import numpy as np
from medical.viewer import PatientViewer

# Create viewer with numpy arrays
volume = np.random.rand(256, 256, 100)
mask = np.random.randint(0, 2, (256, 256, 100))

viewer = PatientViewer(volume=volume, mask=mask)

from medical.viewer import PatientViewer

# Load from DICOM directory
viewer = PatientViewer(volume="/path/to/dicom_folder")

# Load from NRRD file
viewer = PatientViewer(volume="/path/to/scan.nrrd")

# Load from NIfTI file
viewer = PatientViewer(volume="/path/to/brain.nii.gz")

# Load from NumPy files
viewer = PatientViewer(
    volume="/path/to/volume.npy",
    mask="/path/to/mask.npy"
)

from medical.viewer import PatientViewer

# Provide labels for mask values
viewer = PatientViewer(
    volume="/path/to/scan.nrrd",
    mask="/path/to/segmentation.npy",
    class_names=["tumor", "edema", "necrosis"]
)

# Or use a dictionary mapping names to values
viewer = PatientViewer(
    volume=volume,
    mask=mask,
    class_names={"background": 0, "liver": 1, "tumor": 2}
)

from medical.viewer import PatientViewer, ViewerParameters

params = ViewerParameters(
    projection="axial",      # Initial view: "axial", "sagittal", or "coronal"
    window="Soft",           # Window preset: "Soft", "Lung", "Brain", "Bone", "Mask"
    flip_on=False,           # Flip the view
    contour=True,            # Show contour lines on masks
    alpha=0.3,               # Mask overlay transparency (0.0 - 1.0)
    color_map=True,          # Show color legend for classes
    clip=(-100, 300),        # Custom intensity clipping range
    z=50,                    # Initial slice index
    slice_bbox=False,        # Show bounding box for current slice
    mask_bbox=True,          # Show bounding box around mask
    component_bbox=False,    # Show per-component bounding boxes
    image_format="jpeg",     # Output format: "jpeg" or "png"
    jpeg_quality=95,         # JPEG quality (1-100)
)

viewer = PatientViewer(
    volume="/path/to/scan.nrrd",
    mask="/path/to/mask.npy",
    params=params
)

from medical.io import read_volume

# Read volume as numpy array
volume = read_volume("/path/to/dicom_folder")
volume = read_volume("/path/to/scan.nrrd")
volume = read_volume("/path/to/data.npy")
volume = read_volume("/path/to/data.npz", npz_key="arr_0")