### Install pynrrd from GitHub (Bash)

Source: https://pynrrd.readthedocs.io/en/stable/_sources/index

Installs the pynrrd library directly from its GitHub repository using pip. This is useful for installing the latest development version.

```bash
pip install git+https://github.com/mhe/pynrrd.git
```

--------------------------------

### Install pynrrd via Pip (Bash)

Source: https://pynrrd.readthedocs.io/en/stable/_sources/index

Installs the pynrrd library using pip from the Python Package Index (PyPI). This is the recommended installation method.

```bash
pip install pynrrd
```

--------------------------------

### Write and Read NRRD with Custom Fields using pynrrd

Source: https://pynrrd.readthedocs.io/en/stable/_sources/examples

Demonstrates writing and reading NRRD files that include custom header fields. This example shows how to define custom fields and their types for both writing and reading. Requires the numpy and nrrd libraries.

```python
import numpy as np
import nrrd

data = np.linspace(1, 60, 60).reshape((3, 10, 2))
header = {'kinds': ['domain', 'domain', 'domain'], 'units': ['mm', 'mm', 'mm'], 'spacings': [1.0458, 1.0458, 2.5], 'space': 'right-anterior-superior', 'space directions': np.array([[1, 0, 0], [0, 1, 0], [0, 0, 1]]), 'encoding': 'ASCII', 'custom_field_here1': 24.34, 'custom_field_here2': np.array([1, 2, 3, 4])}
custom_field_map = {'custom_field_here1': 'double', 'custom_field_here2': 'int list'}

nrrd.write('output.nrrd', data, header, custom_field_map=custom_field_map)

data2, header2 = nrrd.read('output.nrrd', custom_field_map)

print(np.all(data == data2))
>>> True

print(header)
>>> {'units': ['mm', 'mm', 'mm'], 'spacings': [1.0458, 1.0458, 2.5], 'custom_field_here1': 24.34, 'space': 'right-anterior-superior', 'space directions': array([[1, 0, 0],
       [0, 1, 0],
       [0, 0, 1]]), 'type': 'double', 'encoding': 'ASCII', 'kinds': ['domain', 'domain', 'domain'], 'dimension': 3, 'custom_field_here2': array([1, 2, 3, 4]), 'sizes': [3, 10, 2]}

print(header2)
>>> OrderedDict([('type', 'double'), ('dimension', 3), ('space', 'right-anterior-superior'), ('sizes', array([ 3, 10,  2])), ('space directions', array([[1., 0., 0.],
       [0., 1., 0.],
       [0., 0., 1.]])), ('kinds', ['domain', 'domain', 'domain']), ('encoding', 'ASCII'), ('spacings', array([1.0458, 1.0458, 2.5   ])), ('units', ['mm', 'mm', 'mm']), ('custom_field_here1', 24.34), ('custom_field_here2', array([1, 2, 3, 4]))])
```

--------------------------------

### Read NRRD Header Only with pynrrd

Source: https://pynrrd.readthedocs.io/en/stable/_sources/examples

Shows how to read only the header information from an NRRD file without loading the actual data. This is useful when you only need metadata. Requires the numpy and nrrd libraries.

```python
import numpy as np
import nrrd

data = np.linspace(1, 50, 50)
nrrd.write('output.nrrd', data)

header = nrrd.read_header('output.nrrd')
print(header)
>>> OrderedDict([('type', 'double'), ('dimension', 1), ('sizes', array([50])), ('endian', 'little'), ('encoding', 'gzip')])
```

--------------------------------

### Read and Write NRRD with C-order Indexing using pynrrd

Source: https://pynrrd.readthedocs.io/en/stable/examples

Explains and demonstrates how to handle C-order (row-major) indexing when writing and reading NRRD files with pynrrd. It shows how to specify the index order during writing and how to interpret the 'sizes' field in the header which will always be in Fortran-order. Requires numpy and nrrd.

```python
import numpy as np
import nrrd

# Treat this data array as a 3D volume using C-order indexing
# This means we have a volume with a shape of 600x800x70 (x by y by z)
data = np.zeros((70, 800, 600)) # Shape is (z, y, x) for C-order
# Save the NRRD object with the correct index order
nrrd.write('output.nrrd', data, index_order='C')

# Read the NRRD file with C-order indexing
# Note: We can specify either index order here, this is just a preference unlike in nrrd.write where
# it MUST be set based on the data setup
data, header = nrrd.read('output.nrrd', index_order='C')

# The data shape is exactly the same shape as what we wrote
print(data.shape)
>>> (70, 800, 600)

# But the shape saved in the header is in Fortran-order
print(header['sizes'])
>>> [600 800  70]

# Read the NRRD file with Fortran-order indexing now
data, header = nrrd.read('output.nrrd', index_order='F')

# The data shape is now in Fortran order, or transposed from what we wrote
print(data.shape)
>>> (600, 800, 70)
print(header['sizes'])
>>> [600 800  70]

```

--------------------------------

### Read and Write NRRD from Memory with pynrrd

Source: https://pynrrd.readthedocs.io/en/stable/_sources/examples

Illustrates how to write NRRD data to an in-memory byte stream (io.BytesIO) and read it back. This avoids creating temporary files on disk. Requires the io, numpy, and nrrd libraries.

```python
import io
import numpy as np
import nrrd

memory_nrrd = io.BytesIO()

data = np.linspace(1, 50, 50)
nrrd.write(memory_nrrd, data)

memory_nrrd.seek(0)

header = nrrd.read_header(memory_nrrd)

print(header)
>>> OrderedDict([('type', 'double'), ('dimension', 1), ('sizes', array([50])), ('endian', 'little'), ('encoding', 'gzip')])

data2 = nrrd.read_data(header, memory_nrrd)

print(np.all(data == data2))
>>> True
```

--------------------------------

### Quick Start: Read and Write NRRD Files (Python)

Source: https://pynrrd.readthedocs.io/en/stable/_sources/index

Demonstrates the basic usage of the pynrrd library to write a numpy array to an NRRD file and then read it back. It shows how to import the library, create sample data, and use the `write` and `read` functions.

```python
import numpy as np
import nrrd

# Some sample numpy data
data = np.zeros((5, 4, 3, 2))
filename = 'testdata.nrrd'

# Write to a NRRD file
nrrd.write(filename, data)

# Read the data back from file
readdata, header = nrrd.read(filename)
print(readdata.shape)
print(header)
```

--------------------------------

### Write and Read NRRD Data with pynrrd

Source: https://pynrrd.readthedocs.io/en/stable/examples

Demonstrates the basic workflow of writing a NumPy array to an NRRD file and then reading it back. It verifies that the read data matches the original data and prints the header information. Dependencies include numpy and nrrd.

```python
import numpy as np
import nrrd

data = np.linspace(1, 50, 50)
nrrd.write('output.nrrd', data)

data2, header = nrrd.read('output.nrrd')
print(np.all(data == data2))
>>> True

print(header)
>>> OrderedDict([('type', 'double'), ('dimension', 1), ('sizes', array([50])), ('endian', 'little'), ('encoding', 'gzip')])

```

--------------------------------

### Write and Read NRRD File with pynrrd

Source: https://pynrrd.readthedocs.io/en/stable/_sources/examples

Demonstrates the basic workflow of writing a NumPy array to an NRRD file and then reading it back. It verifies that the data read matches the original data and prints the header information. Requires the numpy and nrrd libraries.

```python
import numpy as np
import nrrd

data = np.linspace(1, 50, 50)
nrrd.write('output.nrrd', data)

data2, header = nrrd.read('output.nrrd')
print(np.all(data == data2))
>>> True

print(header)
>>> OrderedDict([('type', 'double'), ('dimension', 1), ('sizes', array([50])), ('endian', 'little'), ('encoding', 'gzip')])
```

--------------------------------

### NRRD Read/Write with C-order Indexing using pynrrd

Source: https://pynrrd.readthedocs.io/en/stable/_sources/examples

Explains and demonstrates how to specify C-order indexing when writing NRRD files with pynrrd. It also shows how to read the file specifying either C-order or Fortran-order indexing, highlighting the effect on data shape and header sizes. Requires the numpy and nrrd libraries.

```python
import numpy as np
import nrrd

# Treat this data array as a 3D volume using C-order indexing
# This means we have a volume with a shape of 600x800x70 (x by y by z)
data = np.zeros((70, 800, 600))
# Save the NRRD object with the correct index order
nrrd.write('output.nrrd', data, index_order='C')

# Read the NRRD file with C-order indexing
# Note: We can specify either index order here, this is just a preference unlike in nrrd.write where
# it MUST be set based on the data setup
data, header = nrrd.read('output.nrrd', index_order='C')

# The data shape is exactly the same shape as what we wrote
print(data.shape)
>>> (70, 800, 600)

# But the shape saved in the header is in Fortran-order
print(header['sizes'])
>>> [600 800  70]

# Read the NRRD file with Fortran-order indexing now
data, header = nrrd.read('output.nrrd', index_order='F')

# The data shape is exactly the same shape as what we wrote
# The data shape is now in Fortran order, or transposed from what we wrote
print(data.shape)
>>> (600, 800, 70)
```

--------------------------------

### Access NRRD Header Sizes in Python

Source: https://pynrrd.readthedocs.io/en/stable/_sources/examples

Demonstrates how to access the 'sizes' field from a NRRD header dictionary in Python. This typically represents the dimensions of the NRRD data. No external dependencies are required beyond the pynrrd library.

```python
print(header['sizes'])
>>> [600 800  70]
```

--------------------------------

### Write and Read NRRD with Custom Fields using pynrrd

Source: https://pynrrd.readthedocs.io/en/stable/examples

Demonstrates how to write NRRD files with custom header fields and associated type mappings, and then read them back, preserving the custom data. This allows for extended metadata storage. Dependencies include numpy and nrrd.

```python
import numpy as np
import nrrd

data = np.linspace(1, 60, 60).reshape((3, 10, 2))
header = {'kinds': ['domain', 'domain', 'domain'], 'units': ['mm', 'mm', 'mm'], 'spacings': [1.0458, 1.0458, 2.5], 'space': 'right-anterior-superior', 'space directions': np.array([[1, 0, 0], [0, 1, 0], [0, 0, 1]]), 'encoding': 'ASCII', 'custom_field_here1': 24.34, 'custom_field_here2': np.array([1, 2, 3, 4])}
custom_field_map = {'custom_field_here1': 'double', 'custom_field_here2': 'int list'}

nrrd.write('output.nrrd', data, header, custom_field_map=custom_field_map)

data2, header2 = nrrd.read('output.nrrd', custom_field_map)

print(np.all(data == data2))
>>> True

print(header)
>>> {'units': ['mm', 'mm', 'mm'], 'spacings': [1.0458, 1.0458, 2.5], 'custom_field_here1': 24.34, 'space': 'right-anterior-superior', 'space directions': array([[1, 0, 0],
   [0, 1, 0],
   [0, 0, 1]]), 'type': 'double', 'encoding': 'ASCII', 'kinds': ['domain', 'domain', 'domain'], 'dimension': 3, 'custom_field_here2': array([1, 2, 3, 4]), 'sizes': [3, 10, 2]}

print(header2)
>>> OrderedDict([('type', 'double'), ('dimension', 3), ('space', 'right-anterior-superior'), ('sizes', array([ 3, 10,  2])), ('space directions', array([[1., 0., 0.],
   [0., 1., 0.],
   [0., 0., 1.]])), ('kinds', ['domain', 'domain', 'domain']), ('encoding', 'ASCII'), ('spacings', array([1.0458, 1.0458, 2.5   ])), ('units', ['mm', 'mm', 'mm']), ('custom_field_here1', 24.34), ('custom_field_here2', array([1, 2, 3, 4]))])

```

--------------------------------

### Handle Duplicated Header Fields in NRRD with pynrrd

Source: https://pynrrd.readthedocs.io/en/stable/_sources/examples

Shows how to configure pynrrd to allow reading NRRD files that contain duplicated header fields. By setting `nrrd.reader.ALLOW_DUPLICATE_FIELD = True`, warnings are issued instead of errors. Requires the nrrd library.

```python
import nrrd

# Set this field to True to enable the reading of files with duplicated header fields
nrrd.reader.ALLOW_DUPLICATE_FIELD = True

# Name of the file you want to read with a duplicated header field
filename = "filename.nrrd"

# Read the file
# filedata = numpy array
# fileheader = header of the NRRD file
# A warning is now received about duplicate headers rather than an error being thrown
filedata, fileheader = nrrd.read(filename)
>>> UserWarning: Duplicate header field: 'space' warnings.warn(dup_message)
```

--------------------------------

### Read NRRD Header Only with pynrrd

Source: https://pynrrd.readthedocs.io/en/stable/examples

Shows how to read only the header information from an NRRD file without loading the actual data. This is useful for inspecting metadata or checking file structure. Requires numpy and nrrd libraries.

```python
import numpy as np
import nrrd

data = np.linspace(1, 50, 50)
nrrd.write('output.nrrd', data)

header = nrrd.read_header('output.nrrd')
print(header)
>>> OrderedDict([('type', 'double'), ('dimension', 1), ('sizes', array([50])), ('endian', 'little'), ('encoding', 'gzip')])

```

--------------------------------

### Quick Start: Reading and Writing NRRD Files with pynrrd

Source: https://pynrrd.readthedocs.io/en/stable/index

This Python code snippet demonstrates the basic usage of the pynrrd library. It shows how to create sample numpy data, write it to a NRRD file, and then read it back, printing the shape of the data and the header information. Dependencies include numpy.

```python
import numpy as np
import nrrd

# Some sample numpy data
data = np.zeros((5, 4, 3, 2))
filename = 'testdata.nrrd'

# Write to a NRRD file
nrrd.write(filename, data)

# Read the data back from file
readdata, header = nrrd.read(filename)
print(readdata.shape)
print(header)

```

--------------------------------

### Write and Read NRRD Data from Memory with pynrrd

Source: https://pynrrd.readthedocs.io/en/stable/examples

Illustrates writing NRRD data to an in-memory byte stream (io.BytesIO) and then reading it back. This is useful for scenarios where temporary NRRD data does not need to be persisted to disk. It requires the io, numpy, and nrrd libraries.

```python
import io
import numpy as np
import nrrd

memory_nrrd = io.BytesIO()

data = np.linspace(1, 50, 50)
nrrd.write(memory_nrrd, data)

memory_nrrd.seek(0)

header = nrrd.read_header(memory_nrrd)

print(header)
>>> OrderedDict([('type', 'double'), ('dimension', 1), ('sizes', array([50])), ('endian', 'little'), ('encoding', 'gzip')])

data2 = nrrd.read_data(header, memory_nrrd)

print(np.all(data == data2))
>>> True

```

--------------------------------

### Handle Duplicate Header Fields when Reading NRRD with pynrrd

Source: https://pynrrd.readthedocs.io/en/stable/examples

Shows how to enable the reading of NRRD files that contain duplicate header fields, which would normally raise an error. By setting `nrrd.reader.ALLOW_DUPLICATE_FIELD = True`, a UserWarning is issued instead of an error, allowing processing to continue. Requires the nrrd library.

```python
import nrrd

# Set this field to True to enable the reading of files with duplicated header fields
nrrd.reader.ALLOW_DUPLICATE_FIELD = True

# Name of the file you want to read with a duplicated header field
filename = "filename.nrrd"

# Read the file
# filedata = numpy array
# fileheader = header of the NRRD file
# A warning is now received about duplicate headers rather than an error being thrown
filedata, fileheader = nrrd.read(filename)
>>> UserWarning: Duplicate header field: 'space' warnings.warn(dup_message)

```

--------------------------------

### Validate NRRD Magic Line

Source: https://pynrrd.readthedocs.io/en/stable/_modules/nrrd/reader

Validates the initial 'NRRD' magic line of an NRRD file and extracts the version number. It ensures the file starts with 'NRRD' and handles version checks, raising errors for unsupported versions or invalid formats. This function is crucial for identifying NRRD files and their compatibility.

```python
def _validate_magic_line(line: str) -> int:
    """For NRRD files, the first four characters are always "NRRD", and
    remaining characters give information about the file format version

    >>> _validate_magic_line('NRRD0005')
    8
    >>> _validate_magic_line('NRRD0006')
    Traceback (most recent call last):
        ...
    NrrdError: NRRD file version too new for this library.
    >>> _validate_magic_line('NRRD')
    Traceback (most recent call last):
        ...
    NrrdError: Invalid NRRD magic line: NRRD
    """

    if not line.startswith('NRRD'):
        raise NRRDError('Invalid NRRD magic line. Is this an NRRD file?')

    try:
        version = int(line[4:])
        if version > 5:
            raise NRRDError(f'Unsupported NRRD file version (version: {version}). This library only supports v5 '
                          'and below.')
    except ValueError:
        raise NRRDError(f'Invalid NRRD magic line: {line}')

    return len(line)
```

--------------------------------

### Import necessary modules for nrrd.reader

Source: https://pynrrd.readthedocs.io/en/stable/_modules/nrrd/reader

Imports required modules for reading NRRD files, including compression libraries, I/O utilities, regular expressions, command-line parsing, warnings, and typing hints. It also imports specific components from the 'nrrd' package for parsing and data types.

```python
import bz2
import io
import os
import re
import shlex
import warnings
import zlib
from collections import OrderedDict
from typing import IO, Any, AnyStr, Iterable, Tuple

import nrrd
from nrrd.parsers import *
from nrrd.types import IndexOrder, NRRDFieldMap, NRRDFieldType, NRRDHeader
```

--------------------------------

### Write NRRD Header and Data (Python)

Source: https://pynrrd.readthedocs.io/en/stable/_modules/nrrd/writer

This snippet demonstrates writing NRRD header and data. It handles file objects and automatically generates header fields. It supports custom fields and compression levels.

```python
    header = _handle_header(data, header, index_order)

    # If the file is a file handle, then write to the file.
    if isinstance(file, io.IOBase):
        _write_header(file, header, custom_field_map)
        _write_data(data, file, header, compression_level=compression_level, index_order=index_order)
        return
```

--------------------------------

### NRRD File Format Structure

Source: https://pynrrd.readthedocs.io/en/stable/background/about

This code snippet illustrates the general structure of an NRRD file, including the magic line, header fields, custom fields, comments, and data placement. It serves as a template for understanding how NRRD files are organized.

```plaintext
NRRD<NRRD file version>
# Complete NRRD file format specification at:
# http://teem.sourceforge.net/nrrd/format.html
<field>: <value>
<field>: <value>
...
<field>: <value>
<custom field>:=<value>
<custom field>:=<value>
...
<custom field>:=<value>
# Comments are identified with a # symbol

<data here if stored in same file, otherwise stored in detached file>

```

--------------------------------

### Representing String Lists in NRRD and Python

Source: https://pynrrd.readthedocs.io/en/stable/background/datatypes

Shows the NRRD syntax for space-separated strings ('s s ... s') and its parsing into a Python list of strings. This is for handling multiple text entries.

```python
[‘this’, ‘is’, ‘space’, ‘separated’]
```

--------------------------------

### Import Statements and Data Handling Notes for nrrd.writer

Source: https://pynrrd.readthedocs.io/en/stable/_modules/nrrd/writer

This snippet shows the import statements for the nrrd.writer module and a comment discussing a historical Python limitation regarding large uncompressed data. It highlights the use of libraries like bz2, io, os, zlib, and numpy, along with nrrd-specific components. The comment explains a workaround for handling data exceeding 4GB by reading in smaller chunks, with a default chunk size of 1MB.

```python
import bz2
import io
import os
import zlib
from collections import OrderedDict
from datetime import datetime
from typing import IO, Any, Dict

import numpy.typing as npt

from nrrd.errors import NRRDError
from nrrd.formatters import *
from nrrd.reader import _get_field_type
from nrrd.types import IndexOrder, NRRDFieldMap, NRRDFieldType, NRRDHeader

# Older versions of Python had issues when uncompressed data was larger than 4GB (2^32). This should be fixed in latest
# version of Python 2.7 and all versions of Python 3. The fix for this issue is to read the data in smaller chunks. The
# chunk size is set to be small here at 1MB since performance did not vary much based on the chunk size. A smaller chunk
```

--------------------------------

### Main NRRD Write Function

Source: https://pynrrd.readthedocs.io/en/stable/_modules/nrrd/writer

Orchestrates the writing of NumPy arrays to NRRD files. It handles file paths, header information, compression settings, and detached header creation. It validates input parameters and calls appropriate internal functions based on the specified encoding.

```python
def write(file: Union[str, IO], data: npt.NDArray, header: Optional[NRRDHeader] = None,
detached_header: bool = False, relative_data_path: bool = True,
          custom_field_map: Optional[NRRDFieldMap] = None, compression_level: int = 9, index_order: IndexOrder = 'F'):
    """Write :class:`numpy.ndarray` to NRRD file

    The :obj:`file` parameter specifies the absolute or relative filename to write the NRRD file to or an
    io.BytesIO object.

    If :obj:`file` is a filename and the extension is .nhdr, then the :obj:`detached_header` parameter is set to true
    automatically. If the :obj:`detached_header` parameter is set to :obj:`True` and the :obj:`filename` ends in .nrrd,
    then the header file will have the same path and base name as the :obj:`file` but with an extension of .nhdr.
    In all other cases, the header and data are saved in the same file.

    :obj:`header` is an optional parameter containing the fields and values to be added to the NRRD header.

    .. note::
            :obj:`detached_header` is ignored if :obj:`file` is io.BytesIO and not a str filename

    .. note::
    
```

--------------------------------

### nrrd.read() - Read Entire NRRD File

Source: https://pynrrd.readthedocs.io/en/stable/reference/reading

Reads an entire NRRD file, returning both the header information and the data as a NumPy array. It supports custom field mapping and index order specification.

```APIDOC
## nrrd.read()

### Description
Read a NRRD file and return the header and data.

### Method
`nrrd.read`

### Endpoint
Not applicable (Function call)

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
None

### Parameters
- **filename** (str) - Required - Filename of the NRRD file.
- **custom_field_map** (dict[str, Literal['int', 'double', 'string', 'int list', 'double list', 'string list', 'quoted string list', 'int vector', 'double vector', 'int matrix', 'double matrix']]) - Optional - Dictionary used for parsing custom field types where the key is the custom field name and the value is a string identifying datatype for the custom field.
- **index_order** (Literal['F', 'C']) - Optional - Specifies the index order of the resulting data array. Either ‘C’ (C-order) or ‘F’ (Fortran-order).

### Returns
- **data** (numpy.ndarray) - Data read from NRRD file.
- **header** (dict[str, Any]) - Dictionary containing the header fields and their corresponding parsed value.

### Request Example
```python
import nrrd
data, header = nrrd.read('my_file.nrrd')
```

### Response
#### Success Response (Tuple[ndarray, dict])
- **data** (numpy.ndarray) - The data content of the NRRD file.
- **header** (dict) - A dictionary containing all parsed header fields.

#### Response Example
```json
{
  "data": "<numpy.ndarray>",
  "header": {
    "type": "int8",
    "dimension": 3,
    "sizes": [100, 100, 100],
    "space": "left-posterior-superior",
    "space directions": [
      [1, 0, 0],
      [0, 1, 0],
      [0, 0, 1]
    ],
    "kinds": [
      "domain",
      "domain",
      "domain"
    ]
  }
}
```
```

--------------------------------

### Representing Integer Matrices in NRRD and Python

Source: https://pynrrd.readthedocs.io/en/stable/background/datatypes

Details the NRRD syntax for integer matrices ('(i,i,...) (i,i,...) ...') and their conversion into a 2D NumPy array of integers in Python. All rows must be specified.

```python
np.array([[1, 0, 0], [0, 1, 0], [0, 0, 1]])
```

--------------------------------

### Write Compressed Data (gzip/bzip2) in Chunks

Source: https://pynrrd.readthedocs.io/en/stable/_modules/nrrd/writer

Writes NRRD data using gzip or bzip2 compression. It initializes the appropriate compressor object and writes the data in chunks, compressing each chunk before writing to the file object. The process includes flushing the compressor to ensure all data is written.

```python
# Convert the data into a string
raw_data = data.tobytes(order=index_order)

# Construct the compressor object based on encoding
if header['encoding'] in ['gzip', 'gz']:
    compressobj = zlib.compressobj(compression_level, zlib.DEFLATED, zlib.MAX_WBITS | 16)
elif header['encoding'] in ['bzip2', 'bz2']:
    compressobj = bz2.BZ2Compressor(compression_level)
else:
    raise NRRDError(f'Unsupported encoding: {header["encoding"]}')

# Write the data in chunks (see _WRITE_CHUNKSIZE declaration for more information why)
# Obtain the length of the data since we will be using it repeatedly, more efficient
start_index = 0
raw_data_len = len(raw_data)

# Loop through the data and write it by chunk
while start_index < raw_data_len:
    # End index is start index plus the chunk size
    # Set to the string length to read the remaining chunk at the end
    end_index = min(start_index + _WRITE_CHUNKSIZE, raw_data_len)

    # Write the compressed data
    fh.write(compressobj.compress(raw_data[start_index:end_index]))

    start_index = end_index

# Finish writing the data
fh.write(compressobj.flush())
fh.flush()
```

--------------------------------

### Basic Datatypes in pynrrd

Source: https://pynrrd.readthedocs.io/en/stable/_sources/background/datatypes

Demonstrates the mapping of simple NRRD datatypes (int, double, string) to their Python equivalents. These are fundamental types used for single values within NRRD headers.

```python
import numpy as np

# NRRD Syntax: <i>
# Python Datatype: :class:`int`
python_int = 12

# NRRD Syntax: <d>
# Python Datatype: :class:`float`
python_float = 3.14

# NRRD Syntax: <s>
# Python Datatype: :class:`str`
python_string = 'test'
```

--------------------------------

### Representing Strings in NRRD and Python

Source: https://pynrrd.readthedocs.io/en/stable/background/datatypes

Illustrates the NRRD syntax for strings ('s') and their mapping to Python strings. This is used for textual data within headers.

```python
‘test’
```

--------------------------------

### Representing Integers in NRRD and Python

Source: https://pynrrd.readthedocs.io/en/stable/background/datatypes

Demonstrates the NRRD syntax for single integers ('i') and their representation as Python integers. This is a fundamental datatype for numerical data.

```python
12
```

--------------------------------

### Representing Integer Vector Lists in NRRD and Python

Source: https://pynrrd.readthedocs.io/en/stable/background/datatypes

Explains the NRRD syntax for lists of integer vectors ('(i,i,...) (i,i,...) ...') and their parsing into a Python list of NumPy integer arrays. Optional rows are represented as None.

```python
[np.array([1, 0, 0]), np.array([0, 1, 0]), None, np.array([0, 0, 1])]
```

--------------------------------

### nrrd.format_vector_list

Source: https://pynrrd.readthedocs.io/en/stable/reference/formatting

Formats a list of (N,) NumPy arrays into a NRRD vector list string.

```APIDOC
## nrrd.format_vector_list

### Description
Formats a list of (N,) NumPy arrays into a NRRD vector list string.

### Method
`nrrd.format_vector_list(x)`

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
- **x** (list of ndarray) - Required - The list of (N,) NumPy arrays to convert.

### Request Example
```json
{
  "x": [[1.0, 2.0], [3.0, 4.0]]
}
```

### Response
#### Success Response (200)
- **vector_list** (str) - The formatted vector list as a string.

#### Response Example
```json
{
  "vector_list": "(1.0,2.0);(3.0,4.0)"
}
```
```

--------------------------------

### Write NRRD Header and Data (Python)

Source: https://pynrrd.readthedocs.io/en/stable/_modules/nrrd/writer

This code snippet demonstrates how to write NRRD file headers and associated data using the pynrrd library. It handles both cases where the header and data are written to a single file or to separate header (.nhdr) and data (.nrrd) files. It utilizes internal functions like `_write_header` and `_write_data`.

```python
elif file.endswith('.nrrd') and detached_header:
        data_filename = file
        file = f'{os.path.splitext(file)[0]}.nhdr'
        header['data file'] = os.path.basename(data_filename) if relative_data_path else os.path.abspath(data_filename)
    else:
        # Write header & data as one file
        data_filename = file
        detached_header = False

    with open(file, 'wb') as fh:
        _write_header(fh, header, custom_field_map)

        # If header & data in the same file is desired, write data in the file
        if not detached_header:
            _write_data(data, fh, header, compression_level=compression_level, index_order=index_order)

    # If detached header desired, write data to different file
    if detached_header:
        with open(data_filename, 'wb') as data_fh:
            _write_data(data, data_fh, header, compression_level=compression_level, index_order=index_order)
```

--------------------------------

### nrrd.write API

Source: https://pynrrd.readthedocs.io/en/stable/reference/writing

This section details the `nrrd.write` function for saving numpy arrays to NRRD files. It covers parameters for file handling, data input, header customization, and compression options.

```APIDOC
## POST /nrrd/write

### Description
Writes a `numpy.ndarray` to an NRRD file. Supports various options for header customization, detached file storage, and compression.

### Method
POST

### Endpoint
/nrrd/write

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
- **file** (str or io.IOBase) - Required - Filename or file object for the NRRD file.
- **data** (numpy.ndarray) - Required - The numpy array data to be saved.
- **header** (dict, optional) - Optional - Dictionary containing NRRD header fields and values.
- **detached_header** (bool or str, optional) - Optional - If True, saves header and data in separate files. If a string is provided, it specifies the path to the data file when the main file ends with '.nhdr'. Defaults to False.
- **relative_data_path** (bool, optional) - Optional - Determines if the data filename in a detached header is relative or absolute. Ignored if not using detached headers. Defaults to True.
- **custom_field_map** (dict, optional) - Optional - Maps custom field names to their data types for parsing.
- **compression_level** (int, optional) - Optional - Compression level (1-9) for compressed encodings (gzip, bzip). Defaults to 9.
- **index_order** (str, optional) - Optional - Specifies the index order for writing ('C' for C-order, 'F' for Fortran-order). Must be consistent with reading order. Defaults to 'F'.

### Request Example
```json
{
  "file": "output.nrrd",
  "data": [[1, 2], [3, 4]],
  "header": {
    "comment": "Example NRRD file"
  },
  "detached_header": false,
  "compression_level": 6
}
```

### Response
#### Success Response (200)
- **message** (str) - Confirmation message indicating the file was written successfully.

#### Response Example
```json
{
  "message": "File output.nrrd written successfully."
}
```
```

--------------------------------

### Handle Unsupported Encodings

Source: https://pynrrd.readthedocs.io/en/stable/_modules/nrrd/reader

Raises an NRRDError if the specified encoding in the NRRD header is not supported (e.g., not 'raw', 'ASCII', 'gzip', or 'bzip2'). It also ensures the file handle is closed if it was opened internally.

```python
else:
    # Must close the file because if the file was opened above from detached filename, there is no "with" block
    # to close it for us
    if data_filename is not None:
        fh.close()

    raise NRRDError(f'Unsupported encoding: {header["encoding"]}')
```

--------------------------------

### nrrd.format_optional_vector_list

Source: https://pynrrd.readthedocs.io/en/stable/reference/formatting

Formats a list containing (N,) NumPy arrays or None into a NRRD optional vector list string.

```APIDOC
## nrrd.format_optional_vector_list

### Description
Formats a list of (N,) NumPy arrays or None into a NRRD optional vector list string.

### Method
`nrrd.format_optional_vector_list(x)`

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
- **x** (list of ndarray or None) - Required - The list of (N,) NumPy arrays or None to convert.

### Request Example
```json
{
  "x": [[1.0, 2.0], null, [3.0, 4.0]]
}
```

### Response
#### Success Response (200)
- **vector_list** (str) - The formatted optional vector list as a string.

#### Response Example
```json
{
  "vector_list": "(1.0,2.0);none;(3.0,4.0)"
}
```
```

--------------------------------

### Write NRRD File Header

Source: https://pynrrd.readthedocs.io/en/stable/_modules/nrrd/writer

Writes the NRRD file header to a given file object. Includes magic number, generation timestamp, and comments. It also formats and writes header fields, including custom fields, in a defined order.

```python
def _write_header(file: IO, header: Dict[str, Any], custom_field_map: Optional[NRRDFieldMap] = None):
    file.write(b'NRRD0005\n')
    file.write(b'# This NRRD file was generated by pynrrd\n')
    file.write(b'# on ' + datetime.utcnow().strftime('%Y-%m-%d %H:%M:%S').encode('ascii') + b'(GMT).\n')
    file.write(b'# Complete NRRD file format specification at:\n')
    file.write(b'# http://teem.sourceforge.net/nrrd/format.html\n')

    # Copy the options since dictionaries are mutable when passed as an argument
    # Thus, to prevent changes to the actual options, a copy is made
    # Empty ordered_options list is made (will be converted into dictionary)
    local_options = header.copy()
    ordered_options = []

    # Loop through field order and add the key/value if present
    # Remove the key/value from the local options so that we know not to add it again
    for field in _NRRD_FIELD_ORDER:
        if field in local_options:
            ordered_options.append((field, local_options[field]))
            del local_options[field]

    # Leftover items are assumed to be the custom field/value options
```

--------------------------------

### Decompress and Parse Bzip2 Encoded Data

Source: https://pynrrd.readthedocs.io/en/stable/_modules/nrrd/reader

Manages the decompression of bzip2-encoded NRRD data. It reads compressed data in chunks, decompresses it using bz2.BZ2Decompressor, and then parses the decompressed bytes into a NumPy array, applying any byte skip.

```python
elif header['encoding'] in ['bzip2', 'bz2']:
    decompobj = bz2.BZ2Decompressor()
# ... (rest of the decompression loop and parsing)
data = np.frombuffer(decompressed_data[byte_skip:], dtype)
```

--------------------------------

### Representing Double Matrices in NRRD and Python

Source: https://pynrrd.readthedocs.io/en/stable/background/datatypes

Shows the NRRD syntax for double matrices ('(d,d,...) (d,d,...) ...') and their representation as 2D NumPy arrays of floats in Python. Supports 'none' for empty rows, mapped to NaN.

```python
np.array([[2.54, 1.3, 0.0], [3.14, 0.3, 3.3], [np.nan, np.nan, np.nan], [0.0, -12.3, -3.3]])
```

--------------------------------

### Representing Integer Lists in NRRD and Python

Source: https://pynrrd.readthedocs.io/en/stable/background/datatypes

Details the NRRD syntax for a sequence of integers ('i i ... i') and its conversion into a 1D NumPy array with integer dtype in Python. Useful for collections of integer values.

```python
np.array([1, 2, 3, 4])
```

--------------------------------

### nrrd.format_matrix

Source: https://pynrrd.readthedocs.io/en/stable/reference/formatting

Formats a NumPy array of shape (M,N) into a NRRD matrix string.

```APIDOC
## nrrd.format_matrix

### Description
Formats a (M,N) NumPy array into a NRRD matrix string.

### Method
`nrrd.format_matrix(x)`

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
- **x** (ndarray) - Required - The (M,N) NumPy array to convert.

### Request Example
```json
{
  "x": [[1, 2], [3, 4]]
}
```

### Response
#### Success Response (200)
- **matrix** (str) - The formatted matrix as a string.

#### Response Example
```json
{
  "matrix": "(1,2;3,4)"
}
```
```

--------------------------------

### Write Custom Fields to NRRD Header

Source: https://pynrrd.readthedocs.io/en/stable/_modules/nrrd/writer

Appends custom fields to the NRRD header, differentiating between standard and custom fields using a ':=' delimiter for custom entries. It iterates through ordered options, formats field values, and writes them to the file, followed by a closing newline.

```python
# So get current size and any items past this index will be a custom value
custom_field_start_index = len(ordered_options)

# Add the leftover items to the end of the list and convert the options into a dictionary
ordered_options.extend(local_options.items())
ordered_options = OrderedDict(ordered_options)

for x, (field, value) in enumerate(ordered_options.items()):
    # Get the field_type based on field and then get corresponding
    # value as a str using _format_field_value
    field_type = _get_field_type(field, custom_field_map)
    value_str = _format_field_value(value, field_type)

    # Custom fields are written as key/value pairs with a := instead of : delimiter
    if x >= custom_field_start_index:
        file.write((f'{field}:={value_str}\n').encode('ascii'))
    else:
        file.write((f'{field}: {value_str}\n').encode('ascii'))

# Write the closing extra newline
file.write(b'\n')
```

--------------------------------

### Decompress and Parse Gzip Encoded Data

Source: https://pynrrd.readthedocs.io/en/stable/_modules/nrrd/reader

Handles decompression of gzip-encoded NRRD data. It reads compressed data in chunks, decompresses it, and then parses the resulting bytes into a NumPy array according to the specified dtype and byte skip.

```python
if header['encoding'] in ['gzip', 'gz']:
    decompobj = zlib.decompressobj(zlib.MAX_WBITS | 16)
# ... (rest of the decompression loop and parsing)
data = np.frombuffer(decompressed_data[byte_skip:], dtype)
```

--------------------------------

### Representing Double Vector Lists in NRRD and Python

Source: https://pynrrd.readthedocs.io/en/stable/background/datatypes

Details the NRRD syntax for lists of double vectors ('(d,d,...) (d,d,...) ...') and their conversion into a Python list of NumPy float arrays. Optional rows are handled as None.

```python
[np.array([2.54, 1.3, 0.0]), np.array([3.14, 0.3, 3.3]), None, np.array([0.0, -12.3, -3.3])]
```

--------------------------------

### Representing Quoted String Lists in NRRD and Python

Source: https://pynrrd.readthedocs.io/en/stable/background/datatypes

Details the NRRD syntax for quoted strings ('“<s>” “<s>” ... “<s>”') and their conversion into a Python list of strings. This handles strings that may contain spaces.

```python
[‘one item’, ‘two items’, ‘three’, ‘four’]
```

--------------------------------

### Read NRRD File Data and Header with pynrrd

Source: https://pynrrd.readthedocs.io/en/stable/_modules/nrrd/reader

Reads data and header information from an NRRD file. It handles custom field parsing and allows specification of the data array's index order (C-order or Fortran-order). Returns a NumPy array for the data and a dictionary for the header.

```python
with open(filename, 'rb') as fh:
    header = read_header(fh, custom_field_map)
    data = read_data(header, fh, filename, index_order)

return data, header
```

--------------------------------

### Parse ASCII Data from BytesIO

Source: https://pynrrd.readthedocs.io/en/stable/_modules/nrrd/reader

Reads data encoded as ASCII text from a BytesIO object, splitting values by spaces and converting them to a specified NumPy dtype. This is for in-memory text-based NRRD data.

```python
if isinstance(fh, io.BytesIO):
    data = np.fromstring(fh.read(), dtype, sep=' ')
else:
    data = np.fromfile(fh, dtype, sep=' ')
```

--------------------------------

### Handle large uncompressed data in nrrd.reader

Source: https://pynrrd.readthedocs.io/en/stable/_modules/nrrd/reader

Addresses a historical Python issue where uncompressed data larger than 4GB could cause problems. The code comments explain that this is fixed in newer Python versions and suggests reading data in smaller chunks if issues arise, with a default chunk size of 1GB for performance.

```python
# Older versions of Python had issues when uncompressed data was larger than 4GB (2^32). This should be fixed in latest
# version of Python 2.7 and all versions of Python 3. The fix for this issue is to read the data in smaller chunks.
# Chunk size is set to be large at 1GB to improve performance. If issues arise decompressing larger files, try to reduce
```