class_docstr: An annealed sinusoidal encoding.
class_docstr_tok: ["An","annealed","sinusoidal","encoding","."]
docstr: Eases in each frequency one by one with a cosine.
  
  This is equivalent to taking a Tukey window and sliding it to the right
  along the frequency spectrum.
  
  Args:
    min_freq_log2: the lower frequency band.
    max_freq_log2: the upper frequency band.
    num_bands: the number of frequencies.
    alpha: will ease in each frequency as alpha goes from 0.0 to num_freqs.
  
  Returns:
    A 1-d numpy array with num_sample elements containing the window.
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code: def cosine_easing_window(
      cls, min_freq_log2, max_freq_log2, num_bands, alpha
  ):
      """Eases in each frequency one by one with a cosine.
  
      This is equivalent to taking a Tukey window and sliding it to the right
      along the frequency spectrum.
  
      Args:
        min_freq_log2: the lower frequency band.
        max_freq_log2: the upper frequency band.
        num_bands: the number of frequencies.
        alpha: will ease in each frequency as alpha goes from 0.0 to num_freqs.
  
      Returns:
        A 1-d numpy array with num_sample elements containing the window.
      """
      if max_freq_log2 is None:
          max_freq_log2 = num_bands - 1.0
      bands = jnp.linspace(min_freq_log2, max_freq_log2, num_bands)
      x = jnp.clip(alpha - bands, 0.0, 1.0)
      return 0.5 * (1 + jnp.cos(jnp.pi * x + jnp.pi))
  
imports: import functools
  from typing import Optional, Tuple
  from flax import linen
  import jax
  import jax.numpy
  from nerfies import types
label_desc: Use image node_id 2 for calling the AnnealedSinusoidalEncoder obj's underlying member method code with example usage: obj.cosine_easing_window(cls, min_freq_log2, max_freq_log2, num_bands, alpha) and returns: unknown