original_docstring: 
      Returns the data vector `D` from the `w_tilde_data` matrix (see `w_tilde_data_imaging_from`), which encodes the
      the 1D image `d` and 1D noise-map values `\sigma` (see Warren & Dye 2003).
  
      This uses the array `data_to_pix_unique`, which describes the unique mappings of every set of image sub-pixels to
      pixelization pixels and `data_weights`, which describes how many sub-pixels uniquely map to each pixelization
      pixels (see `data_slim_to_pixelization_unique_from`).
  
      Parameters
      -----------
      w_tilde_data
          A matrix that encodes the PSF convolution values between the imaging divided by the noise map**2 that enables
          efficient calculation of the data vector.
      data_to_pix_unique
          An array that maps every data pixel index (e.g. the masked image pixel indexes in 1D) to its unique set of
          pixelization pixel indexes (see `data_slim_to_pixelization_unique_from`).
      data_weights
          For every unique mapping between a set of data sub-pixels and a pixelization pixel, the weight of these mapping
          based on the number of sub-pixels that map to pixelization pixel.
      pix_lengths
          A 1D array describing how many unique pixels each data pixel maps too, which is used to iterate over
          `data_to_pix_unique` and `data_weights`.
      pix_pixels
          The total number of pixels in the pixelization that reconstructs the data.
      
docstring: 
  
  This uses the array `data_to_pix_unique`, which describes the unique mappings of every set of image sub-pixels to
  pixelization pixels and `data_weights`, which describes how many sub-pixels uniquely map to each pixelization
  pixels .
  
  Parameters
  
  w_tilde_data
  A matrix that encodes the PSF convolution values between the imaging divided by the noise map**2 that enables
  efficient calculation of the data vector.
  data_to_pix_unique
  An array that maps every data pixel index  to its unique set of
  pixelization pixel indexes .
  data_weights
  For every unique mapping between a set of data sub-pixels and a pixelization pixel, the weight of these mapping
  based on the number of sub-pixels that map to pixelization pixel.
  pix_lengths
  A 1D array describing how many unique pixels each data pixel maps too, which is used to iterate over
  `data_to_pix_unique` and `data_weights`.
  pix_pixels
  The total number of pixels in the pixelization that reconstructs the data.
docstring_tokens: This uses the array ` data_to_pix_unique ` which describes the unique mappings of every set of image sub - pixels to pixelization pixels and ` data_weights ` which describes how many sub - pixels uniquely map to each pixelization pixels . Parameters w_tilde_data A matrix that encodes the PSF convolution values between the imaging divided by the noise map ** 2 that enables efficient calculation of the data vector . data_to_pix_unique An array that maps every data pixel index to its unique set of pixelization pixel indexes . data_weights For every unique mapping between a set of data sub - pixels and a pixelization pixel the weight of these mapping based on the number of sub - pixels that map to pixelization pixel . pix_lengths A 1D array describing how many unique pixels each data pixel maps too which is used to iterate over ` data_to_pix_unique ` and ` data_weights ` . pix_pixels The total number of pixels in the pixelization that reconstructs the data .
code: def data_vector_via_w_tilde_data_imaging_from(
      w_tilde_data: np.ndarray,
      data_to_pix_unique: np.ndarray,
      data_weights: np.ndarray,
      pix_lengths: np.ndarray,
      pix_pixels: int,
  ) -> np.ndarray:
      """
      Returns the data vector `D` from the `w_tilde_data` matrix (see `w_tilde_data_imaging_from`), which encodes the
      the 1D image `d` and 1D noise-map values `\sigma` (see Warren & Dye 2003).
  
      This uses the array `data_to_pix_unique`, which describes the unique mappings of every set of image sub-pixels to
      pixelization pixels and `data_weights`, which describes how many sub-pixels uniquely map to each pixelization
      pixels (see `data_slim_to_pixelization_unique_from`).
  
      Parameters
      -----------
      w_tilde_data
          A matrix that encodes the PSF convolution values between the imaging divided by the noise map**2 that enables
          efficient calculation of the data vector.
      data_to_pix_unique
          An array that maps every data pixel index (e.g. the masked image pixel indexes in 1D) to its unique set of
          pixelization pixel indexes (see `data_slim_to_pixelization_unique_from`).
      data_weights
          For every unique mapping between a set of data sub-pixels and a pixelization pixel, the weight of these mapping
          based on the number of sub-pixels that map to pixelization pixel.
      pix_lengths
          A 1D array describing how many unique pixels each data pixel maps too, which is used to iterate over
          `data_to_pix_unique` and `data_weights`.
      pix_pixels
          The total number of pixels in the pixelization that reconstructs the data.
      """
  
      data_pixels = w_tilde_data.shape[0]
  
      data_vector = np.zeros(pix_pixels)
  
      for data_0 in range(data_pixels):
  
          for pix_0_index in range(pix_lengths[data_0]):
  
              data_0_weight = data_weights[data_0, pix_0_index]
              pix_0 = data_to_pix_unique[data_0, pix_0_index]
  
              data_vector[pix_0] += data_0_weight * w_tilde_data[data_0]
  
      return data_vector
code_tokens: def data_vector_via_w_tilde_data_imaging_from ( w_tilde_data : np . ndarray , data_to_pix_unique : np . ndarray , data_weights : np . ndarray , pix_lengths : np . ndarray , pix_pixels : int , ) -> np . ndarray : data_pixels = w_tilde_data . shape [ 0 ] data_vector = np . zeros ( pix_pixels ) for data_0 in range ( data_pixels ) : for pix_0_index in range ( pix_lengths [ data_0 ] ) : data_0_weight = data_weights [ data_0 , pix_0_index ] pix_0 = data_to_pix_unique [ data_0 , pix_0_index ] data_vector [ pix_0 ] += data_0_weight * w_tilde_data [ data_0 ] return data_vector
short_docstring: Returns the data vector `D` from the `w_tilde_data` matrix (see `w_tilde_data_imaging_from`), which encodes the
  the 1D image `d` and 1D noise-map values `\sigma` (see Warren & Dye 2003).
short_docstring_tokens: Returns the data vector ` D ` from the ` w_tilde_data ` matrix ( see ` w_tilde_data_imaging_from ` ) which encodes the the 1D image ` d ` and 1D noise - map values ` \ sigma ` ( see Warren & Dye 2003 ) .
comment: """
      Returns the data vector `D` from the `w_tilde_data` matrix (see `w_tilde_data_imaging_from`), which encodes the
      the 1D image `d` and 1D noise-map values `\sigma` (see Warren & Dye 2003).
  
      This uses the array `data_to_pix_unique`, which describes the unique mappings of every set of image sub-pixels to
      pixelization pixels and `data_weights`, which describes how many sub-pixels uniquely map to each pixelization
      pixels (see `data_slim_to_pixelization_unique_from`).
  
      Parameters
      -----------
      w_tilde_data
          A matrix that encodes the PSF convolution values between the imaging divided by the noise map**2 that enables
          efficient calculation of the data vector.
      data_to_pix_unique
          An array that maps every data pixel index (e.g. the masked image pixel indexes in 1D) to its unique set of
          pixelization pixel indexes (see `data_slim_to_pixelization_unique_from`).
      data_weights
          For every unique mapping between a set of data sub-pixels and a pixelization pixel, the weight of these mapping
          based on the number of sub-pixels that map to pixelization pixel.
      pix_lengths
          A 1D array describing how many unique pixels each data pixel maps too, which is used to iterate over
          `data_to_pix_unique` and `data_weights`.
      pix_pixels
          The total number of pixels in the pixelization that reconstructs the data.
      """