import rastereasy

Removing some bands

Two options

• Return an image with removed bands (function remove_bands with default options)

• Remove bands from image directly (function remove_bands with inplace=True option)

name_im='./data/demo/sentinel.tif'
image=rastereasy.Geoimage(name_im)
image.info()

- Size of the image:
   - Rows (height): 1000
   - Cols (width): 1000
   - Bands: 12
- Spatial resolution: 10.0  meters / degree (depending on projection system)
- Central point latitude - longitude coordinates: (7.04099599, 38.39058840)
- Driver: GTiff
- Data type: int16
- Projection system: EPSG:32637
- Nodata: -32768.0

- Given names for spectral bands: 
   {'1': 1, '2': 2, '3': 3, '4': 4, '5': 5, '6': 6, '7': 7, '8': 8, '9': 9, '10': 10, '11': 11, '12': 12}

help(image.remove_bands)

Help on method remove_bands in module rastereasy.rastereasy:

remove_bands(bands, inplace=False, reformat_names=False, dest_name=None) method of rastereasy.rastereasy.Geoimage instance
    Remove specified bands from the image in-place.

    This method modifies the current image by removing the specified bands.
    The remaining bands can be renamed sequentially or retain their original names.

    Parameters
    ----------
    bands : str, list, int, or array-like
        The bands to remove from the image. Format depends on band naming:
        - If using named bands: band name(s) as string(s) (e.g., 'NIR', ['R', 'G', 'B'])
        - If using indexed bands: band index/indices as int(s) or string(s) (e.g., 3, ['1', '4', '7'])

    inplace : bool, default False
        If False, return a copy. Otherwise, do removing in place and return None.


    reformat_names : bool, optional
        Band naming behavior after removal:
        - If True: Rename remaining bands sequentially as "1", "2", "3", etc.
        - If False: Preserve original band names with their indices updated
        Default is False.

    dest_name : str, optional
        Path to save the modified image. If None, the image is not saved.
        Default is None.

    Returns
    -------
    Geoimage
        The image with specified bands removed, allowing for method chaining.

    Raises
    ------
    ValueError
        If any specified band doesn't exist in the image, or if removing all bands.

    Examples
    --------
    >>> # Remove a single band
    >>> original_bands = list(image.names.keys())
    >>> image_removed = image.remove_bands('B4')
    >>> print(f"Original: {original_bands}, After removal: {list(image_removed.names.keys())}")
    >>>
    >>> # Remove multiple bands and rename sequentially
    >>> image_removed = image.remove_bands(['B1', 'B2'], reformat_names=True)
    >>> print(f"After renaming: {list(image_removed = .names.keys())}")
    >>>
    >>> # Remove bands and save the result
    >>> image_removed = image.remove_bands(['SWIR1', 'SWIR2'], dest_name='visible_only.tif')
    >>>
    >>> # Remove a single band
    >>> original_bands = list(image.names.keys())
    >>> image.remove_bands('B4', inplace=True)
    >>> print(f"Original: {original_bands}, After removal: {list(image.names.keys())}")
    >>>
    >>> # Remove multiple bands and rename sequentially
    >>> image.remove_bands(['B1', 'B2'], reformat_names=True, inplace=True)
    >>> print(f"After renaming: {list(image.names.keys())}")
    >>>
    >>> # Remove bands and save the result
    >>> image.remove_bands(['SWIR1', 'SWIR2'], dest_name='visible_only.tif', inplace=True)

    Notes
    -----
    - This method permanently removes the specified bands from the image.
    - If you want to preserve the original image, use apply_remove_bands() instead.
    - If reformat_names=False (default), band names are preserved but indices are updated.
    - If reformat_names=True, bands are renamed sequentially (1, 2, 3, ...).

1) Return an image with removed bands (function remove_bands)

image_removed=image.remove_bands([10,8,9])
image_removed.info()

- Size of the image:
   - Rows (height): 1000
   - Cols (width): 1000
   - Bands: 9
- Spatial resolution: 10.0  meters / degree (depending on projection system)
- Central point latitude - longitude coordinates: (7.04099599, 38.39058840)
- Driver: GTiff
- Data type: int16
- Projection system: EPSG:32637
- Nodata: -32768.0

- Given names for spectral bands: 
   {'1': 1, '2': 2, '3': 3, '4': 4, '5': 5, '6': 6, '7': 7, '11': 8, '12': 9}

As you can see, it can be interesting to reformat bands names (depending of application). In this case, use reformat_names=True

image_removed=image.remove_bands([10,8,9],reformat_names=True)
image_removed.info()

- Size of the image:
   - Rows (height): 1000
   - Cols (width): 1000
   - Bands: 9
- Spatial resolution: 10.0  meters / degree (depending on projection system)
- Central point latitude - longitude coordinates: (7.04099599, 38.39058840)
- Driver: GTiff
- Data type: int16
- Projection system: EPSG:32637
- Nodata: -32768.0

- Given names for spectral bands: 
   {'1': 1, '2': 2, '3': 3, '4': 4, '5': 5, '6': 6, '7': 7, '8': 8, '9': 9}

In this case, it can be easier to deal with real names

names = {"CO" : 1,"B": 2,"G":3,"R":4,"RE1":5,"RE2":6,"RE3":7,"NIR":8,"WA":9,"SWIR1":10,"SWIR2":11,"SWIR3":12}
image_names=rastereasy.Geoimage(name_im,names=names)
image_removed=image_names.remove_bands(['SWIR1','NIR','WA'])
image_removed.info()

- Size of the image:
   - Rows (height): 1000
   - Cols (width): 1000
   - Bands: 9
- Spatial resolution: 10.0  meters / degree (depending on projection system)
- Central point latitude - longitude coordinates: (7.04099599, 38.39058840)
- Driver: GTiff
- Data type: int16
- Projection system: EPSG:32637
- Nodata: -32768.0

- Given names for spectral bands: 
   {'CO': 1, 'B': 2, 'G': 3, 'R': 4, 'RE1': 5, 'RE2': 6, 'RE3': 7, 'SWIR2': 8, 'SWIR3': 9}

2) Remove bands from image directly (option inplace=True)

image_names.info()
image_names.remove_bands(['SWIR1','NIR','WA'], inplace=True)
image_names.info()

- Size of the image:
   - Rows (height): 1000
   - Cols (width): 1000
   - Bands: 12
- Spatial resolution: 10.0  meters / degree (depending on projection system)
- Central point latitude - longitude coordinates: (7.04099599, 38.39058840)
- Driver: GTiff
- Data type: int16
- Projection system: EPSG:32637
- Nodata: -32768.0

- Given names for spectral bands: 
   {'CO': 1, 'B': 2, 'G': 3, 'R': 4, 'RE1': 5, 'RE2': 6, 'RE3': 7, 'NIR': 8, 'WA': 9, 'SWIR1': 10, 'SWIR2': 11, 'SWIR3': 12}


- Size of the image:
   - Rows (height): 1000
   - Cols (width): 1000
   - Bands: 9
- Spatial resolution: 10.0  meters / degree (depending on projection system)
- Central point latitude - longitude coordinates: (7.04099599, 38.39058840)
- Driver: GTiff
- Data type: int16
- Projection system: EPSG:32637
- Nodata: -32768.0

- Given names for spectral bands: 
   {'CO': 1, 'B': 2, 'G': 3, 'R': 4, 'RE1': 5, 'RE2': 6, 'RE3': 7, 'SWIR2': 8, 'SWIR3': 9}