diff options
| -rw-r--r-- | SARS.png | bin | 28850 -> 28280 bytes | |||
| -rw-r--r-- | data/SARS-Confirmed2.csv | 2 | ||||
| -rw-r--r-- | data/sars-confirmed.csv | 4 | ||||
| -rw-r--r-- | out/SARS-data.csv | 4 | ||||
| -rw-r--r-- | out/SARS-prediction.csv | 85 | ||||
| -rw-r--r-- | solver2.py | 2 |
6 files changed, 83 insertions, 14 deletions
| Binary files differ diff --git a/data/SARS-Confirmed2.csv b/data/SARS-Confirmed2.csv new file mode 100644 index 0000000..9bf50bb --- /dev/null +++ b/data/SARS-Confirmed2.csv @@ -0,0 +1,2 @@ +Country/Region,3/17/03,3/18/03,3/19/03,3/20/03,3/21/03,3/22/03,3/24/03,3/25/03,3/26/03,3/27/03,3/28/03,3/29/03,3/31/03,4/1/03,4/2/03,4/3/03,4/4/03,4/5/03,4/7/03,4/8/03,4/9/03,4/10/03,4/11/03,4/12/03,4/14/03,4/15/03,4/16/03,4/17/03,4/18/03,4/19/03,4/21/03,4/22/03,4/23/03,4/24/03,4/25/03,4/26/03,4/28/03,4/29/03,4/30/03,5/1/03,5/2/03,5/3/03,5/5/03,5/6/03,5/7/03,5/8/03,5/9/03,5/10/03,5/12/03,5/13/03,5/14/03,5/15/03,5/16/03,5/17/03,5/19/03,5/20/03,5/21/03,5/22/03,5/23/03,5/24/03,5/26/03,5/27/03,5/28/03,5/29/03,5/30/03,5/31/03,6/2/03,6/3/03,6/4/03,6/5/03,6/6/03,6/9/03,6/10/03,6/11/03,6/12/03,6/13/03,6/16/03,6/17/03,6/18/03,6/19/03,6/20/03,6/23/03,6/24/03,6/25/03,6/26/03,6/27/03,6/30/03,7/1/03,7/2/03,7/3/03,7/4/03,7/7/03,7/8/03,7/9/03,7/10/03,7/11/03,8/7/03 +Hong_Kong,95,123,150,173,203,222,260,286,316,367,425,470,530,685,708,734,761,800,883,928,970,998,1059,1108,1190,1232,1268,1297,1358,1358,1402,1434,1458,1488,1510,1527,1557,1572,1589,1600,1611,1621,1637,1646,1654,1661,1667,1674,1683,1689,1698,1703,1706,1710,1714,1718,1719,1722,1724,1724,1726,1728,1730,1732,1736,1739,1746,1747,1748,1748,1750,1753,1754,1754,1755,1755,1755,1755,1755,1755,1755,1755,1755,1755,1755,1755,1755,1755,1755,1755,1755,1755,1755,1755,1755,1755,1755 diff --git a/data/sars-confirmed.csv b/data/sars-confirmed.csv index 9bf50bb..4eeaf13 100644 --- a/data/sars-confirmed.csv +++ b/data/sars-confirmed.csv @@ -1,2 +1,2 @@ -Country/Region,3/17/03,3/18/03,3/19/03,3/20/03,3/21/03,3/22/03,3/24/03,3/25/03,3/26/03,3/27/03,3/28/03,3/29/03,3/31/03,4/1/03,4/2/03,4/3/03,4/4/03,4/5/03,4/7/03,4/8/03,4/9/03,4/10/03,4/11/03,4/12/03,4/14/03,4/15/03,4/16/03,4/17/03,4/18/03,4/19/03,4/21/03,4/22/03,4/23/03,4/24/03,4/25/03,4/26/03,4/28/03,4/29/03,4/30/03,5/1/03,5/2/03,5/3/03,5/5/03,5/6/03,5/7/03,5/8/03,5/9/03,5/10/03,5/12/03,5/13/03,5/14/03,5/15/03,5/16/03,5/17/03,5/19/03,5/20/03,5/21/03,5/22/03,5/23/03,5/24/03,5/26/03,5/27/03,5/28/03,5/29/03,5/30/03,5/31/03,6/2/03,6/3/03,6/4/03,6/5/03,6/6/03,6/9/03,6/10/03,6/11/03,6/12/03,6/13/03,6/16/03,6/17/03,6/18/03,6/19/03,6/20/03,6/23/03,6/24/03,6/25/03,6/26/03,6/27/03,6/30/03,7/1/03,7/2/03,7/3/03,7/4/03,7/7/03,7/8/03,7/9/03,7/10/03,7/11/03,8/7/03 -Hong_Kong,95,123,150,173,203,222,260,286,316,367,425,470,530,685,708,734,761,800,883,928,970,998,1059,1108,1190,1232,1268,1297,1358,1358,1402,1434,1458,1488,1510,1527,1557,1572,1589,1600,1611,1621,1637,1646,1654,1661,1667,1674,1683,1689,1698,1703,1706,1710,1714,1718,1719,1722,1724,1724,1726,1728,1730,1732,1736,1739,1746,1747,1748,1748,1750,1753,1754,1754,1755,1755,1755,1755,1755,1755,1755,1755,1755,1755,1755,1755,1755,1755,1755,1755,1755,1755,1755,1755,1755,1755,1755 +Country/Region,4/10/03,4/11/03,4/12/03,4/14/03,4/15/03,4/16/03,4/17/03,4/18/03,4/19/03,4/21/03,4/22/03,4/23/03,4/24/03,4/25/03,4/26/03,4/28/03,4/29/03,4/30/03,5/1/03,5/2/03,5/3/03,5/5/03,5/6/03,5/7/03,5/8/03,5/9/03,5/10/03,5/12/03,5/13/03,5/14/03,5/15/03,5/16/03,5/17/03,5/19/03,5/20/03,5/21/03,5/22/03,5/23/03,5/24/03,5/26/03,5/27/03,5/28/03,5/29/03,5/30/03,5/31/03,6/2/03,6/3/03,6/4/03,6/5/03,6/6/03,6/9/03,6/10/03,6/11/03,6/12/03,6/13/03,6/16/03,6/17/03,6/18/03,6/19/03,6/20/03,6/23/03,6/24/03,6/25/03,6/26/03,6/27/03,6/30/03,7/1/03,7/2/03,7/3/03,7/4/03,7/7/03,7/8/03,7/9/03,7/10/03,7/11/03,8/7/03 +Hong_Kong,998,1059,1108,1190,1232,1268,1297,1358,1358,1402,1434,1458,1488,1510,1527,1557,1572,1589,1600,1611,1621,1637,1646,1654,1661,1667,1674,1683,1689,1698,1703,1706,1710,1714,1718,1719,1722,1724,1724,1726,1728,1730,1732,1736,1739,1746,1747,1748,1748,1750,1753,1754,1754,1755,1755,1755,1755,1755,1755,1755,1755,1755,1755,1755,1755,1755,1755,1755,1755,1755,1755,1755,1755,1755,1755,1755 diff --git a/out/SARS-data.csv b/out/SARS-data.csv index f98e7f5..65b5f2f 100644 --- a/out/SARS-data.csv +++ b/out/SARS-data.csv @@ -1,3 +1,3 @@ Beta: 1e-08 -Gamma: 0.01700912239686379 -R0: 5.879198095396057e-07
\ No newline at end of file +Gamma: 0.0061248427719888315 +R0: 1.6326949723074842e-06
\ No newline at end of file diff --git a/out/SARS-prediction.csv b/out/SARS-prediction.csv index 2849d47..f677152 100644 --- a/out/SARS-prediction.csv +++ b/out/SARS-prediction.csv @@ -1,10 +1,77 @@ ,Actual,S,I,R -4/10/03,0.21148953068592058,13499.000074068588,0.9999259314124879,0.0 -4/11/03,0.2244162454873646,13499.000074058673,0.98306190629524,0.016864035031213732 -4/12/03,0.23479999999999998,13499.000074048927,0.9664822974727793,0.033443653600438765 -4/14/03,0.2521768953068592,13499.000074039344,0.9501823087970815,0.049743651858518506 -4/15/03,0.2610772563176895,13499.000074029924,0.9341572239618826,0.06576874611448988 -4/16/03,0.2687061371841155,13499.000074020661,0.9184024060302004,0.08152357330806109 -4/17/03,0.27485162454873646,13499.000074011556,0.9029132970915866,0.09701269135235983 -4/18/03,0.2877783393501805,13499.000074002603,0.8876854169726223,0.11224058042343865 -4/19/03,0.2877783393501805,13499.000073993802,0.872714359634142,0.12721164656305334 +4/10/03,0.1566473081148956,9999.0,1.0,0.0 +4/11/03,0.16622194318003453,9998.999999990032,0.9938938857782499,0.00610612419019138 +4/12/03,0.17391304347826086,9998.999999980124,0.9878250561849686,0.01217496369104556 +4/14/03,0.18678386438549677,9998.999999970278,0.9817932835629529,0.018206746160137382 +4/15/03,0.1933762360696908,9998.99999996049,0.9757983416361868,0.02420169787385227 +4/16/03,0.1990268403704285,9998.999999950764,0.9698400055077305,0.03016004372949699 +4/17/03,0.20357871605713387,9998.999999941096,0.9639180446502709,0.036082014254761215 +4/18/03,0.2131533511222728,9998.999999931486,0.958032229361117,0.0419678391527109 +4/19/03,0.2131533511222728,9998.999999921936,0.9521823415639332,0.04781773650003748 +4/21/03,0.2200596452676189,9998.999999912445,0.9463681643524197,0.05363192320339512 +4/22/03,0.22508240464605242,9998.99999990301,0.9405894819398969,0.05941061504981562 +4/23/03,0.22884947417987755,9998.999999893635,0.9348460796593057,0.0651540267067084 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+7/2/03,0.27546695966096374,9998.999999450503,0.6634089965460216,0.3365915529503593 +7/3/03,0.27546695966096374,9998.999999443891,0.6593581480002312,0.34064240810929924 +7/4/03,0.27546695966096374,9998.999999437317,0.6553320344454865,0.34466852823681265 +7/7/03,0.27546695966096374,9998.999999430785,0.651330504719,0.3486700644959339 +7/8/03,0.27546695966096374,9998.999999424292,0.647353408589452,0.35264716711822797 +7/9/03,0.27546695966096374,9998.99999941784,0.643400596756991,0.35659998540379023 +7/10/03,0.27546695966096374,9998.999999411426,0.6394719208532331,0.36052866772124653 +7/11/03,0.27546695966096374,9998.99999940505,0.635567233441263,0.3644333615077531 +8/7/03,0.27546695966096374,9998.999999398715,0.6316863880156327,0.36831421326899677 @@ -45,7 +45,7 @@ class Learner(object): if args.end != None: confirmed_sums = np.sum([reg.loc[args.start:args.end].values for reg in country_df.iloc], axis = 0) else: - confirmed_sums = np.sum([reg.loc[[args.start:]].values for reg in country_df.iloc], axis = 0) + confirmed_sums = np.sum([reg.loc[args.start:].values for reg in country_df.iloc], axis = 0) if args.end != None: new_data = pd.DataFrame(confirmed_sums, country_df.iloc[0].loc[args.start:args.end].index.tolist()) |
