parameters: (x, y, new_x)
return_statement: return new_y
docstring: Linearly interpolates values in new_x based in the log space of y.
  
      Parameters
      ----------
      x : array_like
          Independent values.
      y : array_like
          Dependent values.
      new_x : array_like
          The x values to return interpolated y values at.
docstring_summary: Linearly interpolates values in new_x based in the log space of y.
docstring_tokens: Linearly interpolates values in new_x based in the log space of y .
function: def logarithmic(x, y, new_x):
      """
      Linearly interpolates values in new_x based in the log space of y.
  
      Parameters
      ----------
      x : array_like
          Independent values.
      y : array_like
          Dependent values.
      new_x : array_like
          The x values to return interpolated y values at.
  
      """
      x = atleast_1d_and_contiguous(x, np.float64)
      y = atleast_1d_and_contiguous(y, np.float64)
      new_x = atleast_1d_and_contiguous(new_x, np.float64)
  
      if y.ndim > 2:
          raise ValueError("`linear` only works with 1-D or 2-D arrays.")
      if len(y.shape) == 2:
          new_y = np.zeros((y.shape[0], len(new_x)), np.float64)
          for i in range(len(new_y)):
              _interpolate.loginterp_dddd(x, y[i], new_x, new_y[i])
      else:
          new_y = np.zeros(len(new_x), np.float64)
          _interpolate.loginterp_dddd(x, y, new_x, new_y)
  
      return new_y
function_tokens: def logarithmic ( x , y , new_x ) : x = atleast_1d_and_contiguous ( x , np . float64 ) y = atleast_1d_and_contiguous ( y , np . float64 ) new_x = atleast_1d_and_contiguous ( new_x , np . float64 ) if y . ndim > 2 : raise ValueError ( "`linear` only works with 1-D or 2-D arrays." ) if len ( y . shape ) == 2 : new_y = np . zeros ( ( y . shape [ 0 ] , len ( new_x ) ) , np . float64 ) for i in range ( len ( new_y ) ) : _interpolate . loginterp_dddd ( x , y [ i ] , new_x , new_y [ i ] ) else : new_y = np . zeros ( len ( new_x ) , np . float64 ) _interpolate . loginterp_dddd ( x , y , new_x , new_y ) return new_y