Implement validation function.

The constraints that must be validated upon invocation of this function include:

[X] Each dataset object has a data property.
[X] data is an array (not a string or number or any other type)
[X] data is an array of objects, not of string or number or any other type.
[X] Each dataset object must have a metadata property.
[X] #dataset.metadata.columns must be an array, not a string or number or any other type.
[X] #dataset.metadata.columns is an array of objects, not of string or number or any other type.
[X] each column descriptor object has a "name" field
[X] each column descriptor object has a "name" field that is a string
[X] each column descriptor object has a "type" field
[X] each column descriptor object has a "type" field whose value is "number", "string", or "date"
[X] Each row object has keys corresponding to column names in #dataset.metadata.columns
[X] #dataset.metadata.columns names must match those in the data array.
[X] Each row object has values whose type corresponds to column types in #dataset.metadata.columns
[ ] If #dataset.metadata.isCube is true, each column is interpreted as either as a dimension or measure, depending on the value of the isDimension property.
[ ] Each of these objects must have the properties name, label and type.
[ ] If isCube is not true, then each of these column descriptor objects must not have the properties isDimension or interval.
[ ] #dataset.metadata.columns[i].name corresponds to the keys in each row object of dataset.data.
[ ] #dataset.metadata.columns[i].label Should be defined. A validation warning should be raised if the label is missing.
[ ] #dataset.metadata.columns[i].type must be either "number", "string", or "date".
[ ] If #dataset.metadata.columns[i].isDimension is set to true, then isCube must be set to true.
[ ] If #dataset.metadata.columns[i].isDimension is set to true and the column is of type "number" or "date", then interval must be defined.
[ ] If #dataset.metadata.columns[i].interval is defined, then
- the dataset is aggregated (isCube == true) and
- the column is a dimension (isDimension is true), and
- the column type is either "number" or "date".
[ ] If the column type is "number", then interval must be a number.
[ ] If the column type is "date", then interval must be a string corresponding to one of the interval types defined in d3-time. This includes, for example, "minute", "hour", "day", "week", "month", and "year".
[ ] If #dataset.metadata.columns[i].interval is defined, then data values should be spaced according to this interval (relative to any other data value from the column) when the column type is "number".
[ ] If #dataset.metadata.columns[i].interval is defined, then data values should be spaced according to this interval (relative to any other data value from the column) when the column type is "date".
[ ] If #dataset.metadata.columns[i].domain is defined and the column type is "string", then the domain must be an array of unique string values that occur in the column.
[ ] If #dataset.metadata.columns[i].domain is defined and the column type is "number", then the domain must be an array containing two numbers, the minimum (domain[0]) and the maximum (domain[1]).
[ ] If #dataset.metadata.columns[i].domain is defined and the column type is "number", then all values in the column must fall within the domain.
[ ] If #dataset.metadata.columns[i].domain is defined and the column type is "date", then the domain is an array containing two JavaScript Date objects, the minimum (domain[0]) and the maximum (domain[1]).
[ ] If #dataset.metadata.columns[i].domain is defined and the column type is "date", then all values in the column must fall within the domain.

chiasm-project / chiasm-dataset

Implement validation function. #1