In [2]:
# Load Biospytial modules and etc.
%matplotlib inline
import sys
sys.path.append('/apps')
import django
django.setup()
import pandas as pd
import matplotlib.pyplot as plt
## Use the ggplot style
plt.style.use('ggplot')
In [3]:
data = pd.read_csv("/RawDataCSV/iDiv_data_share/plotsClimateData_11092017.csv")
/opt/conda/envs/biospytial/lib/python2.7/site-packages/IPython/core/interactiveshell.py:2717: DtypeWarning: Columns (24) have mixed types. Specify dtype option on import or set low_memory=False.
interactivity=interactivity, compiler=compiler, result=result)
In [4]:
import geopandas as gpd
In [7]:
data.keys()
Out[7]:
Index([u'Unnamed: 0', u'STATECD', u'STATENM', u'STATEAB', u'COUNTYCD', u'PLOT',
u'PLOT_ID', u'PlotIDn', u'LAT', u'LON', u'INVYR', u'N_subplot',
u'StandAge', u'treeDensity', u'plotBA', u'plotBiomass', u'SppN',
u'ECO_ID_U', u'ECO_CODE', u'ECO_NAME', u'ECO_NUM', u'ECODE_NAME',
u'CLS_CODE', u'ECO_NOTES', u'WWF_REALM', u'WWF_REALM2', u'WWF_MHTNUM',
u'WWF_MHTNAM', u'RealmMHT', u'ER_UPDATE', u'ER_DATE_U', u'ER_RATION',
u'SOURCEDATA', u'ECOR', u'AnnualMeanPrec', u'TempSeason', u'AnnualPrec',
u'PrecSeason', u'AET', u'lon', u'lat'],
dtype='object')
In [10]:
gpd.GeoDataFrame?
In [11]:
geod = gpd.GeoDataFrame(data)
Out[11]:
Unnamed: 0
STATECD
STATENM
STATEAB
COUNTYCD
PLOT
PLOT_ID
PlotIDn
LAT
LON
...
ER_RATION
SOURCEDATA
ECOR
AnnualMeanPrec
TempSeason
AnnualPrec
PrecSeason
AET
lon
lat
0
1
1
Alabama
AL
1
3
1_1_3
3
32.602260
-86.476329
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
17.658865
718.992591
1413
21.577757
1044.0
-86.476329
32.602260
1
2
1
Alabama
AL
1
7
1_1_7
7
32.548292
-86.633541
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
17.499334
722.630181
1409
21.034854
1047.0
-86.633541
32.548292
2
3
1
Alabama
AL
1
12
1_1_12
11
32.693874
-86.424075
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
17.322198
725.387013
1439
21.317879
1044.0
-86.424075
32.693874
3
4
1
Alabama
AL
1
15
1_1_15
13
32.557749
-86.477435
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
17.658865
718.992591
1413
21.577757
1040.0
-86.477435
32.557749
4
5
1
Alabama
AL
1
16
1_1_16
14
32.474320
-86.785024
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
17.920864
715.418624
1368
21.251447
1040.0
-86.785024
32.474320
5
6
1
Alabama
AL
1
20
1_1_20
18
32.385575
-86.793624
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
17.920864
715.418624
1368
21.251447
1034.0
-86.793624
32.385575
6
7
1
Alabama
AL
1
21
1_1_21
19
32.633755
-86.747287
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
17.493771
725.831803
1398
20.756506
1053.0
-86.747287
32.633755
7
8
1
Alabama
AL
1
25
1_1_25
23
32.385228
-86.483333
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
18.230385
713.867338
1376
21.776178
1030.0
-86.483333
32.385228
8
9
1
Alabama
AL
1
27
1_1_27
25
32.513878
-86.584285
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
17.499334
722.630181
1409
21.034854
1041.0
-86.584285
32.513878
9
10
1
Alabama
AL
1
46
1_1_46
40
32.506287
-86.751136
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
17.493771
725.831803
1398
20.756506
1044.0
-86.751136
32.506287
10
11
1
Alabama
AL
1
47
1_1_47
41
32.341720
-86.785581
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
17.920864
715.418624
1368
21.251447
1033.0
-86.785581
32.341720
11
12
1
Alabama
AL
1
50
1_1_50
44
32.469436
-86.486575
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
18.230385
713.867338
1376
21.776178
1032.0
-86.486575
32.469436
12
13
1
Alabama
AL
1
53
1_1_53
46
32.599499
-86.429499
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
17.658865
718.992591
1413
21.577757
1045.0
-86.429499
32.599499
13
14
1
Alabama
AL
1
64
1_1_64
57
32.346711
-86.505816
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
18.046698
713.714886
1370
21.620137
1030.0
-86.505816
32.346711
14
15
1
Alabama
AL
1
65
1_1_65
58
32.620641
-86.870002
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
17.472802
726.829570
1394
20.525088
1053.0
-86.870002
32.620641
15
16
1
Alabama
AL
3
3
1_3_3
64
30.624574
-87.811685
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Conifer Forests
19.300364
639.761846
1691
19.817678
1223.0
-87.811685
30.624574
16
17
1
Alabama
AL
3
9
1_3_9
69
30.910634
-87.911595
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Conifer Forests
19.160156
648.849315
1659
18.898880
1220.0
-87.911595
30.910634
17
18
1
Alabama
AL
3
11
1_3_11
70
31.107329
-87.835514
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Conifer Forests
18.994667
655.935493
1631
18.486169
1209.0
-87.835514
31.107329
18
19
1
Alabama
AL
3
21
1_3_21
77
30.827385
-87.743657
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Conifer Forests
19.006365
646.916936
1692
19.750294
1233.0
-87.743657
30.827385
19
20
1
Alabama
AL
3
29
1_3_29
82
30.568903
-87.556019
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Conifer Forests
19.285844
639.298778
1676
20.595675
1204.0
-87.556019
30.568903
20
21
1
Alabama
AL
3
32
1_3_32
84
31.106793
-87.691191
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Conifer Forests
18.724844
662.706571
1644
18.736410
1213.0
-87.691191
31.106793
21
22
1
Alabama
AL
3
46
1_3_46
90
31.153125
-87.941087
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Conifer Forests
18.994667
655.935493
1631
18.486169
1201.0
-87.941087
31.153125
22
23
1
Alabama
AL
3
50
1_3_50
93
30.512405
-87.527604
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Conifer Forests
19.285844
639.298778
1676
20.595675
1192.0
-87.527604
30.512405
23
24
1
Alabama
AL
3
54
1_3_54
95
31.011483
-87.838071
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Conifer Forests
18.994667
655.935493
1631
18.486169
1218.0
-87.838071
31.011483
24
25
1
Alabama
AL
3
68
1_3_68
104
30.784826
-87.797096
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Conifer Forests
19.006365
646.916936
1692
19.750294
1231.0
-87.797096
30.784826
25
26
1
Alabama
AL
3
76
1_3_76
108
30.962482
-87.852304
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Conifer Forests
19.160156
648.849315
1659
18.898880
1221.0
-87.852304
30.962482
26
27
1
Alabama
AL
3
78
1_3_78
110
31.227792
-87.777660
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Conifer Forests
18.724542
668.365948
1598
18.669643
1194.0
-87.777660
31.227792
27
28
1
Alabama
AL
3
81
1_3_81
113
30.870260
-87.733493
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Conifer Forests
18.834052
653.362024
1678
19.590974
1231.0
-87.733493
30.870260
28
29
1
Alabama
AL
3
84
1_3_84
115
31.196096
-87.631524
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Conifer Forests
18.460552
669.891546
1601
18.312511
1202.0
-87.631524
31.196096
29
30
1
Alabama
AL
3
85
1_3_85
116
30.693417
-87.792019
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Conifer Forests
19.006365
646.916936
1692
19.750294
1230.0
-87.792019
30.693417
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
36815
36841
55
Wisconsin
WI
139
20013
55_139_20013
156543
44.005539
-88.679883
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
7.260365
1108.505050
786
38.217657
654.0
-88.679883
44.005539
36816
36842
55
Wisconsin
WI
139
20058
55_139_20058
156545
43.998038
-88.755331
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
7.164750
1107.269609
790
38.533905
661.0
-88.755331
43.998038
36817
36843
55
Wisconsin
WI
139
20167
55_139_20167
156546
44.236548
-88.520169
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
6.935885
1108.396337
783
38.202941
659.0
-88.520169
44.236548
36818
36844
55
Wisconsin
WI
141
20044
55_141_20044
156557
44.284849
-89.926944
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
6.801469
1140.398093
815
44.347439
694.0
-89.926944
44.284849
36819
36845
55
Wisconsin
WI
141
20053
55_141_20053
156561
44.360807
-90.275293
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
5.986812
1136.289426
839
44.876172
697.0
-90.275293
44.360807
36820
36846
55
Wisconsin
WI
141
20081
55_141_20081
156566
44.541150
-89.904645
...
Yes/August2003/LSotomayor / J. Slaats/July2003
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
5.834990
1141.028737
824
45.040813
701.0
-89.904645
44.541150
36821
36847
55
Wisconsin
WI
141
20084
55_141_20084
156568
44.529212
-90.131815
...
Yes/August2003/LSotomayor / J. Slaats/July2003
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
5.768531
1147.732404
834
45.689294
701.0
-90.131815
44.529212
36822
36848
55
Wisconsin
WI
141
20130
55_141_20130
156581
44.328047
-89.773745
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
6.671948
1138.598423
815
44.571311
694.0
-89.773745
44.328047
36823
36849
55
Wisconsin
WI
141
20143
55_141_20143
156582
44.286563
-89.973917
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
6.801469
1140.398093
815
44.347439
691.0
-89.973917
44.286563
36824
36850
55
Wisconsin
WI
141
20173
55_141_20173
156586
44.393739
-90.110988
...
Yes/August2003/LSotomayor / J. Slaats/July2003
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
6.156490
1141.859358
828
44.915918
696.0
-90.110988
44.393739
36825
36851
55
Wisconsin
WI
141
20201
55_141_20201
156592
44.315250
-90.054372
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
6.557719
1122.433089
821
44.678805
692.0
-90.054372
44.315250
36826
36852
55
Wisconsin
WI
141
20219
55_141_20219
156596
44.291181
-90.092533
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
6.557719
1122.433089
821
44.678805
693.0
-90.092533
44.291181
36827
36853
55
Wisconsin
WI
141
20222
55_141_20222
156597
44.404072
-89.748225
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
6.528260
1141.610364
813
44.397223
695.0
-89.748225
44.404072
36828
36854
55
Wisconsin
WI
141
20252
55_141_20252
156602
44.523927
-90.183388
...
Yes/August2003/LSotomayor / J. Slaats/July2003
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
5.615729
1142.890886
842
46.013819
702.0
-90.183388
44.523927
36829
36855
55
Wisconsin
WI
141
20263
55_141_20263
156603
44.279302
-90.155504
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
6.557719
1122.433089
821
44.678805
693.0
-90.155504
44.279302
36830
36856
55
Wisconsin
WI
141
20271
55_141_20271
156605
44.388963
-90.223114
...
Yes/August2003/LSotomayor / J. Slaats/July2003
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
5.986812
1136.289426
839
44.876172
697.0
-90.223114
44.388963
36831
36857
55
Wisconsin
WI
141
20277
55_141_20277
156608
44.370275
-90.102854
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
6.156490
1141.859358
828
44.915918
696.0
-90.102854
44.370275
36832
36858
55
Wisconsin
WI
141
20303
55_141_20303
156613
44.253966
-90.032898
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
6.557719
1122.433089
821
44.678805
691.0
-90.032898
44.253966
36833
36859
55
Wisconsin
WI
141
20313
55_141_20313
156615
44.504710
-90.175232
...
Yes/August2003/LSotomayor / J. Slaats/July2003
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
5.615729
1142.890886
842
46.013819
701.0
-90.175232
44.504710
36834
36860
55
Wisconsin
WI
141
20319
55_141_20319
156616
44.651950
-89.868171
...
Yes/August2003/LSotomayor / J. Slaats/July2003
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
5.834990
1141.028737
824
45.040813
701.0
-89.868171
44.651950
36835
36861
55
Wisconsin
WI
141
20328
55_141_20328
156622
44.442028
-89.811739
...
Yes/August2003/LSotomayor / J. Slaats/July2003
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
6.528260
1141.610364
813
44.397223
694.0
-89.811739
44.442028
36836
36862
55
Wisconsin
WI
141
20329
55_141_20329
156623
44.376466
-89.854789
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
6.319188
1141.978175
822
44.159047
693.0
-89.854789
44.376466
36837
36863
55
Wisconsin
WI
141
20380
55_141_20380
156636
44.399949
-89.913148
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
6.319188
1141.978175
822
44.159047
697.0
-89.913148
44.399949
36838
36864
55
Wisconsin
WI
141
20381
55_141_20381
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44.417291
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Yes/August2003/LSotomayor / J. Slaats/July2003
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
6.156490
1141.859358
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44.915918
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44.417291
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Wisconsin
WI
141
20382
55_141_20382
156638
44.386097
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NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
6.156490
1141.859358
828
44.915918
697.0
-90.052550
44.386097
36840
36866
55
Wisconsin
WI
141
20384
55_141_20384
156639
44.316655
-90.122631
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
6.557719
1122.433089
821
44.678805
693.0
-90.122631
44.316655
36841
36867
55
Wisconsin
WI
141
20403
55_141_20403
156643
44.423240
-90.027616
...
Yes/August2003/LSotomayor / J. Slaats/July2003
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
6.156490
1141.859358
828
44.915918
697.0
-90.027616
44.423240
36842
36868
55
Wisconsin
WI
141
20404
55_141_20404
156644
44.366777
-89.726969
...
NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
6.528260
1141.610364
813
44.397223
693.0
-89.726969
44.366777
36843
36869
55
Wisconsin
WI
141
20405
55_141_20405
156645
44.313614
-90.237374
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NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
6.396365
1134.578026
832
44.349472
698.0
-90.237374
44.313614
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55
Wisconsin
WI
141
20406
55_141_20406
156646
44.261186
-89.746097
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NA / D. Dorfman/ECO2001
Bailey, R, modified by TNC. 2004. Ecoregions o...
Temperate Broadleaf and Mixed Forests
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1138.598423
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44.571311
688.0
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36845 rows × 41 columns
In [ ]:
In [ ]:
In [ ]:
In [ ]:
In [76]:
fig = plt.figure(figsize=(16,10), dpi= 80, facecolor='w', edgecolor='w')
plt.rcParams['axes.facecolor'] = 'white'
plt.scatter(data.lon,data.lat,c=data.AET,cmap=plt.cm.Greens,edgecolors='')
plt.title("Evapotranspiration")
plt.colorbar()
Out[76]:
<matplotlib.colorbar.Colorbar at 0x7f2d8a8f4690>
In [4]:
fig = plt.figure(figsize=(16,10), dpi= 80, facecolor='w', edgecolor='w')
plt.scatter(data.lon,data.lat,c=data.StandAge,edgecolors='',cmap=plt.cm.BrBG)
plt.title("Stand Age")
plt.colorbar()
Out[4]:
<matplotlib.colorbar.Colorbar at 0x7f2f6be15c10>
In [77]:
fig = plt.figure(figsize=(16,10), dpi= 80, facecolor='w', edgecolor='w')
plt.scatter(data.lon,data.lat,c=data.SppN,edgecolors='')
plt.title("Species Richness")
plt.colorbar()
Out[77]:
<matplotlib.colorbar.Colorbar at 0x7f2d8a7d2c10>
In [6]:
fig = plt.figure(figsize=(16,10), dpi= 80, facecolor='w', edgecolor='w')
plt.scatter(data.lon,data.lat,c=data.plotBiomass,edgecolors='',cmap=plt.cm.Greens)
plt.title("Plot Biomass")
plt.colorbar()
Out[6]:
<matplotlib.colorbar.Colorbar at 0x7f2f6824cf50>
In [7]:
plt.scatter(data.AET,data.SppN)
Out[7]:
<matplotlib.collections.PathCollection at 0x7f2f680745d0>
In [70]:
len(data.lon)
#X = data[['AET','StandAge','lon','lat']]
X = data[['SppN','lon','lat']]
#X = data[['lon','lat']]
Y = data['plotBiomass']
#Y = data[['SppN']]
## First step in spatial autocorrelation
#Y = pd.DataFrame(np.zeros(len(Y)))
## Let´s take a small sample only for the spatial autocorrelation
import numpy as np
sample_size = 2000
randindx = np.random.randint(0,X.shape[0],sample_size)
nX = X.loc[randindx]
nY = Y.loc[randindx]
In [72]:
# Import GPFlow
import GPflow as gf
k = gf.kernels.Matern12(2, lengthscales=1, active_dims = [1,2] )
In [73]:
model = gf.gpr.GPR(nX.as_matrix(),nY.as_matrix().reshape(sample_size,1).astype(float),k)
In [74]:
model.likelihood.variance = 10
model.optimize()
Out[74]:
fun: 20596.08632030103
hess_inv: <3x3 LbfgsInvHessProduct with dtype=float64>
jac: array([ 5.78522765e-08, -1.91589997e-07, -7.37748439e-06])
message: 'CONVERGENCE: NORM_OF_PROJECTED_GRADIENT_<=_PGTOL'
nfev: 71
nit: 60
status: 0
success: True
x: array([ 1244635.29196167, 15585310.29301777, 38550013.84500826])
In [94]:
Nn = 300
predicted_x = np.linspace(min(data.lon),max(data.lon),Nn)
predicted_y = np.linspace(min(data.lat),max(data.lat),Nn)
Xx, Yy = np.meshgrid(predicted_x,predicted_y)
## Fake richness
fake_sp_rich = np.ones(len(Xx.ravel()))
predicted_coordinates = np.vstack([ Xx.ravel(), Yy.ravel()]).transpose()
predicted_coordinates = np.vstack([data.SppN, data.lon, data.lat]).transpose()
In [95]:
predicted_coordinates.shape
Out[95]:
(36845, 3)
In [96]:
means,variances = model.predict_y(predicted_coordinates)
In [98]:
plt.scatter(data.SppN,means)
Out[98]:
<matplotlib.collections.PathCollection at 0x7f2d5ad352d0>
In [67]:
fig = plt.figure(figsize=(16,10), dpi= 80, facecolor='w', edgecolor='w')
plt.pcolor(Xx,Yy,means.reshape(Nn,Nn),cmap=plt.cm.Greens)
plt.colorbar()
plt.scatter(nX.lon,nX.lat,c=nY,edgecolors='',cmap=plt.cm.Greys)
plt.title("Mean Biomass")
plt.colorbar()
Out[67]:
<matplotlib.colorbar.Colorbar at 0x7f2e55148b10>
In [100]:
fig = plt.figure(figsize=(16,10), dpi= 80, facecolor='w', edgecolor='w')
plt.pcolor(Xx,Yy,variances.reshape(Nn,Nn),cmap=plt.cm.Blues)
plt.colorbar()
plt.scatter(nX.lon,nX.lat,c=nY,edgecolors='',cmap=plt.cm.Greys)
plt.title("Variance")
plt.colorbar()
ValueErrorTraceback (most recent call last)
<ipython-input-100-b0554ae360fc> in <module>()
1 fig = plt.figure(figsize=(16,10), dpi= 80, facecolor='w', edgecolor='w')
----> 2 plt.pcolor(Xx,Yy,variances.reshape(Nn,Nn),cmap=plt.cm.Blues)
3 plt.colorbar()
4 plt.scatter(nX.lon,nX.lat,c=nY,edgecolors='',cmap=plt.cm.Greys)
5 plt.title("Variance")
ValueError: total size of new array must be unchanged
<matplotlib.figure.Figure at 0x7f2d5ac8c7d0>
In [83]:
predicted_coordinates = np.vstack([data.SppN, data.lon, data.lat])
In [84]:
means,variances = model.predict_y(predicted_coordinates)
In [80]:
plt.plot(predicted_coordinates)
Out[80]:
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...]
Traceback (most recent call last):
File "/opt/conda/envs/biospytial/lib/python2.7/site-packages/ipykernel/ipkernel.py", line 175, in do_execute
shell.run_cell(code, store_history=store_history, silent=silent)
File "/opt/conda/envs/biospytial/lib/python2.7/site-packages/IPython/core/interactiveshell.py", line 2725, in run_cell
self.events.trigger('post_execute')
File "/opt/conda/envs/biospytial/lib/python2.7/site-packages/IPython/core/events.py", line 74, in trigger
func(*args, **kwargs)
File "/opt/conda/envs/biospytial/lib/python2.7/site-packages/ipykernel/pylab/backend_inline.py", line 113, in flush_figures
return show(True)
File "/opt/conda/envs/biospytial/lib/python2.7/site-packages/ipykernel/pylab/backend_inline.py", line 36, in show
display(figure_manager.canvas.figure)
File "/opt/conda/envs/biospytial/lib/python2.7/site-packages/IPython/core/display.py", line 164, in display
format_dict, md_dict = format(obj, include=include, exclude=exclude)
File "/opt/conda/envs/biospytial/lib/python2.7/site-packages/IPython/core/formatters.py", line 145, in format
data = formatter(obj)
File "<decorator-gen-9>", line 2, in __call__
File "/opt/conda/envs/biospytial/lib/python2.7/site-packages/IPython/core/formatters.py", line 190, in catch_format_error
r = method(self, *args, **kwargs)
File "/opt/conda/envs/biospytial/lib/python2.7/site-packages/IPython/core/formatters.py", line 307, in __call__
return printer(obj)
File "/opt/conda/envs/biospytial/lib/python2.7/site-packages/IPython/core/pylabtools.py", line 227, in <lambda>
png_formatter.for_type(Figure, lambda fig: print_figure(fig, 'png', **kwargs))
File "/opt/conda/envs/biospytial/lib/python2.7/site-packages/IPython/core/pylabtools.py", line 119, in print_figure
fig.canvas.print_figure(bytes_io, **kw)
File "/opt/conda/envs/biospytial/lib/python2.7/site-packages/matplotlib/backend_bases.py", line 2180, in print_figure
**kwargs)
File "/opt/conda/envs/biospytial/lib/python2.7/site-packages/matplotlib/backends/backend_agg.py", line 527, in print_png
FigureCanvasAgg.draw(self)
File "/opt/conda/envs/biospytial/lib/python2.7/site-packages/matplotlib/backends/backend_agg.py", line 474, in draw
self.figure.draw(self.renderer)
File "/opt/conda/envs/biospytial/lib/python2.7/site-packages/matplotlib/artist.py", line 61, in draw_wrapper
draw(artist, renderer, *args, **kwargs)
File "/opt/conda/envs/biospytial/lib/python2.7/site-packages/matplotlib/figure.py", line 1159, in draw
func(*args)
File "/opt/conda/envs/biospytial/lib/python2.7/site-packages/matplotlib/artist.py", line 61, in draw_wrapper
draw(artist, renderer, *args, **kwargs)
File "/opt/conda/envs/biospytial/lib/python2.7/site-packages/matplotlib/axes/_base.py", line 2324, in draw
a.draw(renderer)
File "/opt/conda/envs/biospytial/lib/python2.7/site-packages/matplotlib/artist.py", line 61, in draw_wrapper
draw(artist, renderer, *args, **kwargs)
File "/opt/conda/envs/biospytial/lib/python2.7/site-packages/matplotlib/lines.py", line 731, in draw
tpath, affine = transf_path.get_transformed_path_and_affine()
File "/opt/conda/envs/biospytial/lib/python2.7/site-packages/matplotlib/transforms.py", line 2712, in get_transformed_path_and_affine
return self._transformed_path, self.get_affine()
File "/opt/conda/envs/biospytial/lib/python2.7/site-packages/matplotlib/transforms.py", line 2722, in get_affine
return self._transform.get_affine()
File "/opt/conda/envs/biospytial/lib/python2.7/site-packages/matplotlib/transforms.py", line 2374, in get_affine
return Affine2D(np.dot(self._b.get_affine().get_matrix(),
File "/opt/conda/envs/biospytial/lib/python2.7/site-packages/matplotlib/transforms.py", line 2375, in get_affine
self._a.get_affine().get_matrix()))
File "/opt/conda/envs/biospytial/lib/python2.7/site-packages/matplotlib/transforms.py", line 1796, in __init__
Affine2DBase.__init__(self, **kwargs)
File "/opt/conda/envs/biospytial/lib/python2.7/site-packages/matplotlib/transforms.py", line 1641, in __init__
Transform.__init__(self, *args, **kwargs)
File "/opt/conda/envs/biospytial/lib/python2.7/site-packages/matplotlib/transforms.py", line 98, in __init__
self._parents = WeakValueDictionary()
File "/opt/conda/envs/biospytial/lib/python2.7/weakref.py", line 65, in __init__
self._iterating = set()
KeyboardInterrupt
In [ ]:
ndata = pd.concat([nY,nX],axis=1)
plt.scatter(ndata.lon,ndata.lat,c=ndata.SppN)
plt.title("Species Richness")
plt.colorbar()
In [ ]:
In [ ]:
import statsmodels.api as sm
In [ ]:
glm_binom = sm.GLM(data, data.exog, family=sm.families.Binomial())
res = glm_binom.fit()
print(res.summary())
In [ ]:
from sketches.models import Country
us = Country.objects.filter(name__contains="United States")[1]
In [ ]:
from raster_api.models import ETOPO1
from raster_api.tools import RasterData
In [ ]:
usrast = RasterData(ETOPO1,us.geom)
In [ ]:
chiqui = usrast.getRaster()
In [ ]:
usrast.display_field()
In [ ]:
usrast = RasterField
In [ ]:
Content source: molgor/spystats
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