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Test whether float datatype of different sizes are not subdtypes of each other in Python
To check whether float data types of different sizes are not subdtypes of each other, use the numpy.issubdtype() method in Python Numpy. The parameters are the dtype or object coercible to one.
Steps
At first, import the required library −
import numpy as np
Using the issubdtype() method in Numpy. Checking for float datatype with different sizes −
print("Result...",np.issubdtype(np.float16, np.float32)) print("Result...",np.issubdtype(np.float32, np.float16)) print("Result...",np.issubdtype(np.float64, np.float32)) print("Result...",np.issubdtype(np.float32, np.float64)) print("Result...",np.issubdtype(np.float16, np.float64)) print("Result...",np.issubdtype(np.float64, np.float16))
Example
import numpy as np # To check whether float data types of different sizes are not subdtypes of each other, use the numpy.issubdtype() method in Python Numpy. # The parameters are the dtype or object coercible to one print("Using the issubdtype() method in Numpy\n") # Checking for float datatype with different sizes print("Result...",np.issubdtype(np.float16, np.float32)) print("Result...",np.issubdtype(np.float32, np.float16)) print("Result...",np.issubdtype(np.float64, np.float32)) print("Result...",np.issubdtype(np.float32, np.float64)) print("Result...",np.issubdtype(np.float16, np.float64)) print("Result...",np.issubdtype(np.float64, np.float16))
Output
Using the issubdtype() method in Numpy Result... False Result... False Result... False Result... False Result... False Result... False
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