iframe-proxy | Sunbelt Computer Software

Repository navigation

# Author: OMKAR PATHAK

# Data type Description

# bool_ Boolean (True or False) stored as a byte

# int_ Default integer type (same as C long; normally either int64 or int32)

# intc Identical to C int (normally int32 or int64)

# intp Integer used for indexing (same as C ssize_t; normally either int32 or int64)

# int8 Byte (-128 to 127)

# int16 Integer (-32768 to 32767)

# int32 Integer (-2147483648 to 2147483647)

# int64 Integer (-9223372036854775808 to 9223372036854775807)

# uint8 Unsigned integer (0 to 255)

# uint16 Unsigned integer (0 to 65535)

# uint32 Unsigned integer (0 to 4294967295)

# uint64 Unsigned integer (0 to 18446744073709551615)

# float_ Shorthand for float64.

# float16 Half precision float: sign bit, 5 bits exponent, 10 bits mantissa

# float32 Single precision float: sign bit, 8 bits exponent, 23 bits mantissa

# float64 Double precision float: sign bit, 11 bits exponent, 52 bits mantissa

# complex_ Shorthand for complex128.

# complex64 Complex number, represented by two 32-bit floats (real and imaginary components)

# complex128 Complex number, represented by two 64-bit floats (real and imaginary components)

import numpy as np

# while creating a numpy array, any data type from above can be explicitly specified.

myArray = np.arange(10)

print(myArray) # [0 1 2 3 4 5 6 7 8 9]

myArray = np.array(myArray, dtype = np.float32)

print(myArray) # [ 0. 1. 2. 3. 4. 5. 6. 7. 8. 9.]

myArray = np.array(myArray, dtype = np.complex64)

print(myArray) # [ 0.+0.j 1.+0.j 2.+0.j 3.+0.j 4.+0.j 5.+0.j 6.+0.j 7.+0.j 8.+0.j 9.+0.j]