![\"example13\"](\"https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2018\/12\/example13.png?resize=528%2C528\")
<\/p>\n<\/p>\n
\r\nimport os\r\nimport matplotlib.pyplot as plt\r\nimport numpy as np\r\nos.chdir('\/home\/vg\/Downloads\/projects\/ex13')\r\nos.getcwd()\r\nfig,axes = plt.subplots(2,2,figsize=(6,6),sharex=True,sharey=True,squeeze=False) \r\nx1=np.random.randn(100)\r\nx2=np.random.randn(100)\r\naxes[0,0].set_title("Uncorrelated")\r\naxes[0,0].scatter(x1,x2)\r\naxes[0,1].set_title("Weakly positively correlated")\r\naxes[0,1].scatter(x1,x1+x2)\r\naxes[1,0].set_title("Weakly negatively correlated")\r\naxes[1,0].scatter(x1,-x1+x2)\r\naxes[1,1].set_title("Strongly correlated")\r\naxes[1,1].scatter(x1,x1+0.15*x2)\r\naxes[1,1].set_xlabel("x")\r\naxes[1,0].set_xlabel("x")\r\naxes[0,0].set_ylabel("y")\r\naxes[1,0].set_ylabel("y")\r\nplt.subplots_adjust(left=0.1,right=0.95,bottom=0.1,top=0.95,wspace=0.1,hspace=0.2)\r\nplt.savefig("example13.png", dpi=100)\r\nplt.show()\r\nplt.close()\r\n<\/pre>\n","protected":false},"excerpt":{"rendered":"import os import matplotlib.pyplot as plt import numpy as np os.chdir(‘\/home\/vg\/Downloads\/projects\/ex13’) os.getcwd() fig,axes = plt.subplots(2,2,figsize=(6,6),sharex=True,sharey=True,squeeze=False) x1=np.random.randn(100) x2=np.random.randn(100) axes[0,0].set_title("Uncorrelated") axes[0,0].scatter(x1,x2) axes[0,1].set_title("Weakly positively correlated") axes[0,1].scatter(x1,x1+x2) axes[1,0].set_title("Weakly negatively correlated") axes[1,0].scatter(x1,-x1+x2) axes[1,1].set_title("Strongly correlated") axes[1,1].scatter(x1,x1+0.15*x2) axes[1,1].set_xlabel("x") axes[1,0].set_xlabel("x") axes[0,0].set_ylabel("y") axes[1,0].set_ylabel("y") plt.subplots_adjust(left=0.1,right=0.95,bottom=0.1,top=0.95,wspace=0.1,hspace=0.2) plt.savefig("example13.png", dpi=100) plt.show() plt.close()<\/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_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":"","jetpack_post_was_ever_published":false},"categories":[2],"tags":[70],"class_list":["post-85","post","type-post","status-publish","format-standard","hentry","category-python","tag-matplotlib"],"modified_by":"gantovnik","jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/p8bH0k-1n","jetpack_likes_enabled":true,"jetpack-related-posts":[{"id":136,"url":"https:\/\/gantovnik.com\/bio-tips\/2019\/01\/multivariate-interpolation\/","url_meta":{"origin":85,"position":0},"title":"Multivariate interpolation","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\\ex28') os.getcwd() x = y = np.linspace(-2, 2, 20) def f(x, y): return np.exp(-(x + .5)**2 - 2*(y + .5)**2) - np.exp(-(x - .5)**2 - 2*(y - .5)**2) X, Y = np.meshgrid(x, y) # simulate noisy\u2026","rel":"","context":"In "python"","block_context":{"text":"python","link":"https:\/\/gantovnik.com\/bio-tips\/category\/python\/"},"img":{"alt_text":"example28","src":"https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2019\/01\/example28.png?resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2019\/01\/example28.png?resize=350%2C200 1x, https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2019\/01\/example28.png?resize=525%2C300 1.5x"},"classes":[]},{"id":139,"url":"https:\/\/gantovnik.com\/bio-tips\/2019\/01\/multidimensional-spline\/","url_meta":{"origin":85,"position":1},"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 "python"","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":232,"url":"https:\/\/gantovnik.com\/bio-tips\/2019\/01\/regression\/","url_meta":{"origin":85,"position":2},"title":"#47 Regression","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.model_selection import train_test_split from sklearn import linear_model from sklearn import metrics from sklearn import tree from sklearn import neighbors from sklearn import svm from sklearn import ensemble from sklearn import cluster import seaborn\u2026","rel":"","context":"In "python"","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\/example47_2.png?resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2019\/01\/example47_2.png?resize=350%2C200 1x, https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2019\/01\/example47_2.png?resize=525%2C300 1.5x, https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2019\/01\/example47_2.png?resize=700%2C400 2x, https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2019\/01\/example47_2.png?resize=1050%2C600 3x"},"classes":[]},{"id":93,"url":"https:\/\/gantovnik.com\/bio-tips\/2018\/12\/plots-of-nonlinear-functions\/","url_meta":{"origin":85,"position":3},"title":"Plots of nonlinear functions","author":"gantovnik","date":"2018-12-31","format":false,"excerpt":"import os import matplotlib.pyplot as plt import numpy as np os.chdir('\/home\/vg\/Downloads\/projects\/ex15') os.getcwd() #define model parameters x=np.linspace(-2,2,1000) #examples of nonlinear functions f1=x**2-x-1 f2=x**3-3*np.sin(x) f3=np.exp(x)-2 f4=1-x**2+np.sin(50\/(1+x**2)) fig,axes=plt.subplots(1,4,figsize=(12,3),sharey=True) for n,f in enumerate([f1,f2,f3,f4]): axes[n].plot(x,f,lw=1.5) axes[n].axhline(0,ls=':',color='k') axes[n].set_ylim(-5,5) axes[n].set_xticks([-2,-1,0,1,2]) axes[n].set_xlabel(r'$x$',fontsize=18) axes[0].set_ylabel(r'$f(x)$',fontsize=18) titles=[r'$f(x)=x^2-x-1$',r'$f(x)=x^3-3\\sin(x)$',r'$f(x)=\\exp(x)-2$', r'$f(x)=\\sin\\left(50\/(1+x^2)\\right)+1-x^2$'] for n,title in enumerate(titles): axes[n].set_title(title) plt.savefig(\"example15.png\", dpi=100) plt.show() plt.close()","rel":"","context":"In "python"","block_context":{"text":"python","link":"https:\/\/gantovnik.com\/bio-tips\/category\/python\/"},"img":{"alt_text":"example15","src":"https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2018\/12\/example15.png?resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2018\/12\/example15.png?resize=350%2C200 1x, https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2018\/12\/example15.png?resize=525%2C300 1.5x"},"classes":[]},{"id":1185,"url":"https:\/\/gantovnik.com\/bio-tips\/2021\/11\/204-mandelbrot-fractal-using-python-2-2-2\/","url_meta":{"origin":85,"position":4},"title":"#207 Zoom region inset axes","author":"gantovnik","date":"2021-11-27","format":false,"excerpt":"[code language=\"python\"] from matplotlib import cbook import matplotlib.pyplot as plt import numpy as np def get_demo_image(): z = cbook.get_sample_data(\"axes_grid\/bivariate_normal.npy\", np_load=True) # z is a numpy array of 15x15 return z, (-3, 4, -4, 3) fig, ax = plt.subplots(figsize=[5, 4]) # make data Z, extent = get_demo_image() Z2 = np.zeros((150, 150))\u2026","rel":"","context":"In "python"","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\/2021\/11\/ex207.png?resize=350%2C200&ssl=1","width":350,"height":200},"classes":[]},{"id":243,"url":"https:\/\/gantovnik.com\/bio-tips\/2019\/01\/classification\/","url_meta":{"origin":85,"position":5},"title":"#48 Classification","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.model_selection import train_test_split from sklearn import linear_model from sklearn import metrics from sklearn import tree from sklearn import neighbors from sklearn import svm from sklearn import ensemble from sklearn import cluster import seaborn\u2026","rel":"","context":"In "python"","block_context":{"text":"python","link":"https:\/\/gantovnik.com\/bio-tips\/category\/python\/"},"img":{"alt_text":"example48","src":"https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2019\/01\/example48.png?resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2019\/01\/example48.png?resize=350%2C200 1x, https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2019\/01\/example48.png?resize=525%2C300 1.5x"},"classes":[]}],"_links":{"self":[{"href":"https:\/\/gantovnik.com\/bio-tips\/wp-json\/wp\/v2\/posts\/85","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/gantovnik.com\/bio-tips\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/gantovnik.com\/bio-tips\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/gantovnik.com\/bio-tips\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/gantovnik.com\/bio-tips\/wp-json\/wp\/v2\/comments?post=85"}],"version-history":[{"count":3,"href":"https:\/\/gantovnik.com\/bio-tips\/wp-json\/wp\/v2\/posts\/85\/revisions"}],"predecessor-version":[{"id":2029,"href":"https:\/\/gantovnik.com\/bio-tips\/wp-json\/wp\/v2\/posts\/85\/revisions\/2029"}],"wp:attachment":[{"href":"https:\/\/gantovnik.com\/bio-tips\/wp-json\/wp\/v2\/media?parent=85"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/gantovnik.com\/bio-tips\/wp-json\/wp\/v2\/categories?post=85"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/gantovnik.com\/bio-tips\/wp-json\/wp\/v2\/tags?post=85"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}