{"id":379,"date":"2019-02-07T11:26:32","date_gmt":"2019-02-07T19:26:32","guid":{"rendered":"https:\/\/gantovnik.com\/bio-tips\/?p=379"},"modified":"2021-11-12T15:23:27","modified_gmt":"2021-11-12T23:23:27","slug":"find-nearest-value-in-numpy-array","status":"publish","type":"post","link":"https:\/\/gantovnik.com\/bio-tips\/2019\/02\/find-nearest-value-in-numpy-array\/","title":{"rendered":"#54 Find nearest value in numpy array"},"content":{"rendered":"<pre class=\"brush: python; title: ; notranslate\" title=\"\">\r\nimport numpy as np\r\ndef find_nearest(array, value):\r\n    array = np.asarray(array)\r\n    idx = (np.abs(array - value)).idxmin()\r\n    return array&#x5B;idx]\r\n\r\narray = np.random.random(10)\r\nprint(array)\r\n# &#x5B; 0.21069679  0.61290182  0.63425412  0.84635244  0.91599191  0.00213826\r\n#   0.17104965  0.56874386  0.57319379  0.28719469]\r\n\r\nvalue = 0.5\r\n\r\nprint(find_nearest(array, value))\r\n# 0.568743859261\r\n<\/pre>\n","protected":false},"excerpt":{"rendered":"<p>import numpy as np def find_nearest(array, value): array = np.asarray(array) idx = (np.abs(array &#8211; value)).idxmin() return array&#x5B;idx] array = np.random.random(10) print(array) # &#x5B; 0.21069679 0.61290182 0.63425412 0.84635244 0.91599191 0.00213826 # 0.17104965 0.56874386 0.57319379 0.28719469] value = 0.5 print(find_nearest(array, value)) # 0.568743859261<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"nf_dc_page":"","_et_pb_use_builder":"","_et_pb_old_content":"","_et_gb_content_width":"","_lmt_disableupdate":"yes","_lmt_disable":"","jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[2],"tags":[],"class_list":["post-379","post","type-post","status-publish","format-standard","hentry","category-python"],"modified_by":"gantovnik","jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/p8bH0k-67","jetpack_likes_enabled":true,"jetpack-related-posts":[{"id":248,"url":"https:\/\/gantovnik.com\/bio-tips\/2019\/01\/clustering\/","url_meta":{"origin":379,"position":0},"title":"#49 Clustering","author":"gantovnik","date":"2019-01-13","format":false,"excerpt":"[code language=\"python\"] import os import numpy as np import matplotlib.pyplot as plt from sklearn import datasets from sklearn import metrics from sklearn import cluster os.chdir(r'D:\\projects\\wordpress\\ex49') os.getcwd() iris = datasets.load_iris() X, y = iris.data, iris.target np.random.seed(123) n_clusters = 3 c = cluster.KMeans(n_clusters=n_clusters) c.fit(X) y_pred = c.predict(X) print(y_pred[::8]) print(y[::8]) idx_0, idx_1, idx_2\u2026","rel":"","context":"In &quot;python&quot;","block_context":{"text":"python","link":"https:\/\/gantovnik.com\/bio-tips\/category\/python\/"},"img":{"alt_text":"example49","src":"https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2019\/01\/example49.png?resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2019\/01\/example49.png?resize=350%2C200 1x, https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2019\/01\/example49.png?resize=525%2C300 1.5x"},"classes":[]},{"id":101,"url":"https:\/\/gantovnik.com\/bio-tips\/2018\/12\/solution-of-system-of-nonlinear-equations\/","url_meta":{"origin":379,"position":1},"title":"Solution of system of nonlinear equations","author":"gantovnik","date":"2018-12-31","format":false,"excerpt":"import os import matplotlib.pyplot as plt import numpy as np import scipy os.chdir('\/home\/vg\/Downloads\/projects\/ex17') os.getcwd() def f(x): return [x[1]-x[0]**3-2*x[0]**2+1,x[1]+x[0]**2-1] tol=0.1 a,b=-2,2 x=np.linspace(-3,2,5000) y1=x**3+2*x**2-1 y2=-x**2+1 fig,ax=plt.subplots(figsize=(8,4)) ax.plot(x,y1,'k',lw=1.5) ax.plot(x,y2,'k',lw=1.5) sol1=scipy.optimize.fsolve(f,[-2,2]) sol2=scipy.optimize.fsolve(f,[1,-1]) sol3=scipy.optimize.fsolve(f,[-2,-5]) sols=[sol1,sol2,sol3] colors=['r','b','g'] for idx,s in enumerate(sols): ax.plot(s[0],s[1],colors[idx]+'*',markersize=15) for m in np.linspace(-4,3,80): for n in np.linspace(-20,20,40): x_guess=[m,n] sol=scipy.optimize.fsolve(f,x_guess) idx = (abs(sols-sol)**2).sum(axis=1).argmin() ax.plot(x_guess[0],x_guess[1],colors[idx]+'.')\u2026","rel":"","context":"In &quot;python&quot;","block_context":{"text":"python","link":"https:\/\/gantovnik.com\/bio-tips\/category\/python\/"},"img":{"alt_text":"example17","src":"https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2018\/12\/example17.png?resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2018\/12\/example17.png?resize=350%2C200 1x, https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2018\/12\/example17.png?resize=525%2C300 1.5x"},"classes":[]},{"id":139,"url":"https:\/\/gantovnik.com\/bio-tips\/2019\/01\/multidimensional-spline\/","url_meta":{"origin":379,"position":2},"title":"Multidimensional Spline","author":"gantovnik","date":"2019-01-04","format":false,"excerpt":"import os import matplotlib.pyplot as plt import numpy as np from scipy import interpolate os.chdir(r'D:\\data\\scripts\\web1\\ex29') os.getcwd() np.random.seed(115925231) x = y = np.linspace(-1, 1, 100) X, Y = np.meshgrid(x, y) def f(x, y): return np.exp(-x**2 - y**2) * np.cos(4*x) * np.sin(6*y) Z = f(X, Y) N = 500 xdata = np.random.uniform(-1,\u2026","rel":"","context":"In &quot;python&quot;","block_context":{"text":"python","link":"https:\/\/gantovnik.com\/bio-tips\/category\/python\/"},"img":{"alt_text":"example29","src":"https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2019\/01\/example29.png?resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2019\/01\/example29.png?resize=350%2C200 1x, https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2019\/01\/example29.png?resize=525%2C300 1.5x"},"classes":[]},{"id":304,"url":"https:\/\/gantovnik.com\/bio-tips\/2019\/01\/training-a-perceptron-via-scikit-learn\/","url_meta":{"origin":379,"position":3},"title":"#53 Training a perceptron via scikit-learn","author":"gantovnik","date":"2019-01-22","format":false,"excerpt":"[code language=\"python\"] import os import matplotlib.pyplot as plt import numpy as np from sklearn import datasets os.chdir(r'D:\\projects\\wordpress\\ex53') os.getcwd() iris = datasets.load_iris() X = iris.data[:, [2, 3]] y = iris.target from sklearn.model_selection import train_test_split X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=0) from sklearn.preprocessing import StandardScaler sc = StandardScaler() sc.fit(X_train)\u2026","rel":"","context":"In &quot;python&quot;","block_context":{"text":"python","link":"https:\/\/gantovnik.com\/bio-tips\/category\/python\/"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2019\/01\/example53.png?resize=350%2C200&ssl=1","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2019\/01\/example53.png?resize=350%2C200&ssl=1 1x, https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2019\/01\/example53.png?resize=525%2C300&ssl=1 1.5x"},"classes":[]},{"id":187,"url":"https:\/\/gantovnik.com\/bio-tips\/2019\/01\/coupled-damped-springs\/","url_meta":{"origin":379,"position":4},"title":"Coupled damped springs","author":"gantovnik","date":"2019-01-09","format":false,"excerpt":"\u00a0 import os import numpy as np import matplotlib.pyplot as plt from scipy import integrate os.chdir(r'D:\\projects\\wordpress\\ex37') os.getcwd() def f(t, y, args): m1, k1, g1, m2, k2, g2 = args return [y[1], - k1\/m1 * y[0] + k2\/m1 * (y[2] - y[0]) - g1\/m1 * y[1], y[3], - k2\/m2 * (y[2]\u2026","rel":"","context":"In &quot;python&quot;","block_context":{"text":"python","link":"https:\/\/gantovnik.com\/bio-tips\/category\/python\/"},"img":{"alt_text":"example37","src":"https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2019\/01\/example37.png?resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2019\/01\/example37.png?resize=350%2C200 1x, https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2019\/01\/example37.png?resize=525%2C300 1.5x"},"classes":[]},{"id":193,"url":"https:\/\/gantovnik.com\/bio-tips\/2019\/01\/double-pendulum\/","url_meta":{"origin":379,"position":5},"title":"#39 Double pendulum using python","author":"gantovnik","date":"2019-01-10","format":false,"excerpt":"import os import numpy as np import matplotlib.pyplot as plt from scipy import integrate import sympy os.chdir(r'D:\\projects\\wordpress\\ex39') os.getcwd() t, g, m1, l1, m2, l2 = sympy.symbols(\"t, g, m_1, l_1, m_2, l_2\") theta1, theta2 = sympy.symbols(\"theta_1, theta_2\", cls=sympy.Function) ode1 = sympy.Eq((m1+m2)*l1 * theta1(t).diff(t,t) + m2*l2 * theta2(t).diff(t,t) + m2*l2 * theta2(t).diff(t)**2\u2026","rel":"","context":"In &quot;python&quot;","block_context":{"text":"python","link":"https:\/\/gantovnik.com\/bio-tips\/category\/python\/"},"img":{"alt_text":"example39","src":"https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2019\/01\/example39.png?resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2019\/01\/example39.png?resize=350%2C200 1x, https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2019\/01\/example39.png?resize=525%2C300 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