Shape validation using wx_shape

In this article we discuss how to validate the shape of objects (mostly arrays).

Syntax definition

Let us say we have an array with 5 dimensions we want the first three have the dimension of n=3 the fourth has dimension 4 and the last one is optional with dimension 2. We would get this shape syntax

expected = [n, n, n, 4, (2)]

and would validate it with the actual shape

test = [3, 3, 3, 4, 2].

Through the given shape the variable n is defined. And any shape that does not match our requirement would not be accepted and throws a value error.

Some examples that would not match our expected shape:

[1, 2, 2, 4, 2] the n mismatches.

[7, 7, 7, 4, 3] the optional 5th dimension has to be a 2.

[1, 1, 1, 4, 2, 2] this has more dimensions as we expect.

So what we need is a set of rules for the syntax of those shapes. The document will follow with exceptions and examples.

Syntax

Each shape item follows these rules:

  • an Integer indicates a fix dimension for the same item

  • a ~ indicates a single dimension of arbitrary length.

  • a ... indicates an arbitrary number of dimensions of arbitrary length, which can be optional.

  • a n indicates a single dimension fixed to an alphanumeric. So a string out of letters and numbers is allowed.

  • parenthesis (_) indicate that the dimension is optional. This can be combined with the other rules.

  • the symbols ~ furthermore add the option to implement an interval. This string 4~ would be an open interval that accepts all dimensions that are greater or equal to 4.

Exceptions

This is an additional rule set which describes (un-)intuitive rules:

  • No negative Dimensions are allowed.

  • Parenthesis and ... cannot be combined to (...).

  • The addition with the interval can only be ascending. Wrong would be 5~2

  • Parenthesis and ... can either be at the beginning or the end of the shape syntax.

  • It is possible to have multiple optional dimensions. They must stand all be at the beginning or the end. So [(1), 2, (3)] is not allowed.

Examples

Example of a validator and its matches and mismatches.

Validator:
["n", "~", 2, "~6", "(n)", (3), "..."]

Matches:
[3, 4, 2, 4, 3]
[1, 3, 2, 3, 1, 3, 7, 8, 9]
[1, 1, 2, 1]

Mismatches:
[1, 4, 2, 4, 3] mismatch of n: 1 = 3
[2, 4, 2, 4, 2, 2] mismatch of optional (3) = 2
[2, 4, 2, 7, 2, 3] mismatch of ~: 7 > 6 but has to be less then or equal to 6.
[2, 4, 2, -3, 2, 3] No negative dimensions allowed\

Now some examples of validators which will throw an error:
["(1)", 2, "(3)"] Validators are only allowed at the beginning or the end.
["11", 22, "3(3)"] Any character outside the parenthesis will cause an error.
["11", 22, "x..."] Any character in the ... will cause an error.
["11", 22, "m_1"] Underscores are not supported in variable names. Only alphanumeric strings are allowed.

ASDF schema usage

Now that we know the syntax let’s take a look at how to incorporate it in our ASDF schema definitions. The validation gets triggered by the wx_shape keyword.

For the validation to work the validator has to be defined on a property that itself has a list-like shape property. Take an ndarray property for example:

# ASDF schema
properties:
  array_prop:
    tag: tag:stsci.edu:asdf/core/ndarray-1.0.0

# ASDF file
array_prop: !core/ndarray-1.0.0
  data: [0, 1, 2, 3, 4]
  datatype: int32
  shape: [5]

We would validate this to always have shape [5] by adding the wx_shape keyword to the schema definition.

# ASDF schema
properties:
  array_prop:
    tag: tag:stsci.edu:asdf/core/ndarray-1.0.0
    wx_shape: [5]

The above example shows the basic usage for a single property. We can use most of the syntax features like (),~ and .... But be aware that the scope of this “inline” wx_shape validation is limited to the property that it validates! So no comparison to other shapes with alphanumerics is possible.

For example, following schema would validate and file would validate:

# ASDF schema
properties:
  array_prop:
    tag: tag:stsci.edu:asdf/core/ndarray-1.0.0
    wx_shape: [n]
  array_prop2:
    tag: tag:stsci.edu:asdf/core/ndarray-1.0.0
    wx_shape: [n]

# ASDF file
array_prop: !core/ndarray-1.0.0
  data: [0, 1, 2, 3, 4]
  datatype: int32
  shape: [5]
array_prop2: !core/ndarray-1.0.0
  data: [0, 1]
  datatype: int32
  shape: [2]

To compare and validate shapes across multiple properties we have to use a nested syntax that has all necessary properties in its scope. To assure array_prop and array_prop2 have the same shape we use the following schema:

# ASDF schema
properties:
  array_prop:
    tag: tag:stsci.edu:asdf/core/ndarray-1.0.0
  array_prop2:
    tag: tag:stsci.edu:asdf/core/ndarray-1.0.0
wx_shape:
  array_prop: [n]
  array_prop2: [n]

Note the following:

  • wx_shape is now defined on the same level as the properties keyword.

  • wx_shape is no longer a shape-like list but itself a nested object with shape-like lists as leaves.

optional properties

Properties that are optional (not listed as required) must be indicated as such for shape validation by putting the name in brackets. In this example, both optional_prop will only get validated if it exists in the tree.

# ASDF schema
properties:
  required_prop:
    tag: tag:stsci.edu:asdf/core/ndarray-1.0.0
  optional_prop:
    tag: tag:stsci.edu:asdf/core/ndarray-1.0.0
wx_shape:
  required_prop: [n]
  (optional_prop): [n]
required: [required_prop]

custom types validation

The following custom types can be validate with wx_shape even though the might not always define a shape property in itself.

  • number will validate like shape: [1]

  • tag:weldx.bam.de:weldx/time/timedeltaindex-1.0.0 will validate against the length of the TimedeltaIndex even if no data is stored.

complex nested example

Here is a more complex example demonstration some of the above points.

%YAML 1.1
---
$schema: "http://stsci.edu/schemas/yaml-schema/draft-01"
id: "http://weldx.bam.de/schemas/weldx/debug/test_shape_validator-1.0.0"
tag: "tag:weldx.bam.de:weldx/debug/test_shape_validator-1.0.0"

title: |
  simple demonstration and test schema for wx_shape validator syntax
type: object
properties:
  prop1:
    tag: tag:stsci.edu:asdf/core/ndarray-1.0.0
    wx_shape: [1,2,(3),(4)]

  prop2:
    tag: tag:stsci.edu:asdf/core/ndarray-1.0.0
    wx_shape: [~,2,1]

  prop3:
    tag: tag:stsci.edu:asdf/core/ndarray-1.0.0
    wx_shape: [2,4,6,8,...]

  prop4:
    tag: tag:stsci.edu:asdf/core/ndarray-1.0.0
    wx_shape: [~,3,5,7,9]

  prop5:
    type: number
    wx_shape: [1]

  nested_prop:
    type: object
    properties:
      p1:
        tag: tag:stsci.edu:asdf/core/ndarray-1.0.0
        wx_shape: [10,8,6,4,2]
      p2:
        tag: tag:stsci.edu:asdf/core/ndarray-1.0.0
        wx_shape: [9,7,5,3,1]

  optional_prop:
    tag: tag:stsci.edu:asdf/core/ndarray-1.0.0
    wx_shape: [1,2,(3),(4)]



required: [prop1,prop2,prop3,prop4,nested_prop]
propertyOrder: [prop1,prop2,prop3,prop4,nested_prop,optional_prop]
flowStyle: block
additionalProperties: true
wx_shape:
  prop1: [(~),2,n]
  prop2: [n,2,1]
  prop3: [2,4,5~7,...]
  prop4: [a,3,5,k,m]
  prop5: [a]
  nested_prop:
    p1: [10,1~10,6,4,2]
    p2: [(m),7,5,3,1]
    (p3): [a,2,n]
  (optional_prop): [a,2,n]