{"id":38465,"date":"2023-01-10T17:13:02","date_gmt":"2023-01-10T17:13:02","guid":{"rendered":"https:\/\/www.askpython.com\/?p=38465"},"modified":"2023-02-16T19:56:25","modified_gmt":"2023-02-16T19:56:25","slug":"numpy-real_if_close","status":"publish","type":"post","link":"https:\/\/www.askpython.com\/python-modules\/numpy\/numpy-real_if_close","title":{"rendered":"Numpy real_if_close – If the input is complex with all imaginary parts close to zero, return real parts"},"content":{"rendered":"\n

In this article, we implement the NumPy real_if_close function of the NumPy package in python<\/a>. Numpy consists of functions that can be utilized to perform operations on an array, numpy real_if_close returns the real part of a complex imaginary input. Below understand the syntax of NumPy real_if_close and implements a few of its examples. <\/p>\n\n\n\n

What is NumPy real_if_close?<\/h2>\n\n\n\n

If the input is complex with all imaginary parts close to zero, we use numpy.real_if_close<\/code> to return real parts of the input. “Close to zero” is defined as tol*(machine epsilon of the type for a). The return type is float if a has complex elements where a is the input array.<\/p>\n\n\n\n

Note: Machine epsilons <\/strong>represent the smallest positive float value greater than zero.<\/p>\n\n\n\n

Syntax<\/h3>\n\n\n
\nnp.real_if_close(a, tol=)\n<\/pre><\/div>\n\n\n
Parameters<\/h3>\n\n\n\n
Parameter<\/strong><\/td>Description<\/strong><\/td>Required\/Optional<\/strong><\/td><\/tr>
a<\/td>input array <\/td>Required <\/td><\/tr>
tol<\/td>tolerance in machine epsilons for the complex part of the input array elements<\/td>Required <\/td><\/tr><\/tbody><\/table>
Numpy real_if_close parameters<\/figcaption><\/figure>\n\n\n\n
Return Value<\/strong>: If the input array has complex elements real_if_close()<\/code> returns a float value.<\/p>\n\n\n\n
Examples of NumPy real_if_close<\/h2>\n\n\n\n
Start by importing numpy<\/strong><\/p>\n\n\n
\nimport numpy as np\narr = np.array([2.1 + 4e-14j, 5.2 + 3e-15j,10.4 + 10e-14j,15.5 + 15e-15j])\n<\/pre><\/div>\n\n\n
Displaying the details of the array <\/strong><\/p>\n\n\n
\nprint("Input Array: \\n",arr)\nprint("\\nDimensions of input array: \\n",arr.ndim)\nprint("\\nDatatype of input array: \\n",arr.dtype)\nprint("\\nShape of input array: \\n",arr.shape)\n<\/pre><\/div>\n\n\n
Output :<\/strong><\/p>\n\n\n
\nInput Array:\n [ 2.1+4.0e-14j  5.2+3.0e-15j 10.4+1.0e-13j 15.5+1.5e-14j]\n\nDimensions of input array:\n 1\n\nDatatype of input array:\n complex128\n\nShape of input array:\n (4,)\n<\/pre><\/div>\n\n\n
Example 1: Sample testing of numpy real_if_close<\/h3>\n\n\n
\nprint("\\n Result: \\n",np.real_if_close(arr, tol = 1000))\n<\/pre><\/div>\n\n\n
Here, the output will contain all the real parts of the elements of the array arr<\/code> since all the imaginary parts are too small.<\/p>\n\n\n\n
Output : <\/strong><\/p>\n\n\n
\nResult: \n[ 2.1 5.2 10.4 15.5]\n<\/pre><\/div>\n\n\n
Example 2: When the imaginary numbers are not close to zero.<\/h3>\n\n\n
\nimport numpy as np\n\narr = np.array([1+5j,3-6j])\n\n# Displaying teh deatils of array\nprint("Input Array: \\n",arr)\n\nprint("\\nDimensions of input array: \\n",arr.ndim)\nprint("\\nDatatype of  input array: \\n",arr.dtype)\nprint("\\nShape of input array: \\n",arr.shape)\n\n# implementing numpy.real_if_close in Python\nprint("\\nResult...\\n",np.real_if_close(arr, tol = 1000))\n<\/pre><\/div>\n\n\n
Since here the imaginary parts are significantly large, np.real_if_close()<\/code> returns back the original complex numbers.<\/p>\n\n\n\n
Output : <\/strong><\/p>\n\n\n
\nInput Array:\n [1.+5.j 3.-6.j]\n\nDimensions of input array:\n 1\n\nDatatype of input array:\n complex128\n\nShape of input array:\n (2,)\n\nResult...\n [1.+5.j 3.-6.j]\n<\/pre><\/div>\n\n\n
Conclusion<\/h2>\n\n\n\n
In this article, we came across the theoretical and practical implementation of Numpy real_if_close(), a function of NumPy in Python. This function helps to return real parts of input with data type float. Given the input is complex with all imaginary parts close to zero.<\/p>\n\n\n\n
Reference <\/h2>\n\n\n\n
https:\/\/numpy.org\/doc\/stable\/reference\/generated\/numpy.real_if_close.html<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
In this article, we implement the NumPy real_if_close function of the NumPy package in python. Numpy consists of functions that can be utilized to perform operations on an array, numpy real_if_close returns the real part of a complex imaginary input. Below understand the syntax of NumPy real_if_close and implements a few of its examples. What […]<\/p>\n","protected":false},"author":52,"featured_media":39293,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[93],"tags":[],"class_list":["post-38465","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-numpy"],"blocksy_meta":[],"_links":{"self":[{"href":"https:\/\/www.askpython.com\/wp-json\/wp\/v2\/posts\/38465","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.askpython.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.askpython.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.askpython.com\/wp-json\/wp\/v2\/users\/52"}],"replies":[{"embeddable":true,"href":"https:\/\/www.askpython.com\/wp-json\/wp\/v2\/comments?post=38465"}],"version-history":[{"count":0,"href":"https:\/\/www.askpython.com\/wp-json\/wp\/v2\/posts\/38465\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.askpython.com\/wp-json\/wp\/v2\/media\/39293"}],"wp:attachment":[{"href":"https:\/\/www.askpython.com\/wp-json\/wp\/v2\/media?parent=38465"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.askpython.com\/wp-json\/wp\/v2\/categories?post=38465"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.askpython.com\/wp-json\/wp\/v2\/tags?post=38465"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}