RankNormalize¶
- class RankNormalize(levels, vmin=None, vmax=None, clip=False)¶
 Color distribution normalization class based on rank and not value.
This class is used to manage the “rank” norm for Contour drawables
- Attributes:
 - clip
 - vmax
 - vmin
 
Methods
autoscale(A)Set vmin, vmax to min, max of A.
If vmin or vmax are not set, use the min/max of A to set them.
process_value(value)Homogenize the input value for easy and efficient normalization.
scaled()Return whether vmin and vmax are set.
inverse
- __init__(levels, vmin=None, vmax=None, clip=False)¶
 Construct the normalization based on rank
- Parameters:
 - levelslist of floats
 List of level values.
- vminfloat, optional
 Minimum value for color distribution
- vmaxfloat, optional
 Maximum value for color distribution
- clipbool, optional
 Indicator for cutting color distribution out of vmin and vmax Required by the parent class, but unused.
- autoscale(A)¶
 Set vmin, vmax to min, max of A.
- autoscale_None(A)¶
 If vmin or vmax are not set, use the min/max of A to set them.
- static process_value(value)¶
 Homogenize the input value for easy and efficient normalization.
value can be a scalar or sequence.
- Returns:
 - resultmasked array
 Masked array with the same shape as value.
- is_scalarbool
 Whether value is a scalar.
Notes
Float dtypes are preserved; integer types with two bytes or smaller are converted to np.float32, and larger types are converted to np.float64. Preserving float32 when possible, and using in-place operations, greatly improves speed for large arrays.
- scaled()¶
 Return whether vmin and vmax are set.
      OpenTURNS