These functions include standard trigonometric functions, functions for arithmetic operations, complex number processing, statistical functions, etc. Generic functions have different characteristics, which are as follows:
- These functions work with ndarray (N-dimensional array), that is, with the Numpy class.
- It does fast element-wise operations on arrays.
- It supports various functions such like array translation, casting, etc.
- Numpy, generic functions — these are objects belonging to the numpy.ufunc class.
- Python functions can also be created as a generic function using the frompyfunc library function.
- Some ufuncs are called automatically when the corresponding arithmetic operator is used in arrays. For example, when adding two arrays is done element by element using the + operator, then np.add () is called internally.
Some of the main generic functions in Numpy are:
Trigonometric functions:
These functions work with radians, so it is necessary to convert angles to radians by multiplying by pi / 180. Only then can we call trigonometric functions. They take an array as input arguments. Includes features such as
| Function | Description |
|---|---|
| sin, cos, tan | compute sine, cosine and tangent of angles |
| arcsin, arccos, arctan | calculate inverse sine, cosine and tangent |
| hypot | calculate hypotenuse of given right triangle |
| sinh, cosh, tanh | compute hyperbolic sine, cosine and tangent |
| arcsinh, arccosh, arctanh | compute inverse hyperbolic sine, cosine and tangent |
| deg2rad | convert degree into radians |
| rad2deg | convert radians into degree |
| |
Exit:
Sine of angles in the array: [0.00000000e + 00 5.00000000e-01 7.07106781e-01 8.66025404e-01 1.00000000e + 00 1.22464680e-16] Inverse Sine of sine values: [0.00000000e + 00 3.00000000e + 01 4.50000000e + 01 6.00000000e + 01 9.00000000e + 01 7.01670930e-15] Sine hyperbolic of angles in the array: [0. 0.54785347 0.86867096 1.24936705 2.3012989 11.54873936] Inverse Sine hyperbolicten: [0. 0.52085606 0.76347124 0.9848655 right triangle is: 5.0
Statistical functions:
These functions are used to calculate the mean , mean -median-mode-in-python-without-libraries/">median, variance, minimum of array elements. Includes features such as
| Function | Description |
|---|---|
| amin, amax | returns minimum or maximum of an array or along an axis |
| ptp | returns range of values (maximum-minimum) of an array or along an axis |
| percentile (a, p, axis) | calculate pth percentile of array or along specified axis |
| mean -median-mode-in-python-without-libraries/">median | compute mean -median-mode-in-python-without-libraries/">median of data along specified axis |
| mean | compute mean of data along specified axis |
| std | compute standard deviation of data along specified axis |
| var | compute variance of data along specified axis |
| average | compute average of data along specified axis |
| |
Exit:
Minimum and maximum weight of the students: 45.0 73.25 Range of the weight of the students: 28.25 Weight below which 70% student fall: 55.317 Mean weight of the students: 54.3225 Median weight of the students: 51.6 Standard deviation of weight of the students: 8.05277397857 Variance of weight of the students: 64.84716875 Average weight of the students: 54.3225
Bit-tiddling functions:
These functions take integer values as input arguments and you perform bitwise operations on the binary representations of these integers. Includes features such as
| Function | Description |
|---|---|
| bitwise_and | performs bitwise and operation on two array elements |
| bitwies_or | performs bitwise or operation on two array elements |
| bitwise_xor | performs bitwise xor operation on two array elements |
| invert | performs bitwise inversion of an array elements |
| left_shift | shift the bits of elements to left |
| right_shift | shift the bits of elements to left |
| |
Exit:
bitwise_and of two arrays: [0 2 4 6 8 16 32] bitwise_or of two arrays: [1 3 5 7 9 17 33] bitwise_xor of two arrays: [1 1 1 1 1 1 1] inversion of even no. array: [-1 -3 -5 -7 -9 -17 -33] left_shift of even no. array: [0 4 8 12 16 32 64] right_shift of even no. array: [0 1 2 3 4 8 16]
