +from typing import List, Dict, Optional, Union +from urllib.parse import urljoin, urlparse, unquote + +# Set up logging +logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s') +logger = logging.getLogger(__name__) + +# Constants +DEFAULT_TEMP_DIR = tempfile.gettempdir() +DEFAULT_JOURNAL_FILE = 'transfer_journal.txt' +DEFAULT_INVALID_DIRLABEL_CHARS_REGEX = "[^a-zA-Z0-9_.-/\\ ]+" +DEFAULT_INVALID_DIRLABEL_REPLACEMENT_CHAR = "." + +class Transfer: + def __init__(self, share_url, dataverse_url, api_token, dataset_doi, skip_existing=False, + subpath="", temp_dir=None, journal_file=DEFAULT_JOURNAL_FILE, + invalid_dirlabel_regex=DEFAULT_INVALID_DIRLABEL_CHARS_REGEX, invalid_dirlabel_replacement_char=DEFAULT_INVALID_DIRLABEL_REPLACEMENT_CHAR, + keep_zips=False): + self.share_url = share_url + self.largest_file_size = -1 + self.dataverse_url = dataverse_url + self.api_token = api_token + self.dataset_doi = dataset_doi + self.subpath = subpath.strip('/') + self.skip_existing = skip_existing + self.temp_dir = temp_dir or tempfile.gettempdir() + self.journal_file = journal_file + self.native_api = NativeApi(dataverse_url, api_token) + self.original_limit = None + self.invalid_dirlabel_regex = re.compile(invalid_dirlabel_regex) + self.invalid_dirlabel_replacement_char = invalid_dirlabel_replacement_char + self.keep_zips = keep_zips + + # Create temp directory if it doesn't exist + os.makedirs(self.temp_dir, exist_ok=True) + + # Session for requests + self.session = requests.Session() + + def get_webdav_url(self): + """Convert public share URL to WebDAV URL""" + parsed = urlparse(self.share_url) + share_token = parsed.path.split('/')[-1] + webdav_url = f"{parsed.scheme}://{parsed.netloc}/public.php/webdav" + return webdav_url, share_token + + def list_files_recursive(self, path: str = "") -> List[Dict[str, str | int]]: + """Recursively list all files in the Nextcloud share using WebDAV""" + webdav_url, share_token = self.get_webdav_url() + full_path = path + if self.subpath: + full_path = f"{self.subpath}/{path}".strip('/') + + propfind_url = urljoin(webdav_url + "/", full_path) + + # PROPFIND request to get directory contents + headers = {'Depth': '1'} + auth = (share_token, '') + + try: + response = self.session.request('PROPFIND', propfind_url, auth=auth, headers=headers) + response.raise_for_status() + except requests.RequestException as e: + logger.error(f"Failed to access Nextcloud share: {e}") + sys.exit(1) + + # Parse WebDAV XML response + files = [] + root = ET.fromstring(response.content) + responses = root.findall('.//{DAV:}response') + + # Check if this is a single file share (only one response and it's a file) + if len(responses) == 1: + response_elem = responses[0] + propstat = response_elem.find('.//{DAV:}propstat') + if propstat is not None: + prop = propstat.find('{DAV:}prop') + if prop is not None: + resourcetype = prop.find('{DAV:}resourcetype') + is_directory = resourcetype.find('{DAV:}collection') is not None + + if not is_directory: + # This is a single file share + href = response_elem.find('{DAV:}href').text + # Remove webdav prefix and decode URL encoding + relative_path = unquote(href.replace('/public.php/webdav/', '').strip('/')) + + size_elem = prop.find('{DAV:}getcontentlength') + file_size = int(size_elem.text) if size_elem is not None else 0 + + # For single file shares, use just the filename + file_path = os.path.basename(relative_path) if relative_path else "shared_file" + + files.append({ + 'path': file_path, + 'size': file_size, + 'full_path': relative_path + }) + + return files + + + for response_elem in responses: + href = response_elem.find('{DAV:}href').text + # Remove webdav prefix and decode + relative_path = unquote(href.replace('/public.php/webdav/', '').strip('/')) + + # Skip the current directory itself + if relative_path == full_path: + continue + + # Get properties + propstat = response_elem.find('.//{DAV:}propstat') + if propstat is None: + continue + + prop = propstat.find('{DAV:}prop') + if prop is None: + continue + + # Check if it's a file or directory + resourcetype = prop.find('{DAV:}resourcetype') + is_directory = resourcetype.find('{DAV:}collection') is not None + + if is_directory: + # Recursively get files from subdirectory + subdir_path = relative_path + if self.subpath: + subdir_path = relative_path[len(self.subpath):].strip('/') + files.extend(self.list_files_recursive(subdir_path)) + else: + # It's a file + size_elem = prop.find('{DAV:}getcontentlength') + file_size = int(size_elem.text) if size_elem is not None else 0 + + file_path = relative_path + if self.subpath: + file_path = relative_path[len(self.subpath):].strip('/') + + files.append({ + 'path': file_path, + 'size': file_size, + 'full_path': relative_path + }) + + return files + + def read_journal(self): + """Read the migration journal to get progress and original limit""" + if not os.path.exists(self.journal_file): + return {} + + journal = {} + + with open(self.journal_file, 'r') as f: + lines = f.readlines() + + for line in lines: + line = line.strip() + if not line: + continue + parts = line.split(';', 1) + if len(parts) == 2: + status, path = parts + journal[path] = status + + return journal + + def update_journal(self, file_path: str, status: str) -> None: + """Update journal with file status""" + journal = self.read_journal() + journal[file_path] = status + + with open(self.journal_file, 'w') as f: + for path, stat in journal.items(): + f.write(f"{stat};{path}\n") + + def download_file(self, file_info: Dict[str, str | int]) -> Optional[str]: + """Download a single file from Nextcloud""" + webdav_url, share_token = self.get_webdav_url() + file_url = urljoin(webdav_url + "/", file_info['full_path']) + + # Local file path + local_path = os.path.join(self.temp_dir, os.path.basename(file_info['path'])) + + auth = (share_token, '') + + try: + logger.info(f"Downloading {file_info['path']} ({file_info['size']} bytes)") + response = self.session.get(file_url, auth=auth, stream=True) + response.raise_for_status() + + with open(local_path, 'wb') as f: + for chunk in response.iter_content(chunk_size=8192): + f.write(chunk) + + logger.info(f"Downloaded to {local_path}") + return local_path + + except requests.RequestException as e: + logger.error(f"Failed to download {file_info['path']}: {e}") + sys.exit(1) + + def sanitize_directory_label(self, directory_label: str) -> str: + """ + Sanitizes a directory label by replacing invalid characters defined in + the regular expression with a specified replacement character. + + :param directory_label: A string representing the directory label to sanitize. + :type directory_label: str + :return: A sanitized version of the directory label where invalid characters + are replaced by the specified character. + :rtype: str + """ + return self.invalid_dirlabel_regex.sub(self.invalid_dirlabel_replacement_char, directory_label) + + def upload_direct(self, local_file_path: str, file_info: Dict[str, str | int]) -> bool: + """Upload file directly to Dataverse using pyDataverse""" + try: + # Create datafile object + df = Datafile() + df.set({ + "pid": self.dataset_doi, + "filename": os.path.basename(file_info['path']), + }) + + # Add directory information if file is in subdirectory + if '/' in file_info['path']: + directory_path = '/'.join(file_info['path'].split('/')[:-1]) + + if self.invalid_dirlabel_regex.search(directory_path): + old_path = directory_path + directory_path = self.sanitize_directory_label(directory_path) + logger.warning(f"'{old_path}' contains invalid characters, sanitized to '{directory_path}'.") + + df.set({"directoryLabel": directory_path}) + + # If this is a ZIP-file and keeping them zipped was requested, double ZIP now. + if file_info['path'].lower().endswith('.zip') and self.keep_zips: + logger.info(f"Double-zipping {file_info['path']} to avoid unpacking by Dataverse") + original_file_path = local_file_path + local_file_path = "{name}.double.zip".format(name = os.path.basename(original_file_path)) + with zipfile.ZipFile(local_file_path, mode='w', compression=ZIP_STORED, compresslevel=None) as zf: + zf.write(original_file_path, arcname=os.path.basename(original_file_path)) + + # Upload file + logger.info(f"Uploading {file_info['path']} to Dataverse dataset {self.dataset_doi} (local file: {local_file_path})") + response = self.native_api.upload_datafile(self.dataset_doi, local_file_path, df.json()) + + if response.status_code == 200: + logger.info(f"Successfully uploaded {file_info['path']}") + return True + else: + # Check for file size limit error message + if "exceeds the size limit of" in response.json().get('message', ''): + logger.error(f"Upload failed for {file_info['path']}.") + match = re.search(r"exceeds the size limit of (.+ [KMGTPE]?B)", response.text) + current_limit = match.group(1) + self.print_curl_command_for_admin(current_limit, self.largest_file_size) + elif "file already exists" in response.json().get('message', '') and self.skip_existing: + logger.warning(f"File {file_info['path']} already exists in dataset, skipping upload as requested.") + return True + else: + logger.error(f"Upload failed for {file_info['path']}: {response.status_code} - {response.text}") + + return False + + except Exception as e: + logger.error(f"Upload failed for {file_info['path']}: {e}") + return False + + def cleanup_temp_file(self, file_path: str) -> None: + """Remove temporary downloaded file""" + try: + os.remove(file_path) + logger.debug(f"Removed temporary file {file_path}") + except OSError as e: + logger.warning(f"Could not remove temporary file {file_path}: {e}") + + def print_curl_command_for_admin(self, current_limit, required_limit): + """Print curl command for admin to increase upload limit""" + msg = "" + msg += "\n" + "="*80 + "\n" + msg += "ADMIN ACTION REQUIRED\n" + msg += "="*80 + "\n" + msg += f"The largest file ({humanize.naturalsize(required_limit, binary=True)}) exceeds the current upload limit of {current_limit}.\n" + msg += "Please run the following curl command as a Dataverse admin to temporarily increase the limit:\n" + msg += f"""curl -X PUT "{self.dataverse_url}/api/v1/admin/settings/:MaxFileUploadSizeInBytes" -d "{required_limit + 1024*1024}"\n""" + msg += "If you're the admin: note to add the ?unblock-key=... parameter when required.\n" + msg += f"This will set the limit to {humanize.naturalsize(required_limit + 1024*1024, binary=True)} (largest file size + 1MB).\n" + msg += "="*80 + "\n" + logger.error(msg) + + + def transfer(self): + """Main migration process""" + logger.info("Starting Nextcloud to Dataverse transfer") + + # Get list of all files + logger.info("Scanning Nextcloud share for files...") + files = self.list_files_recursive() + + if not files: + logger.info("No files found in the share") + return + + logger.info(f"Found {len(files)} files") + for file in files: + logger.debug(f"{file['full_path']} ({humanize.naturalsize(file['size'], binary=True)})") + + # Find largest file + self.largest_file_size = max(file['size'] for file in files) + logger.info(f"Largest file size: {self.largest_file_size} bytes ({humanize.naturalsize(self.largest_file_size, binary=True)})") + + # Read existing journal or create new one + journal = self.read_journal() + + # Process each file + for file_info in files: + file_path = file_info['path'] + + # Check journal status + status = journal.get(file_path, '') + + if status == 'U': + logger.info(f"Skipping {file_path} - already uploaded") + continue + + local_file_path = None + + try: + # Download if not already done + if status != 'D': + local_file_path = self.download_file(file_info) + self.update_journal(file_path, 'D') + else: + # File was downloaded before, find it + local_file_path = os.path.join(self.temp_dir, os.path.basename(file_path)) + if not os.path.exists(local_file_path): + logger.warning(f"Previously downloaded file {local_file_path} not found, re-downloading") + local_file_path = self.download_file(file_info) + self.update_journal(file_path, 'D') + + # Upload file + if self.upload_direct(local_file_path, file_info): + self.update_journal(file_path, 'U') + # Clean up temp file after successful upload + self.cleanup_temp_file(local_file_path) + else: + logger.error(f"Upload failed for {file_path}") + sys.exit(1) + + except Exception as e: + logger.error(f"Error processing {file_path}: {e}") + if local_file_path and os.path.exists(local_file_path): + self.cleanup_temp_file(local_file_path) + sys.exit(1) + + logger.info("Transfer completed successfully!") + logger.warning("\n" + "="*80 + "\n" + + "If changed, remember to restore the original upload limit now!\n" + + "="*80 + "\n") + +def main(): + parser = argparse.ArgumentParser(description='Transfer files from Nextcloud link share to Dataverse') + + # Nextcloud arguments + parser.add_argument('--share', required=False, + help='(Req.) Nextcloud public share URL (e.g., https://cloud.example.com/s/sHaReToKeN). Can be set as env var NEXTCLOUD_SHARE_URL.') + parser.add_argument('--subpath', default='', + help='(Opt.) Subpath within the Nextcloud share to start the file tree traversal from') + + # Dataverse arguments + parser.add_argument('--instance', required=False, + help='(Req.) Dataverse instance URL (e.g., https://demo.dataverse.org). Can be set as env var DATAVERSE_URL.') + parser.add_argument('--api-token', required=False, + help='(Req.) Dataverse API Token. Superadmin or other with permissions for dataset. Can be set as env var DATAVERSE_API_TOKEN.') + parser.add_argument('--dataset-doi', required=False, + help='(Req.) Target dataset DOI (e.g., doi:10.1234/5678). Can be set as env var DATASET_DOI.') + parser.add_argument('--skip-existing', required=False, action='store_true', + help='(Opt.) Skip files that have already been uploaded to the dataset (default: exit with error)') + parser.add_argument('--keep-zips', required=False, action='store_true', + help='(Opt.) If ZIP files are uploaded, double-ZIP them to avoid unpackaging by Dataverse' ) + + # Other arguments + parser.add_argument('--temp-dir', + help='Temporary directory for downloads (default: system temp)') + parser.add_argument('--journal-file', default='transfer_journal.txt', + help='Journal file to track progress (default: transfer_journal.txt)') + parser.add_argument('--verbose', action='store_true', + help='Enable verbose logging output') + parser.add_argument('--env-file', default='.env', + help='Path to .env file (default: .env in current directory)') + parser.add_argument('--invalid-directory-label-chars-regex', default=DEFAULT_INVALID_DIRLABEL_CHARS_REGEX, + help=f"Regex matching any invalid characters in a file's directoryLabel, based on Dataverse\'s FileDirectoryNameValidator (default: {DEFAULT_INVALID_DIRLABEL_CHARS_REGEX})") + parser.add_argument('--replace-invalid-chars-with', default=DEFAULT_INVALID_DIRLABEL_REPLACEMENT_CHAR, + help=f"Character to replace invalid characters in directory path with (default: {DEFAULT_INVALID_DIRLABEL_REPLACEMENT_CHAR})") + + args = parser.parse_args() + + # Set logging level based on verbose flag + if args.verbose: + logging.getLogger().setLevel(logging.DEBUG) + + # Load environment from .env file if present + if os.path.exists(args.env_file): + with open(args.env_file) as f: + for line in f: + if line.strip() and not line.startswith('#'): + key, value = line.strip().split('=', 1) + os.environ[key] = value + + # Check for environment variables as fallback + share_url = args.share or os.getenv('NEXTCLOUD_SHARE_URL') + dataverse_url = args.instance or os.getenv('DATAVERSE_URL') + api_token = args.api_token or os.getenv('DATAVERSE_API_TOKEN') + dataset_doi = args.dataset_doi or os.getenv('DATASET_DOI') + + # Validate required parameters + if not all([share_url, dataverse_url, api_token, dataset_doi]): + logger.error("Missing required parameters. 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+print_warning() { + echo -e "${YELLOW}[WARNING]${NC} $1" +} + +print_error() { + echo -e "${RED}[ERROR]${NC} $1" +} + +# Function to check if ImageMagick is available +check_imagemagick() { + if ! command -v magick >/dev/null 2>&1; then + print_warning "ImageMagick not found. Installing fallback method for images." + return 1 + fi + return 0 +} + +# Optimized function to generate random text content +generate_text_content() { + local lines=$1 + local words_per_line=${2:-10} + local target_size_mb=${3:-1} + + # Calculate total words needed + local total_words=$((lines * words_per_line)) + + # Pre-generate a large pool of random words to avoid repeated openssl calls + local word_pool_size=10000 + local word_pool=$(openssl rand -hex $((word_pool_size * 4)) | sed 's/\(..\)/\1 /g' | tr ' ' '\n' | head -n $word_pool_size) + + # Convert to array for faster access + local -a words_array + readarray -t words_array <<< "$word_pool" + local pool_size=${#words_array[@]} + + # Generate content more efficiently + local word_count=0 + local line_word_count=0 + + for ((i=1; i<=lines; i++)); do + line_word_count=0 + for ((j=1; j<=words_per_line; j++)); do + # Use modulo to cycle through word pool + local word_index=$((word_count % pool_size)) + printf "%s " "${words_array[$word_index]}" + ((word_count++)) + ((line_word_count++)) + done + echo "" + done +} + +# Alternative (fast) text generation using /dev/urandom and base64 +generate_text_content_fast() { + local target_size_mb=$1 + + # Generate random data and convert to readable text + dd if=/dev/urandom bs=1M count="${target_size_mb%.*}" 2>/dev/null | \ + base64 | \ + sed 's/./& /g' | \ + sed 's/[^a-zA-Z0-9 ]//g' | \ + fold -w 80 | \ + head -n $((target_size_mb * 1024 * 1024 / 77)) +} + +# Fast generation of CSV file lines (using 32k character notes) +generate_csv() { + local target_size_mb=$1 + local target_size_chars=$(($1 * 1024 * 1024)) + + echo "id,timestamp,value,category,description,notes" + + local base_timestamp=1000000000 + local char_count=0 + + # Use printf and bash arithmetic for speed + while [ $char_count -lt $((target_size_chars)) ]; do + local timestamp=$((base_timestamp + i * 60)) + local value=$((RANDOM * 1000 / 32767)) + local category=$((RANDOM % 10)) + local desc_num=$((RANDOM)) + local note128k=$(dd if=/dev/urandom bs=32K count=2 2>/dev/null | base64 | sed 's/./& /g' | sed 's/[^a-zA-Z0-9 ]//g' | cut -c -32768) + + local line=$(printf "%d,%s,%.2f,category_%d,desc_%x,%s\n" \ + "$i" \ + "$(date -d "@$timestamp" '+%Y-%m-%d %H:%M:%S')" \ + "$value" \ + "$category" \ + "$desc_num" \ + "$note128k") + char_count=$((char_count + ${#line})) + echo "$line" + + done +} + +# Function to create microscopy-style image +create_microscopy_image() { + local filepath="$1" + local width=${2:-2048} + local height=${3:-1536} + printf "\t - %s\n" "$filepath" + + # Create a base noisy image + magick -size "${width}x${height}" xc:black \ + \( +clone +noise Random \) \ + -compose Lighten -composite \ + \( +clone -blur 0x0.5 \) \ + -compose Multiply -composite \ + \( +clone -colorize 20,30,80 \) \ + -compose Screen -composite \ + -modulate 80,150,100 \ + "$filepath" +} + +# Function to create field photo-style image +create_field_photo() { + local filepath="$1" + local width=${2:-1920} + local height=${3:-1080} + printf "\t - %s\n" "$filepath" + + # Create a landscape-style image + magick -size $"{width}x${height}" \ + gradient:"#87CEEB-#228B22" \ + \( +clone +noise Random -blur 0x1 \) \ + -compose Multiply -composite \ + -modulate 90,120,110 \ + "$filepath" +} + +# Function to create scientific chart/diagram +create_scientific_chart() { + local filepath="$1" + local width=${2:-800} + local height=${3:-600} + printf "\t - %s\n" "$filepath" + + # Create a chart-like image with grid and data points + magick -size ${width}x${height} xc:white \ + \( -size ${width}x${height} xc:none -stroke gray -strokewidth 1 \ + -draw "line 50,50 50,$((height-50)) line 50,$((height-50)) $((width-50)),$((height-50))" \ + -draw "line 50,150 $((width-50)),150 line 50,250 $((width-50)),250 line 50,350 $((width-50)),350" \ + -draw "line 150,50 150,$((height-50)) line 250,50 250,$((height-50)) line 350,50 350,$((height-50))" \) \ + -compose Over -composite \ + \( +clone -fill red -stroke red -strokewidth 2 \ + -draw "circle 100,200 105,205 circle 200,180 205,185 circle 300,220 305,225 circle 400,160 405,165" \) \ + -compose Over -composite \ + "$filepath" +} + +# Function to create satellite-style image +create_satellite_image() { + local filepath="$1" + local width=${2:-4096} + local height=${3:-4096} + printf "\t - %s\n" "$filepath" + + # Create a large, complex satellite-style image + magick -size ${width}x${height} \ + plasma:fractal \ + -blur 0x2 \ + -modulate 70,200,120 \ + -colorize 0,20,40 \ + \( +clone +noise Random -blur 0x0.5 \) \ + -compose Multiply -composite \ + "$filepath" +} + +# Function to create spectrogram-style image +create_spectrogram() { + local filepath="$1" + local width=${2:-1024} + local height=${3:-768} + printf "\t - %s\n" "$filepath" + + # Create a spectrogram-like visualization + magick -size ${width}x${height} xc:black \ + +noise Random \ + -blur 0x1 \ + -normalize \ + -colorspace HSL \ + -channel Hue -evaluate set 60% \ + -channel Saturation -evaluate set 80% \ + -colorspace sRGB \ + "$filepath" +} + +# Function to create lab equipment photo +create_lab_photo() { + local filepath="$1" + local width=${2:-1280} + local height=${3:-960} + printf "\t - %s\n" "$filepath" + + # Create a lab-like environment image + magick -size ${width}x${height} \ + gradient:"#F5F5F5-#E0E0E0" \ + \( +clone +noise Gaussian -blur 0x0.5 \) \ + -compose Multiply -composite \ + \( -size 200x300 xc:"#C0C0C0" \) \ + -gravity Center -compose Over -composite \ + -modulate 95,80,105 \ + "$filepath" +} + +# Function to create a file of specific size (non-image) +create_file_with_size() { + local filepath="$1" + local size_mb="$2" + local file_type="$3" + printf "\t - %s\n" "$filepath" + + case "$file_type" in + "text") + generate_text_content_fast "$size_mb" > "$filepath" + ;; + "binary"|"archive") + # Use dd to create binary files + dd if=/dev/urandom of="$filepath" bs=1M count="$size_mb" 2>/dev/null + ;; + "csv") + # Use optimized CSV generation + generate_csv "$size_mb" > "$filepath" + ;; + *) + dd if=/dev/urandom of="$filepath" bs=1M count="$size_mb" 2>/dev/null + ;; + esac +} + +# Function to create directory structure +create_directories() { + print_status "Creating directory structure..." + + mkdir -p "$DATASET_DIR"/01_raw_data/{images,documents,archives,sensor_data} + mkdir -p "$DATASET_DIR"/02_processed_data/{cleaned,analyzed,transformed} + mkdir -p "$DATASET_DIR"/03_results/{figures,tables,reports} + mkdir -p "$DATASET_DIR"/04_code/{scripts,notebooks,utilities} + mkdir -p "$DATASET_DIR"/05_documentation/{readme,protocols,notes} + mkdir -p "$DATASET_DIR"/06_backup/{daily,weekly,monthly} +} + +# Function to generate research documents +generate_research_files() { + print_status "Generating research documents..." + + local docs_dir="$DATASET_DIR/01_raw_data/documents" + + # Research papers and notes + create_file_with_size "$docs_dir/literature_review.txt" 5 "text" + create_file_with_size "$docs_dir/methodology_notes.txt" 3 "text" + create_file_with_size "$docs_dir/experiment_log.txt" 8 "text" + create_file_with_size "$docs_dir/observations.txt" 12 "text" + + # Create some "PDF" files (binary) + create_file_with_size "$docs_dir/research_paper_draft.pdf" 15 "binary" + create_file_with_size "$docs_dir/conference_presentation.pdf" 25 "binary" + create_file_with_size "$docs_dir/grant_proposal.pdf" 8 "binary" +} + +# Function to generate image files using ImageMagick +generate_image_files() { + print_status "Generating image files..." + + local img_dir="$DATASET_DIR/01_raw_data/images" + + if check_imagemagick; then + print_status "Using ImageMagick to create realistic images..." + + # High-resolution microscopy images (TIFF format for scientific use) + print_status "Creating microscopy images..." + create_microscopy_image "$img_dir/microscopy_001.tiff" 2048 1536 + create_microscopy_image "$img_dir/microscopy_002.tiff" 2048 1536 + create_microscopy_image "$img_dir/microscopy_003.tiff" 1024 768 + + # Convert one to different bit depth for variety + magick "$img_dir/microscopy_003.tiff" -depth 16 "$img_dir/microscopy_003_16bit.tiff" + rm "$img_dir/microscopy_003.tiff" + + # Field photographs (JPEG format) + print_status "Creating field photos..." + create_field_photo "$img_dir/field_photo_001.jpg" 1920 1080 + create_field_photo "$img_dir/field_photo_002.jpg" 1280 960 + create_field_photo "$img_dir/field_site_panorama.jpg" 3840 1080 + + # Scientific diagrams and charts (PNG format for crisp graphics) + print_status "Creating scientific diagrams..." + create_scientific_chart "$img_dir/measurement_chart.png" 800 600 + create_scientific_chart "$img_dir/correlation_plot.png" 1024 768 + + # Spectrogram/analysis images + create_spectrogram "$img_dir/frequency_analysis.png" 1024 768 + create_spectrogram "$img_dir/signal_spectrogram.png" 2048 1024 + + # Large satellite/aerial imagery + print_status "Creating satellite imagery (this may take a moment)..." + create_satellite_image "$img_dir/satellite_overview.tiff" 4096 4096 + + # Lab equipment photos + create_lab_photo "$img_dir/lab_setup_001.jpg" 1280 960 + create_lab_photo "$img_dir/equipment_detail.jpg" 1920 1080 + + # Create some processed/analyzed versions + print_status "Creating processed image variants..." + magick "$img_dir/field_photo_001.jpg" -colorspace Gray "$img_dir/field_photo_001_grayscale.jpg" + magick "$img_dir/microscopy_001.tiff" -enhance -contrast-stretch 2%x98% "$img_dir/microscopy_001_enhanced.tiff" + + # Batch of smaller images (like time series) + for i in {1..5}; do + create_microscopy_image "$img_dir/timeseries_$(printf "%03d" $i).jpg" 512 384 + done + + else + print_warning "ImageMagick not available, creating binary image files..." + # Fallback to binary files with appropriate sizes + create_file_with_size "$img_dir/microscopy_001.tiff" 45 "binary" + create_file_with_size "$img_dir/microscopy_002.tiff" 52 "binary" + create_file_with_size "$img_dir/field_photo_001.jpg" 8 "binary" + create_file_with_size "$img_dir/field_photo_002.jpg" 12 "binary" + create_file_with_size "$img_dir/diagram_01.png" 3 "binary" + create_file_with_size "$img_dir/chart_analysis.png" 2 "binary" + create_file_with_size "$img_dir/satellite_image.tiff" 150 "binary" + create_file_with_size "$img_dir/lab_setup.jpg" 6 "binary" + fi +} + +# Function to generate data files +generate_data_files() { + print_status "Generating data files..." + + local sensor_dir="$DATASET_DIR/01_raw_data/sensor_data" + local processed_dir="$DATASET_DIR/02_processed_data" + + # Raw sensor data (CSV format) + create_file_with_size "$sensor_dir/temperature_readings.csv" 25 "csv" + create_file_with_size "$sensor_dir/pressure_data.csv" 18 "csv" + create_file_with_size "$sensor_dir/humidity_measurements.csv" 22 "csv" + create_file_with_size "$sensor_dir/gps_coordinates.csv" 12 "csv" + + # Large dataset files + create_file_with_size "$sensor_dir/continuous_monitoring.dat" 500 "binary" + create_file_with_size "$sensor_dir/high_frequency_data.bin" 750 "binary" + + # Processed data + create_file_with_size "$processed_dir/cleaned/filtered_temperature.csv" 15 "csv" + create_file_with_size "$processed_dir/analyzed/statistical_summary.txt" 2 "text" + create_file_with_size "$processed_dir/transformed/normalized_data.csv" 30 "csv" +} + +# Function to generate archive files +generate_archives() { + print_status "Generating archive files..." + + local archive_dir=$( realpath "$DATASET_DIR/01_raw_data/archives" ) + local backup_dir=$( realpath "$DATASET_DIR/06_backup" ) + + # Create some temporary files to archive + local temp_dir=$(mktemp -d) + create_file_with_size "$temp_dir/data1.txt" 10 "text" + create_file_with_size "$temp_dir/data2.txt" 15 "text" + create_file_with_size "$temp_dir/binary_data.bin" 20 "binary" + + # Create ZIP archives + (cd "$temp_dir" && zip -q "$archive_dir/experimental_data_batch1.zip" *) + + # Create larger archive files + create_file_with_size "$archive_dir/legacy_data.tar.gz" 200 "archive" + create_file_with_size "$backup_dir/daily/backup_$(date +%Y%m%d).zip" 180 "archive" + create_file_with_size "$backup_dir/weekly/weekly_backup.tar.gz" 450 "archive" + + # Large backup file (GB range) + create_file_with_size "$backup_dir/monthly/full_backup_$(date +%Y%m).tar.gz" $((1024 * 2)) "archive" + + # Cleanup + rm -rf "$temp_dir" +} + +# Function to generate code and script files +generate_code_files() { + print_status "Generating code files..." + + local code_dir="$DATASET_DIR/04_code" + + # Python scripts + cat > "$code_dir/scripts/data_analysis.py" << 'EOF' +#!/usr/bin/env python3 +""" +Data analysis script for research project +""" +import pandas as pd +import numpy as np +import matplotlib.pyplot as plt +from PIL import Image +import cv2 + +def load_data(filename): + """Load data from CSV file""" + return pd.read_csv(filename) + +def analyze_temperature(data): + """Analyze temperature patterns""" + stats = data['temperature'].describe() + return stats + +def process_microscopy_image(image_path): + """Process microscopy images for analysis""" + img = cv2.imread(image_path) + # Apply filters and enhancements + processed = cv2.GaussianBlur(img, (5, 5), 0) + return processed + +def create_visualization(data, output_path): + """Create data visualization""" + plt.figure(figsize=(10, 6)) + plt.plot(data['timestamp'], data['value']) + plt.title('Sensor Data Over Time') + plt.xlabel('Time') + plt.ylabel('Value') + plt.savefig(output_path) + plt.close() + +if __name__ == "__main__": + print("Starting data analysis...") + # Load sensor data + temp_data = load_data("../01_raw_data/sensor_data/temperature_readings.csv") + + # Analyze and save results + stats = analyze_temperature(temp_data) + print("Temperature statistics:", stats) + + # Create visualization + create_visualization(temp_data, "../03_results/figures/temperature_analysis.png") +EOF + + # R script with imaging focus + cat > "$code_dir/scripts/image_analysis.R" << 'EOF' +# Image and Statistical Analysis Script +# Research Project Data Analysis + +library(ggplot2) +library(dplyr) +library(imager) # For image processing + +# Load sensor data +data <- read.csv("../01_raw_data/sensor_data/temperature_readings.csv") + +# Basic statistics +summary(data) + +# Image analysis function +process_microscopy <- function(image_path) { + # Load and process microscopy image + img <- load.image(image_path) + + # Apply filters + filtered <- isoblur(img, sigma = 1) + + return(filtered) +} + +# Create plots +temp_plot <- ggplot(data, aes(x=timestamp, y=value)) + + geom_line(color="blue", size=1) + + geom_smooth(method="loess", color="red") + + labs(title="Temperature Measurements Over Time", + x="Time", y="Temperature (°C)") + + theme_minimal() + +ggsave("../03_results/figures/temperature_trend_analysis.png", temp_plot, + width=12, height=8, dpi=300) + +# Statistical analysis +correlation_analysis <- cor(data[,sapply(data, is.numeric)]) +write.csv(correlation_analysis, "../03_results/tables/correlation_matrix.csv") + +print("Analysis complete!") +EOF + + # Jupyter notebook (JSON format) + cat > "$code_dir/notebooks/image_processing_workflow.ipynb" << 'EOF' +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Image Processing and Analysis Workflow\n", + "Processing microscopy and field images for research analysis" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom PIL import Image\nimport cv2\nfrom skimage import filters, morphology\n\n# Image processing pipeline\ndef process_microscopy_batch(image_dir):\n \"\"\"Process a batch of microscopy images\"\"\"\n processed_images = []\n \n for image_file in os.listdir(image_dir):\n if image_file.endswith('.tiff'):\n img_path = os.path.join(image_dir, image_file)\n img = cv2.imread(img_path, cv2.IMREAD_GRAYSCALE)\n \n # Apply preprocessing\n enhanced = cv2.equalizeHist(img)\n denoised = cv2.bilateralFilter(enhanced, 9, 75, 75)\n \n processed_images.append(denoised)\n \n return processed_images\n\nprint('Image processing notebook loaded')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Load and Display Sample Images" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Load sample microscopy image\nimg_path = '../01_raw_data/images/microscopy_001.tiff'\nif os.path.exists(img_path):\n sample_img = Image.open(img_path)\n plt.figure(figsize=(10, 8))\n plt.imshow(sample_img, cmap='gray')\n plt.title('Sample Microscopy Image')\n plt.axis('off')\n plt.show()\nelse:\n print('Sample image not found')" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "name": "python", + "version": "3.8.0" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} +EOF + + # Shell script for batch processing + cat > "$code_dir/utilities/batch_process_images.sh" << 'EOF' +#!/bin/bash +# Batch image processing utility + +echo "Starting batch image processing..." + +IMAGE_DIR="../01_raw_data/images" +OUTPUT_DIR="../02_processed_data/images" + +# Create output directory +mkdir -p "$OUTPUT_DIR" + +# Process TIFF files (microscopy images) +echo "Processing microscopy images..." +for file in "$IMAGE_DIR"/*.tiff; do + if [[ -f "$file" ]]; then + filename=$(basename "$file" .tiff) + echo "Processing $filename..." + + # Example ImageMagick processing commands + if command -v magick >/dev/null 2>&1; then + # Enhance contrast and reduce noise + magick "$file" -enhance -noise 1 -normalize "$OUTPUT_DIR/${filename}_processed.tiff" + + # Create thumbnail + magick "$file" -resize 256x256 "$OUTPUT_DIR/${filename}_thumb.jpg" + fi + fi +done + +# Process JPEG files (field photos) +echo "Processing field photos..." +for file in "$IMAGE_DIR"/*.jpg; do + if [[ -f "$file" ]]; then + filename=$(basename "$file" .jpg) + echo "Processing $filename..." + + if command -v magick >/dev/null 2>&1; then + # Auto-level and sharpen + magick "$file" -auto-level -unsharp 0x1 "$OUTPUT_DIR/${filename}_enhanced.jpg" + fi + fi +done + +echo "Batch processing complete!" +echo "Processed images saved to: $OUTPUT_DIR" +EOF + + chmod +x "$code_dir/utilities/batch_process_images.sh" +} + +# Function to generate documentation +generate_documentation() { + print_status "Generating documentation..." + + local doc_dir="$DATASET_DIR/05_documentation" + + # README file + cat > "$doc_dir/readme/README.md" << EOF +# Research Dataset + +Generated on: $(date) +Generated with: ImageMagick $(command -v magick >/dev/null 2>&1 && magick -version | head -1 || echo "Not available") + +## Overview +This dataset contains research data collected for [Project Name] study, including high-resolution microscopy images, field photographs, sensor data, and analysis results. + +## Directory Structure +- \`01_raw_data/\` - Original, unprocessed data + - \`images/\` - Microscopy images (TIFF), field photos (JPEG), diagrams (PNG) + - \`sensor_data/\` - CSV files with measurement data + - \`documents/\` - Research documents and papers + - \`archives/\` - Compressed historical data +- \`02_processed_data/\` - Cleaned and processed data +- \`03_results/\` - Analysis results and outputs +- \`04_code/\` - Analysis scripts and code +- \`05_documentation/\` - Project documentation +- \`06_backup/\` - Backup files + +## Image Data Details +### Microscopy Images +- Format: TIFF (16-bit and 8-bit) +- Resolution: 2048x1536 pixels (high-res), 1024x768 (standard) +- Content: Simulated microscopic structures with realistic noise patterns + +### Field Photography +- Format: JPEG +- Resolution: 1920x1080, 1280x960 +- Content: Landscape-style field site documentation + +### Scientific Diagrams +- Format: PNG +- Resolution: 800x600, 1024x768 +- Content: Charts, plots, and measurement visualizations + +### Satellite Imagery +- Format: TIFF +- Resolution: 4096x4096 pixels +- Content: Large-scale terrain simulation + +## File Sizes +- Total dataset size: ~4-6 GB +- Microscopy images: 5-50 MB each +- Field photos: 2-15 MB each +- Satellite imagery: 100-200 MB +- Sensor data files: 10-500 MB + +## Processing Workflow +1. Raw images in \`01_raw_data/images/\` +2. Batch processing scripts in \`04_code/utilities/\` +3. Processed results in \`02_processed_data/\` +4. Analysis notebooks in \`04_code/notebooks/\` + +## Usage Examples +\`\`\`bash +# Batch process images +cd 04_code/utilities +./batch_process_images.sh + +# Run data analysis +cd 04_code/scripts +python3 data_analysis.py + +# R statistical analysis +Rscript image_analysis.R +\`\`\` + +## Software Requirements +- ImageMagick (for image processing) +- Python 3.x with PIL, OpenCV, scikit-image +- R with ggplot2, dplyr, imager packages + +## Contact +[Researcher Name] - [email] +EOF + + # Image processing protocol + cat > "$doc_dir/protocols/image_processing_protocol.md" << 'EOF' +# Image Processing Protocol + +## Equipment and Setup +- High-resolution microscope with TIFF output capability +- Field camera with GPS tagging +- Consistent lighting conditions for lab photography + +## Image Acquisition Standards +### Microscopy Images +1. **Resolution**: Minimum 1024x768, preferred 2048x1536 +2. **Format**: TIFF (uncompressed) for analysis, JPEG for documentation +3. **Bit Depth**: 16-bit for quantitative analysis, 8-bit for visualization +4. **Naming Convention**: `microscopy_XXX.tiff` where XXX is sequential number + +### Field Photography +1. **Resolution**: 1920x1080 minimum +2. **Format**: JPEG with maximum quality setting +3. **Metadata**: Include GPS coordinates and timestamp +4. **Naming Convention**: `field_photo_XXX.jpg` or `site_location_YYYYMMDD.jpg` + +## Processing Pipeline +1. **Quality Check**: Verify image integrity and metadata +2. **Preprocessing**: + - Noise reduction (bilateral filter) + - Contrast enhancement (histogram equalization) + - Normalization for batch processing +3. **Analysis Preparation**: + - Convert to appropriate color space + - Create analysis masks if needed + - Generate thumbnails for quick review + +## Quality Control +- Visual inspection of all processed images +- Verify processing parameters are consistent +- Document any anomalies or processing issues +- Maintain original files alongside processed versions + +## Archive and Backup +- Raw images: Long-term storage with metadata +- Processed images: Working directory with version control +- Regular backup verification +EOF + + # Research notes + create_file_with_size "$doc_dir/notes/image_analysis_notes.txt" 15 "text" + create_file_with_size "$doc_dir/notes/field_work_log.txt" 20 "text" +} + +# Function to create result files (including processed images) +generate_results() { + print_status "Generating result files..." + + local results_dir="$DATASET_DIR/03_results" + + if check_imagemagick; then + # Generate result visualizations + print_status "Creating result visualizations..." + + # Scientific plots and charts + create_scientific_chart "$results_dir/figures/temperature_correlation.png" 1024 768 + create_scientific_chart "$results_dir/figures/statistical_summary.png" 800 600 + create_spectrogram "$results_dir/figures/frequency_domain_analysis.png" 1200 800 + + # Create a comparison figure (before/after style) + magick -size 1200x400 xc:white \ + \( -size 580x380 gradient:"#FF0000-#00FF00" \) -geometry +10+10 -composite \ + \( -size 580x380 gradient:"#0000FF-#FFFF00" \) -geometry +610+10 -composite \ + -font Arial -pointsize 24 -fill black \ + -annotate +250+50 "Before" -annotate +850+50 "After" \ + "$results_dir/figures/processing_comparison.png" + + else + # Fallback to binary files + create_file_with_size "$results_dir/figures/temperature_trend.png" 3 "binary" + create_file_with_size "$results_dir/figures/correlation_matrix.png" 4 "binary" + create_file_with_size "$results_dir/figures/spatial_distribution.png" 8 "binary" + fi + + # Tables and reports + create_file_with_size "$results_dir/tables/summary_statistics.csv" 1 "csv" + create_file_with_size "$results_dir/tables/image_analysis_results.csv" 3 "csv" + create_file_with_size "$results_dir/reports/monthly_report.pdf" 12 "binary" + create_file_with_size "$results_dir/reports/image_processing_report.pdf" 18 "binary" + create_file_with_size "$results_dir/reports/final_analysis.docx" 8 "binary" +} + +# Function to display dataset summary +display_summary() { + print_success "Dataset generation complete!" + echo + print_status "Dataset Summary:" + echo "=================" + + if command -v du >/dev/null 2>&1; then + echo "Total size: $(du -hs "$DATASET_DIR" | cut -f1)" + echo + echo "Directory sizes:" + du -hs "$DATASET_DIR"/*/ | sort -hr + echo + echo "File count by type:" + find "$DATASET_DIR" -type f -name "*.txt" | wc -l | xargs echo "Text files:" + find "$DATASET_DIR" -type f -name "*.csv" | wc -l | xargs echo "CSV files:" + find "$DATASET_DIR" -type f -name "*.jpg" -o -name "*.png" -o -name "*.tiff" | wc -l | xargs echo "Image files:" + find "$DATASET_DIR" -type f -name "*.zip" -o -name "*.tar.gz" | wc -l | xargs echo "Archive files:" + find "$DATASET_DIR" -type f -name "*.py" -o -name "*.R" -o -name "*.sh" -o -name "*.ipynb" | wc -l | xargs echo "Code files:" + + echo + if check_imagemagick; then + print_success "✓ Real images generated with ImageMagick" + echo "Image formats created:" + find "$DATASET_DIR" -name "*.tiff" | wc -l | xargs echo " TIFF files (microscopy):" + find "$DATASET_DIR" -name "*.jpg" | wc -l | xargs echo " JPEG files (photography):" + find "$DATASET_DIR" -name "*.png" | wc -l | xargs echo " PNG files (diagrams):" + else + print_warning "⚠ ImageMagick not available - binary image files created instead" + fi + fi + + echo + print_status "Dataset location: $(pwd)/$DATASET_DIR" + print_status "Sample commands to explore:" + echo " ls -la $DATASET_DIR/01_raw_data/images/" + if check_imagemagick; then + echo " identify $DATASET_DIR/01_raw_data/images/microscopy_001.tiff" + echo " display $DATASET_DIR/01_raw_data/images/field_photo_001.jpg" + fi + echo " head -10 $DATASET_DIR/01_raw_data/sensor_data/temperature_readings.csv" + + print_success "Ready for research!" +} + +# Main execution +main() { + print_status "Starting research dataset generation with ImageMagick support..." + echo + + # Check for required tools + if ! command -v openssl >/dev/null 2>&1; then + print_error "openssl is required but not installed. Please install it first." + exit 1 + fi + + # Check ImageMagick availability + if check_imagemagick; then + print_success "ImageMagick detected - will generate real images!" + else + print_warning "ImageMagick not detected. To install on Ubuntu/Debian: sudo apt-get install imagemagick" + print_warning "Will create binary files instead of real images." + fi + echo + + # Create the dataset + create_directories + generate_research_files + generate_image_files + generate_data_files + generate_archives + generate_code_files + generate_documentation + generate_results + + # Show summary + display_summary +} + +# Run the script +main "$@"