h-mayorquin

"""
TIFF file stubber - Creates a stub of a TIFF file with only the first n pages.
Preserves all metadata, tags, and structure of the original pages.
"""

from pathlib import Path
import tifffile
import numpy as np

h-mayorquin

import h5py
import numpy as np
from typing import Optional
from scipy.sparse import csc_matrix
from pathlib import Path


def stub_caiman_hdf5(input_file: str, output_file: Optional[str] = None, n_timestamps: int = 10, n_units: Optional[int] = None, stub_one_photon_quantities: bool = True):
    """
    Create a stubbed version of a CaImAn HDF5 file with reduced units and timestamps.

h-mayorquin

%%{ init: {
      'theme':'base',
      'themeVariables': {
        'background': '#a7d2eb',          /* light backdrop */
        'lineColor' : '#09205A',          /* navy outlines / arrows */
        'primaryColor'  : '#005CA9',      /* dark blue */
        'secondaryColor': '#238FD6',      /* light blue */
        'tertiaryColor' : '#F57C00'       /* orange accent */
      }

h-mayorquin

import hdf5plugin
import h5py
import numpy as np
from hdmf.backends.hdf5.h5_utils import H5DataIO
from pynwb.testing.mock.file import mock_NWBFile
from pathlib import Path
from pynwb import NWBHDF5IO
from pynwb.file import TimeSeries
from neuroconv.tools.nwb_helpers import AVAILABLE_HDF5_COMPRESSION_METHODS

h-mayorquin

from pathlib import Path
import h5py
import numpy as np


# ────────────────────────────────────────────────────────────────────────────
def copy_group(
    src_group,
    dst_group,
    stub_frames: int,

h-mayorquin

#!/usr/bin/env python3
"""
stub_scan_image_file.py
──────────────────────────────────────────────────────────────────────────────
Functions for creating stub ScanImage TIFF files with modified metadata.
"""

import re
import shutil
import struct

h-mayorquin

from pathlib import Path
from pydub import AudioSegment
import numpy as np
import scipy.io.wavfile as wav

# Create output directory
output_dir = Path("audio_test_files")
output_dir.mkdir(exist_ok=True)

# Define output filenames with realistic names

h-mayorquin

def stub_ome_dataset(file_path, num_timepoints=3, output_dir=None):
    """
    Create a stubbed version of an OME-TIFF dataset based on a file path.
    
    Parameters:
    -----------
    file_path : str or Path
        Path to any TIFF file in the dataset
    num_timepoints : int, optional
        Number of timepoints to keep in the stub, default is 3

h-mayorquin

from pathlib import Path
import numpy as np
import shutil
from typing import Union, Optional, Tuple

def get_memmap_shape(filename: Union[str, Path], 
                     dtype: Union[str, np.dtype], 
                     num_channels: Optional[int] = None, 
                     offset: int = 0) -> Tuple[int, ...]:
    """Calculate the shape of a memory-mapped binary file.

h-mayorquin

from hdmf.data_utils import AbstractDataChunkIterator, DataChunk
import numpy as np
from PIL import Image
from pathlib import Path
from hdmf.backends.hdf5.h5_utils import H5DataIO


def generate_random_images(num_images, width=256, height=256, mode='RGB', seed=None, 
                         output_dir="generated_images", format='PNG'):
    """