linear-regression-data.py

x  = np.array([[ 0.06169621],
       [-0.05147406],
       [ 0.04445121],
       [-0.01159501],
       [-0.03638469],
       [-0.04069594],
       [-0.04716281],
       [-0.00189471],
       [ 0.06169621],
       [ 0.03906215],
       [-0.08380842],
       [ 0.01750591],
       [-0.02884001],
       [-0.00189471],
       [-0.02560657],
       [-0.01806189],
       [ 0.04229559],
       [ 0.01211685],
       [-0.0105172 ],
       [-0.01806189],
       [-0.05686312],
       [-0.02237314],
       [-0.00405033],
       [ 0.06061839],
       [ 0.03582872],
       [-0.01267283],
       [-0.07734155],
       [ 0.05954058],
       [-0.02129532],
       [-0.00620595],
       [ 0.04445121],
       [-0.06548562],
       [ 0.12528712],
       [-0.05039625],
       [-0.06332999],
       [-0.03099563],
       [ 0.02289497],
       [ 0.01103904],
       [ 0.07139652],
       [ 0.01427248],
       [-0.00836158],
       [-0.06764124],
       [-0.0105172 ],
       [-0.02345095],
       [ 0.06816308],
       [-0.03530688],
       [-0.01159501],
       [-0.0730303 ],
       [-0.04177375],
       [ 0.01427248],
       [-0.00728377],
       [ 0.0164281 ],
       [-0.00943939],
       [-0.01590626],
       [ 0.0250506 ],
       [-0.04931844],
       [ 0.04121778],
       [-0.06332999],
       [-0.06440781],
       [-0.02560657],
       [-0.00405033],
       [ 0.00457217],
       [-0.00728377],
       [-0.0374625 ],
       [-0.02560657],
       [-0.02452876],
       [-0.01806189],
       [-0.01482845],
       [-0.02991782],
       [-0.046085  ],
       [-0.06979687],
       [ 0.03367309],
       [-0.00405033],
       [-0.02021751],
       [ 0.00241654],
       [-0.03099563],
       [ 0.02828403],
       [-0.03638469],
       [-0.05794093],
       [-0.0374625 ],
       [ 0.01211685],
       [-0.02237314],
       [-0.03530688],
       [ 0.00996123],
       [-0.03961813],
       [ 0.07139652],
       [-0.07518593],
       [-0.00620595],
       [-0.04069594],
       [-0.04824063],
       [-0.02560657],
       [ 0.0519959 ],
       [ 0.00457217],
       [-0.06440781],
       [-0.01698407],
       [-0.05794093],
       [ 0.00996123],
       [ 0.08864151],
       [-0.00512814],
       [-0.06440781],
       [ 0.01750591],
       [-0.04500719],
       [ 0.02828403],
       [ 0.04121778],
       [ 0.06492964],
       [-0.03207344],
       [-0.07626374],
       [ 0.04984027],
       [ 0.04552903],
       [-0.00943939],
       [-0.03207344],
       [ 0.00457217],
       [ 0.02073935],
       [ 0.01427248],
       [ 0.11019775],
       [ 0.00133873],
       [ 0.05846277],
       [-0.02129532],
       [-0.0105172 ],
       [-0.04716281],
       [ 0.00457217],
       [ 0.01750591],
       [ 0.08109682],
       [ 0.0347509 ],
       [ 0.02397278],
       [-0.00836158],
       [-0.06117437],
       [-0.00189471],
       [-0.06225218],
       [ 0.0164281 ],
       [ 0.09618619],
       [-0.06979687],
       [-0.02129532],
       [-0.05362969],
       [ 0.0433734 ],
       [ 0.05630715],
       [-0.0816528 ],
       [ 0.04984027],
       [ 0.11127556],
       [ 0.06169621],
       [ 0.01427248],
       [ 0.04768465],
       [ 0.01211685],
       [ 0.00564998],
       [ 0.04660684],
       [ 0.12852056],
       [ 0.05954058],
       [ 0.09295276],
       [ 0.01535029],
       [-0.00512814],
       [ 0.0703187 ],
       [-0.00405033],
       [-0.00081689],
       [-0.04392938],
       [ 0.02073935],
       [ 0.06061839],
       [-0.0105172 ],
       [-0.03315126],
       [-0.06548562],
       [ 0.0433734 ],
       [-0.06225218],
       [ 0.06385183],
       [ 0.03043966],
       [ 0.07247433],
       [-0.0191397 ],
       [-0.06656343],
       [-0.06009656],
       [ 0.06924089],
       [ 0.05954058],
       [-0.02668438],
       [-0.02021751],
       [-0.046085  ],
       [ 0.07139652],
       [-0.07949718],
       [ 0.00996123],
       [-0.03854032],
       [ 0.01966154],
       [ 0.02720622],
       [-0.00836158],
       [-0.01590626],
       [ 0.00457217],
       [-0.04285156],
       [ 0.00564998],
       [-0.03530688],
       [ 0.02397278],
       [-0.01806189],
       [ 0.04229559],
       [-0.0547075 ],
       [-0.00297252],
       [-0.06656343],
       [-0.01267283],
       [-0.04177375],
       [-0.03099563],
       [-0.00512814],
       [-0.05901875],
       [ 0.0250506 ],
       [-0.046085  ],
       [ 0.00349435],
       [ 0.05415152],
       [-0.04500719],
       [-0.05794093],
       [-0.05578531],
       [ 0.00133873],
       [ 0.03043966],
       [ 0.00672779],
       [ 0.04660684],
       [ 0.02612841],
       [ 0.04552903],
       [ 0.04013997],
       [-0.01806189],
       [ 0.01427248],
       [ 0.03690653],
       [ 0.00349435],
       [-0.07087468],
       [-0.03315126],
       [ 0.09403057],
       [ 0.03582872],
       [ 0.03151747],
       [-0.06548562],
       [-0.04177375],
       [-0.03961813],
       [-0.03854032],
       [-0.02560657],
       [-0.02345095],
       [-0.06656343],
       [ 0.03259528],
       [-0.046085  ],
       [-0.02991782],
       [-0.01267283],
       [-0.01590626],
       [ 0.07139652],
       [-0.03099563],
       [ 0.00026092],
       [ 0.03690653],
       [ 0.03906215],
       [-0.01482845],
       [ 0.00672779],
       [-0.06871905],
       [-0.00943939],
       [ 0.01966154],
       [ 0.07462995],
       [-0.00836158],
       [-0.02345095],
       [-0.046085  ],
       [ 0.05415152],
       [-0.03530688],
       [-0.03207344],
       [-0.0816528 ],
       [ 0.04768465],
       [ 0.06061839],
       [ 0.05630715],
       [ 0.09834182],
       [ 0.05954058],
       [ 0.03367309],
       [ 0.05630715],
       [-0.06548562],
       [ 0.16085492],
       [-0.05578531],
       [-0.02452876],
       [-0.03638469],
       [-0.00836158],
       [-0.04177375],
       [ 0.12744274],
       [-0.07734155],
       [ 0.02828403],
       [-0.02560657],
       [-0.06225218],
       [-0.00081689],
       [ 0.08864151],
       [-0.03207344],
       [ 0.03043966],
       [ 0.00888341],
       [ 0.00672779],
       [-0.02021751],
       [-0.02452876],
       [-0.01159501],
       [ 0.02612841],
       [-0.05901875],
       [-0.03638469],
       [-0.02452876],
       [ 0.01858372],
       [-0.0902753 ],
       [-0.00512814],
       [-0.05255187],
       [-0.02237314],
       [-0.02021751],
       [-0.0547075 ],
       [-0.00620595],
       [-0.01698407],
       [ 0.05522933],
       [ 0.07678558],
       [ 0.01858372],
       [-0.02237314],
       [ 0.09295276],
       [-0.03099563],
       [ 0.03906215],
       [-0.06117437],
       [-0.00836158],
       [-0.0374625 ],
       [-0.01375064],
       [ 0.07355214],
       [-0.02452876],
       [ 0.03367309],
       [ 0.0347509 ],
       [-0.03854032],
       [-0.03961813],
       [-0.00189471],
       [-0.03099563],
       [-0.046085  ],
       [ 0.00133873],
       [ 0.06492964],
       [ 0.04013997],
       [-0.02345095],
       [ 0.05307371],
       [ 0.04013997],
       [-0.02021751],
       [ 0.01427248],
       [-0.03422907],
       [ 0.00672779],
       [ 0.00457217],
       [ 0.03043966],
       [ 0.0519959 ],
       [ 0.06169621],
       [-0.00728377],
       [ 0.00564998],
       [ 0.05415152],
       [-0.00836158],
       [ 0.114509  ],
       [ 0.06708527],
       [-0.05578531],
       [ 0.03043966],
       [-0.02560657],
       [ 0.10480869],
       [-0.00620595],
       [-0.04716281],
       [-0.04824063],
       [ 0.08540807],
       [-0.01267283],
       [-0.03315126],
       [-0.00728377],
       [-0.01375064],
       [ 0.05954058],
       [ 0.02181716],
       [ 0.01858372],
       [-0.01159501],
       [-0.00297252],
       [ 0.01750591],
       [-0.02991782],
       [-0.02021751],
       [-0.05794093],
       [ 0.06061839],
       [-0.04069594],
       [-0.07195249],
       [-0.05578531],
       [ 0.04552903],
       [-0.00943939],
       [-0.03315126],
       [ 0.04984027],
       [-0.08488624],
       [ 0.00564998],
       [ 0.02073935],
       [-0.00728377],
       [ 0.10480869],
       [-0.02452876],
       [-0.00620595],
       [-0.03854032],
       [ 0.13714305],
       [ 0.17055523],
       [ 0.00241654],
       [ 0.03798434],
       [-0.05794093],
       [-0.00943939],
       [-0.02345095],
       [-0.0105172 ],
       [-0.03422907],
       [-0.00297252],
       [ 0.06816308],
       [ 0.00996123],
       [ 0.00241654],
       [-0.03854032],
       [ 0.02612841],
       [-0.08919748],
       [ 0.06061839],
       [-0.02884001],
       [-0.02991782],
       [-0.0191397 ],
       [-0.04069594],
       [ 0.01535029],
       [-0.02452876],
       [ 0.00133873],
       [ 0.06924089],
       [-0.06979687],
       [-0.02991782],
       [-0.046085  ],
       [ 0.01858372],
       [ 0.00133873],
       [-0.03099563],
       [-0.00405033],
       [ 0.01535029],
       [ 0.02289497],
       [ 0.04552903],
       [-0.04500719],
       [-0.03315126],
       [ 0.097264  ],
       [ 0.05415152],
       [ 0.12313149],
       [-0.08057499],
       [ 0.09295276],
       [-0.05039625],
       [-0.01159501],
       [-0.0277622 ],
       [ 0.05846277],
       [ 0.08540807],
       [-0.00081689],
       [ 0.00672779],
       [ 0.00888341],
       [ 0.08001901],
       [ 0.07139652],
       [-0.02452876],
       [-0.0547075 ],
       [-0.03638469],
       [ 0.0164281 ],
       [ 0.07786339],
       [-0.03961813],
       [ 0.01103904],
       [-0.04069594],
       [-0.03422907],
       [ 0.00564998],
       [ 0.08864151],
       [-0.03315126],
       [-0.05686312],
       [-0.03099563],
       [ 0.05522933],
       [-0.06009656],
       [ 0.00133873],
       [-0.02345095],
       [-0.07410811],
       [ 0.01966154],
       [-0.01590626],
       [-0.01590626],
       [ 0.03906215],
       [-0.0730303 ]])

 
y = np.array([151.,  75., 141., 206., 135.,  97., 138.,  63., 110., 310., 101.,
        69., 179., 185., 118., 171., 166., 144.,  97., 168.,  68.,  49.,
        68., 245., 184., 202., 137.,  85., 131., 283., 129.,  59., 341.,
        87.,  65., 102., 265., 276., 252.,  90., 100.,  55.,  61.,  92.,
       259.,  53., 190., 142.,  75., 142., 155., 225.,  59., 104., 182.,
       128.,  52.,  37., 170., 170.,  61., 144.,  52., 128.,  71., 163.,
       150.,  97., 160., 178.,  48., 270., 202., 111.,  85.,  42., 170.,
       200., 252., 113., 143.,  51.,  52., 210.,  65., 141.,  55., 134.,
        42., 111.,  98., 164.,  48.,  96.,  90., 162., 150., 279.,  92.,
        83., 128., 102., 302., 198.,  95.,  53., 134., 144., 232.,  81.,
       104.,  59., 246., 297., 258., 229., 275., 281., 179., 200., 200.,
       173., 180.,  84., 121., 161.,  99., 109., 115., 268., 274., 158.,
       107.,  83., 103., 272.,  85., 280., 336., 281., 118., 317., 235.,
        60., 174., 259., 178., 128.,  96., 126., 288.,  88., 292.,  71.,
       197., 186.,  25.,  84.,  96., 195.,  53., 217., 172., 131., 214.,
        59.,  70., 220., 268., 152.,  47.,  74., 295., 101., 151., 127.,
       237., 225.,  81., 151., 107.,  64., 138., 185., 265., 101., 137.,
       143., 141.,  79., 292., 178.,  91., 116.,  86., 122.,  72., 129.,
       142.,  90., 158.,  39., 196., 222., 277.,  99., 196., 202., 155.,
        77., 191.,  70.,  73.,  49.,  65., 263., 248., 296., 214., 185.,
        78.,  93., 252., 150.,  77., 208.,  77., 108., 160.,  53., 220.,
       154., 259.,  90., 246., 124.,  67.,  72., 257., 262., 275., 177.,
        71.,  47., 187., 125.,  78.,  51., 258., 215., 303., 243.,  91.,
       150., 310., 153., 346.,  63.,  89.,  50.,  39., 103., 308., 116.,
       145.,  74.,  45., 115., 264.,  87., 202., 127., 182., 241.,  66.,
        94., 283.,  64., 102., 200., 265.,  94., 230., 181., 156., 233.,
        60., 219.,  80.,  68., 332., 248.,  84., 200.,  55.,  85.,  89.,
        31., 129.,  83., 275.,  65., 198., 236., 253., 124.,  44., 172.,
       114., 142., 109., 180., 144., 163., 147.,  97., 220., 190., 109.,
       191., 122., 230., 242., 248., 249., 192., 131., 237.,  78., 135.,
       244., 199., 270., 164.,  72.,  96., 306.,  91., 214.,  95., 216.,
       263., 178., 113., 200., 139., 139.,  88., 148.,  88., 243.,  71.,
        77., 109., 272.,  60.,  54., 221.,  90., 311., 281., 182., 321.,
        58., 262., 206., 233., 242., 123., 167.,  63., 197.,  71., 168.,
       140., 217., 121., 235., 245.,  40.,  52., 104., 132.,  88.,  69.,
       219.,  72., 201., 110.,  51., 277.,  63., 118.,  69., 273., 258.,
        43., 198., 242., 232., 175.,  93., 168., 275., 293., 281.,  72.,
       140., 189., 181., 209., 136., 261., 113., 131., 174., 257.,  55.,
        84.,  42., 146., 212., 233.,  91., 111., 152., 120.,  67., 310.,
        94., 183.,  66., 173.,  72.,  49.,  64.,  48., 178., 104., 132.,
       220.,  57.])