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Found 1204 Articles for Numpy
![AmitDiwan](https://www.tutorialspoint.com/assets/profiles/123055/profile/60_187394-1565938756.jpg)
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To return the result of the power to which the input value is raised with scimath, use the scimath.power() method in Python. Returns x to the power p, i.e. the result of x**p. If x and p are scalars, so is out, otherwise an array is returned.If x contains negative values, the output is converted to the complex domain. The parameter x is the input value. The parameter p is the power(s) to which x is raised. If x contains multiple values, p has to either be a scalar, or contain the same number of values as x. In the ... Read More
![AmitDiwan](https://www.tutorialspoint.com/assets/profiles/123055/profile/60_187394-1565938756.jpg)
161 Views
To return the result of the power to which the input value is raised with scimath, use the scimath.power() method in Python. Returns x to the power p, i.e. the result of x**p. If x and p are scalars, so is out, otherwise an array is returned. If x contains negative values, the output is converted to the complex domain. The parameter x is the input valueThe parameter p is the power(s) to which x is raised. If x contains multiple values, p has to either be a scalar, or contain the same number of values as x. In the ... Read More
![AmitDiwan](https://www.tutorialspoint.com/assets/profiles/123055/profile/60_187394-1565938756.jpg)
81 Views
To return the result of the power to which the input value is raised with scimath, use the scimath.power() method in Python. Returns x to the power p, i.e. the result of x**p. If x and p are scalars, so is out, otherwise an array is returned. If x contains negative values, the output is converted to the complex domain. The parameter x is the input valueThe parameter p is the power(s) to which x is raised. If x contains multiple values, p has to either be a scalar, or contain the same number of values as x. In the ... Read More
![AmitDiwan](https://www.tutorialspoint.com/assets/profiles/123055/profile/60_187394-1565938756.jpg)
116 Views
To compute the logarithm base 10 with scimath, use the scimath.log10() method in Python Numpy. The method returns the log base 10 of the x value(s). If x was a scalar, so is out, otherwise an array object is returned.For a log10() that returns NAN when real x < 0, use numpy.log10 (note, however, that otherwise numpy.log10 and this log10 are identical, i.e., both return -inf for x = 0, inf for x = inf, and, notably, the complex principle value if x.imag != 0). The 1st parameter, x is the value(s) whose log base 10 is (are) required.StepsAt first, ... Read More
![AmitDiwan](https://www.tutorialspoint.com/assets/profiles/123055/profile/60_187394-1565938756.jpg)
300 Views
To compute the logarithm base n with scimath, use the scimath.logn() method in Python Numpy. The method returns the log base n of the x value(s). If x was a scalar, so is out, otherwise an array is returned.If x contains negative inputs, the answer is computed and returned in the complex domain. The 1st parameter, n is the integer base(s) in which the log is taken. The 2nd parameter, x is the value(s) whose log base n is (are) required.StepsAt first, import the required libraries −import numpy as npCreating a numpy array using the array() method −arr = np.array([-4, ... Read More
![AmitDiwan](https://www.tutorialspoint.com/assets/profiles/123055/profile/60_187394-1565938756.jpg)
154 Views
To compute the logarithm base 2 with scimath, use the np.emath.log2() method in Python Numpy. The method returns the log base 2 of the x value(s). If x was a scalar, so is out, otherwise an array is returned. The 1st parameter, x is the value(s) whose log base 2 is (are) required.StepsAt first, import the required libraries −import numpy as npCreating a numpy array using the array() method −arr = np.array([np.inf, -np.inf, 16, np.exp(1), -np.exp(1), -32]) Display the array −print("Our Array...", arr)Check the Dimensions −print("Dimensions of our Array...", arr.ndim) Get the Datatype −print("Datatype of our Array object...", arr.dtype)Get the ... Read More
![AmitDiwan](https://www.tutorialspoint.com/assets/profiles/123055/profile/60_187394-1565938756.jpg)
112 Views
To compute the natural logarithm with scimath, use the np.emath.log() method in Python Numpy. The method returns the log of the x value(s). If x was a scalar, so is out, otherwise an array is returned. The 1st parameter, x is the value(s) whose log is (are) required.StepsAt first, import the required libraries −import numpy as npCreating a numpy array using the array() method −arr = np.array([np.inf, -np.inf, np.exp(1), -np.exp(1)]) Display the array −print("Our Array...", arr)Check the Dimensions −print("Dimensions of our Array...", arr.ndim) Get the Datatype −print("Datatype of our Array object...", arr.dtype)Get the Shape −print("Shape of our Array object...", arr.shape) ... Read More
![AmitDiwan](https://www.tutorialspoint.com/assets/profiles/123055/profile/60_187394-1565938756.jpg)
130 Views
To compute the square root of input, use the emath.sqrt() method in Python Numpy. The method returns the square root of x. If x was a scalar, so is out, otherwise an array is returned. The parameter x is the input value. For negative input elements, a complex value is returnedStepsAt first, import the required libraries −import numpy as npThe complex input explicity using complex() method −a = complex(-9.0, 0.0) Display the array −print("Display the complex value...", a)To compute the square root of input, use the emath.sqrt() method in Python Numpy −print("Result...", np.emath.sqrt(a)) Exampleimport numpy as np # Explicity ... Read More
![AmitDiwan](https://www.tutorialspoint.com/assets/profiles/123055/profile/60_187394-1565938756.jpg)
166 Views
To compute the square root of input, use the scimath.sqrt() method in Python Numpy. The method returns the square root of x. If x was a scalar, so is out, otherwise an array is returned. The parameter x is the input value. For negative input elements, a complex value is returnedStepsAt first, import the required libraries −import numpy as npCreating a numpy array using the array() method −arr = np.array([1, -4, -9, 16, -25, 36]) Display the array −print("Our Array...", arr)Check the Dimensions −print("Dimensions of our Array...", arr.ndim) Get the Datatype −print("Datatype of our Array object...", arr.dtype)Get the Shape −print("Shape ... Read More