Closed seisman closed 3 years ago
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I do not think we have checks that might apply to categorical data. We should check that the input z value exactly matches the entries in the CPT and not the z = 1.5 which should give an error. People who want z from 1-2 to give a constant color should use an discrete CPT, not a categorical one. So we should start with implementing that test. Likewise I think back and foreground does not make too much sense either but I suppose for numerical categories we could allow that. For key-based categorically we clearly should not allow it. I will see what checks I can add.
Shall we distinguish between numerical categorical CPTs and key-based (e.g. text) categorical CPTs? I see the CPT has an unsigned int categorical that is used as a bit flag and bits 1 and 2 are set but I see no use of the bits, just that it is nonzero. I am pretty sure that if you have categories, then any value not among the listed categories should return NaN and there cannot be a fore and background color. It should not matter that the keys happen to be numbers or strings.
I am pretty sure that if you have categories, then any value not among the listed categories should return NaN and there cannot be a fore and background color. It should not matter that the keys happen to be numbers or strings.
Yes, it makes more sense to me.
Closed #4407.
Description of the problem
As per the documentation:
The actual behavior is inconsistent with the documentation.
Full script that generated the error
Actual outcome
Expected outcome
The figure doesn't match the documentation:
System information
gmt --version
): 6.2.0_2cce034_2020.07.28