Programming Articles - Page 776 of 3363

To test array values for NaT, use the numpy.isnat() method in Python Numpy. The new location where we will store the result is a new array.The condition is broadcast over the input. At locations where the condition is True, the out array will be set to the ufunc result. Elsewhere, the out array will retain its original value. Note that if an uninitialized out array is created via the default out=None, locations within it where the condition is False will remain uninitialized.The out is a location into which the result is stored. If provided, it must have a shape that ... Read More

To test array for NaT, use the numpy.isnat() method in Python Numpy. The condition is broadcast over the input. At locations where the condition is True, the out array will be set to the ufunc result. Elsewhere, the out array will retain its original value. Note that if an uninitialized out array is created via the default out=None, locations within it where the condition is False will remain uninitialized.The out is a location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is ... Read More

To test element-wise for NaT, use the numpy.isnat() method in Python Numpy. It checks the value for datetime or timedelta data type.The condition is broadcast over the input. At locations where the condition is True, the out array will be set to the ufunc result. Elsewhere, the out array will retain its original value. Note that if an uninitialized out array is created via the default out=None, locations within it where the condition is False will remain uninitialized.StepsAt first, import the required library −import numpy as npTo test element-wise for NaT, use the numpy.isnat() method in Python Numpy. It checks ... Read More

To test element-wise for NaN, use the numpy.isnan() method in Python Numpy. Returns True where x is NaN, false otherwise. This is a scalar if x is a scalar. The condition is broadcast over the input. At locations where the condition is True, the out array will be set to the ufunc result. Elsewhere, the out array will retain its original value. Note that if an uninitialized out array is created via the default out=None, locations within it where the condition is False will remain uninitialized.NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic (IEEE 754). This means that ... Read More

To test array values for infiniteness, use the numpy.isinf() method in Python Numpy. The new location where we will store the result is a new array. Returns a boolean array of the same shape as x, True where x == +/-inf, otherwise False.NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic (IEEE 754). Errors result if the second argument is supplied when the first argument is a scalar, or if the first and second arguments have different shapes.StepsAt first, import the required library −import numpy as npCreate an array with some inf values −arr = np.array([1, 2, 10, 50, ... Read More

To test array for positive or negative infinity, use the numpy.isinf() method in Python Numpy. Returns a boolean array of the same shape as x, True where x == +/-inf, otherwise False.NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic (IEEE 754). Errors result if the second argument is supplied when the first argument is a scalar, or if the first and second arguments have different shapes.StepsAt first, import the required library −import numpy as npCreate an array with some inf values −arr = np.array([1, 2, 10, 50, -np.inf, 0., np.inf]) Display the arrays −print("Array...", arr)Get the type of ... Read More

To return the x1 * 2**x2, element-wise, use the numpy.ldexp() method in Python Numpy. The 1st parameter X1 is the array of multipliers. The 2nd parameter X2 is the array of twos exponents. If x1.shape != x2.shape, they must be broadcastable to a common shape (which becomes the shape of the output).The out is a location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned. A tuple (possible only as a keyword argument) must have length equal to the number of ... Read More

To extract the fractional and integral parts of a specific array value, use the index value inside the numpy.modf() method. The fractional and integral parts are negative if the given number is negative.The out is a location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs.The condition is broadcast over the input. At locations where the condition is True, the out array will be ... Read More

To cube each element in an array., element-wise, use the numpy.power() method in Python. Here, the 1st parameter is the base and the 2nd exponents. Since, we want the cube, the exponent is 3.Raise each base in x1 to the positionally-corresponding power in x2. x1 and x2 must be broadcastable to the same shape. An integer type raised to a negative integer power will raise a ValueError. Negative values raised to a non-integral value will return nan. To get complex results, cast the input to complex, or specify the dtype to be complex.StepsAt first, import the required library −import numpy ... Read More

To power array elements of an array with a given value, use the numpy.power() method in Python. Here, the 1st parameter is the base and the 2nd exponents. The dtype parameter is used to set the output datatype.Raise each base in x1 to the positionally-corresponding power in x2. x1 and x2 must be broadcastable to the same shape. An integer type raised to a negative integer power will raise a ValueError. Negative values raised to a non-integral value will return nan. To get complex results, cast the input to complex, or specify the dtype to be complex.The condition is broadcast ... Read More