{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"using TSML\n",
"using DataFrames\n",
"using Dates\n",
"using CSV\n",
"using Random"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"DateValNNer(nothing, Dict{Symbol,Any}(:strict => true,:dateinterval => 1 hour,:aggregator => :median,:nnsize => 1,:missdirection => :symmetric))"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"fname =\"testdata.csv\"\n",
"dat = CSV.read(fname)\n",
"rename!(dat,names(dat)[1]=>:Date,names(dat)[2]=>:Value)\n",
"dat.Date = DateTime.(dat.Date,\"d/m/y H:M\")\n",
"orig = deepcopy(dat)\n",
"filter1 = DateValgator()\n",
"filter2 = DateValNNer(Dict(:nnsize=>1))"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(5×2 DataFrame\n",
"│ Row │ Date │ Value │\n",
"│ │ \u001b[90mDateTime\u001b[39m │ \u001b[90mFloat64⍰\u001b[39m │\n",
"├─────┼─────────────────────┼──────────┤\n",
"│ 1 │ 2014-01-01T00:00:00 │ 10.0 │\n",
"│ 2 │ 2014-01-01T01:00:00 │ 9.9 │\n",
"│ 3 │ 2014-01-01T02:00:00 │ 10.0 │\n",
"│ 4 │ 2014-01-01T03:00:00 │ 10.0 │\n",
"│ 5 │ 2014-01-01T04:00:00 │ 10.0 │, 8761)"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"fit!(filter1,dat,[])\n",
"res1=transform!(filter1,dat)\n",
"(first(res1,5),size(res1,1))"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(5×2 DataFrame\n",
"│ Row │ Date │ Value │\n",
"│ │ \u001b[90mDateTime\u001b[39m │ \u001b[90mFloat64⍰\u001b[39m │\n",
"├─────┼─────────────────────┼──────────┤\n",
"│ 1 │ 2014-01-01T00:00:00 │ 10.0 │\n",
"│ 2 │ 2014-01-01T01:00:00 │ 9.9 │\n",
"│ 3 │ 2014-01-01T02:00:00 │ 10.0 │\n",
"│ 4 │ 2014-01-01T03:00:00 │ 10.0 │\n",
"│ 5 │ 2014-01-01T04:00:00 │ 10.0 │, 8761)"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"fit!(filter2,res1,[])\n",
"res2=transform!(filter2,res1)\n",
"(first(res2,5),size(res2,1))"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Pipeline(nothing, Dict{Symbol,Union{Nothing, Array{Transformer,1}}}(:transformers => Transformer[DateValgator(Dict{Symbol,Any}(:dateinterval => 1 hour,:aggregator => :median), Dict{Symbol,Any}(:dateinterval => 1 hour,:aggregator => :median)), DateValNNer(Dict{Symbol,Any}(:loopcount => 1,:strict => true,:dateinterval => 1 hour,:missingcount => 4931,:aggregator => :median,:nnsize => 1,:missdirection => :symmetric), Dict{Symbol,Any}(:loopcount => 1,:strict => true,:dateinterval => 1 hour,:missingcount => 4931,:aggregator => :median,:nnsize => 1,:missdirection => :symmetric))],:transformer_args => nothing))"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"mypipeline = Pipeline(Dict(\n",
" :transformers => [filter1,filter2]\n",
" )\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<table class=\"data-frame\"><thead><tr><th></th><th>Date</th><th>Value</th></tr><tr><th></th><th>DateTime</th><th>Float64⍰</th></tr></thead><tbody><p>5 rows × 2 columns</p><tr><th>1</th><td>2014-01-01T00:00:00</td><td>10.0</td></tr><tr><th>2</th><td>2014-01-01T01:00:00</td><td>9.9</td></tr><tr><th>3</th><td>2014-01-01T02:00:00</td><td>10.0</td></tr><tr><th>4</th><td>2014-01-01T03:00:00</td><td>10.0</td></tr><tr><th>5</th><td>2014-01-01T04:00:00</td><td>10.0</td></tr></tbody></table>"
],
"text/latex": [
"\\begin{tabular}{r|cc}\n",
"\t& Date & Value\\\\\n",
"\t\\hline\n",
"\t& DateTime & Float64⍰\\\\\n",
"\t\\hline\n",
"\t1 & 2014-01-01T00:00:00 & 10.0 \\\\\n",
"\t2 & 2014-01-01T01:00:00 & 9.9 \\\\\n",
"\t3 & 2014-01-01T02:00:00 & 10.0 \\\\\n",
"\t4 & 2014-01-01T03:00:00 & 10.0 \\\\\n",
"\t5 & 2014-01-01T04:00:00 & 10.0 \\\\\n",
"\\end{tabular}\n"
],
"text/plain": [
"5×2 DataFrame\n",
"│ Row │ Date │ Value │\n",
"│ │ \u001b[90mDateTime\u001b[39m │ \u001b[90mFloat64⍰\u001b[39m │\n",
"├─────┼─────────────────────┼──────────┤\n",
"│ 1 │ 2014-01-01T00:00:00 │ 10.0 │\n",
"│ 2 │ 2014-01-01T01:00:00 │ 9.9 │\n",
"│ 3 │ 2014-01-01T02:00:00 │ 10.0 │\n",
"│ 4 │ 2014-01-01T03:00:00 │ 10.0 │\n",
"│ 5 │ 2014-01-01T04:00:00 │ 10.0 │"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"fit!(mypipeline,dat,[])\n",
"resp = transform!(mypipeline,dat)\n",
"first(resp,5)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"transform! (generic function with 42 methods)"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"using TSML.TSMLTypes\n",
"import TSML.TSMLTypes.fit!\n",
"import TSML.TSMLTypes.transform!\n",
"\n",
"mutable struct MyCSVDateValReader <: Transformer\n",
" model\n",
" args\n",
" function MyCSVDateValReader(args=Dict())\n",
" default_args = Dict(\n",
" :filename => \"\",\n",
" :dateformat => \"\"\n",
" )\n",
" new(nothing,mergedict(default_args,args))\n",
" end\n",
"end\n",
"function fit!(csvrdr::MyCSVDateValReader,x::T=[],y::Vector=[]) where {T<:Union{DataFrame,Vector,Matrix}}\n",
" fname = csvrdr.args[:filename]\n",
" fmt = csvrdr.args[:dateformat]\n",
" (fname != \"\" && fmt != \"\") || error(\"missing filename or date format\")\n",
" model = csvrdr.args\n",
"end\n",
"\n",
"function transform!(csvrdr::MyCSVDateValReader,x::T=[]) where {T<:Union{DataFrame,Vector,Matrix}}\n",
" fname = csvrdr.args[:filename]\n",
" fmt = csvrdr.args[:dateformat]\n",
" df = CSV.read(fname)\n",
" ncol(df) == 2 || error(\"dataframe should have only two columns: Date,Value\")\n",
" rename!(df,names(df)[1]=>:Date,names(df)[2]=>:Value)\n",
" df.Date = DateTime.(df.Date,fmt)\n",
" df\n",
"end"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<table class=\"data-frame\"><thead><tr><th></th><th>Date</th><th>Value</th></tr><tr><th></th><th>DateTime</th><th>Float64</th></tr></thead><tbody><p>5 rows × 2 columns</p><tr><th>1</th><td>2014-01-01T00:06:00</td><td>10.0</td></tr><tr><th>2</th><td>2014-01-01T00:18:00</td><td>10.0</td></tr><tr><th>3</th><td>2014-01-01T00:29:00</td><td>10.0</td></tr><tr><th>4</th><td>2014-01-01T00:40:00</td><td>9.9</td></tr><tr><th>5</th><td>2014-01-01T00:51:00</td><td>9.9</td></tr></tbody></table>"
],
"text/latex": [
"\\begin{tabular}{r|cc}\n",
"\t& Date & Value\\\\\n",
"\t\\hline\n",
"\t& DateTime & Float64\\\\\n",
"\t\\hline\n",
"\t1 & 2014-01-01T00:06:00 & 10.0 \\\\\n",
"\t2 & 2014-01-01T00:18:00 & 10.0 \\\\\n",
"\t3 & 2014-01-01T00:29:00 & 10.0 \\\\\n",
"\t4 & 2014-01-01T00:40:00 & 9.9 \\\\\n",
"\t5 & 2014-01-01T00:51:00 & 9.9 \\\\\n",
"\\end{tabular}\n"
],
"text/plain": [
"5×2 DataFrame\n",
"│ Row │ Date │ Value │\n",
"│ │ \u001b[90mDateTime\u001b[39m │ \u001b[90mFloat64\u001b[39m │\n",
"├─────┼─────────────────────┼─────────┤\n",
"│ 1 │ 2014-01-01T00:06:00 │ 10.0 │\n",
"│ 2 │ 2014-01-01T00:18:00 │ 10.0 │\n",
"│ 3 │ 2014-01-01T00:29:00 │ 10.0 │\n",
"│ 4 │ 2014-01-01T00:40:00 │ 9.9 │\n",
"│ 5 │ 2014-01-01T00:51:00 │ 9.9 │"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"csvreader = MyCSVDateValReader(Dict(:filename=>\"testdata.csv\",:dateformat=>\"d/m/y H:M\"))\n",
"fit!(csvreader)\n",
"res=transform!(csvreader)\n",
"first(res,5)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<table class=\"data-frame\"><thead><tr><th></th><th>Date</th><th>Value</th></tr><tr><th></th><th>DateTime</th><th>Float64⍰</th></tr></thead><tbody><p>5 rows × 2 columns</p><tr><th>1</th><td>2014-01-01T00:00:00</td><td>10.0</td></tr><tr><th>2</th><td>2014-01-01T01:00:00</td><td>9.9</td></tr><tr><th>3</th><td>2014-01-01T02:00:00</td><td>10.0</td></tr><tr><th>4</th><td>2014-01-01T03:00:00</td><td>10.0</td></tr><tr><th>5</th><td>2014-01-01T04:00:00</td><td>10.0</td></tr></tbody></table>"
],
"text/latex": [
"\\begin{tabular}{r|cc}\n",
"\t& Date & Value\\\\\n",
"\t\\hline\n",
"\t& DateTime & Float64⍰\\\\\n",
"\t\\hline\n",
"\t1 & 2014-01-01T00:00:00 & 10.0 \\\\\n",
"\t2 & 2014-01-01T01:00:00 & 9.9 \\\\\n",
"\t3 & 2014-01-01T02:00:00 & 10.0 \\\\\n",
"\t4 & 2014-01-01T03:00:00 & 10.0 \\\\\n",
"\t5 & 2014-01-01T04:00:00 & 10.0 \\\\\n",
"\\end{tabular}\n"
],
"text/plain": [
"5×2 DataFrame\n",
"│ Row │ Date │ Value │\n",
"│ │ \u001b[90mDateTime\u001b[39m │ \u001b[90mFloat64⍰\u001b[39m │\n",
"├─────┼─────────────────────┼──────────┤\n",
"│ 1 │ 2014-01-01T00:00:00 │ 10.0 │\n",
"│ 2 │ 2014-01-01T01:00:00 │ 9.9 │\n",
"│ 3 │ 2014-01-01T02:00:00 │ 10.0 │\n",
"│ 4 │ 2014-01-01T03:00:00 │ 10.0 │\n",
"│ 5 │ 2014-01-01T04:00:00 │ 10.0 │"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"mypipeline = Pipeline(Dict(\n",
" :transformers => [csvreader,filter1,filter2]\n",
" )\n",
")\n",
"fit!(mypipeline)\n",
"res=transform!(mypipeline)\n",
"first(res,5)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"4931"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"filter2.args[:missingcount]"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"mydate=DateTime(2014,1,1):Dates.Minute(15):DateTime(2014,1,3) # 15 minutes interval\n",
"values = Array{Union{Float64,Missing}}(sin.(1:0.1:length(mydate)) .+ cos.(1:0.1:length(mydate)))[1:length(mydate)];\n",
"x = DataFrame(Date=mydate,Value=values); xx = deepcopy(x);first(x,10)\n",
"nmissing=floor(nrow(x) * 0.80) |> Integer\n",
"ndxmissing=Random.shuffle(1:nrow(x))[1:nmissing]\n",
"x.Value[ndxmissing] .= missing; first(x,15)\n",
"dvtr = TSML.DateValgator()\n",
"TSML.fit!(dvtr,x,[]);TSML.fit!(dvtr,xx,[])\n",
"inputx = TSML.transform!(dvtr,x); inputxx = TSML.transform!(dvtr,xx);\n",
"dvnnr = TSML.DateValNNer(Dict(:dateinterval=>Dates.Hour(1),:nnsize=>1))\n",
"TSML.fit!(dvnnr,inputx,[])\n",
"pred_y=TSML.transform!(dvnnr,inputx);pred_yy=TSML.transform!(dvnnr,inputxx);"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.522726120677754"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sqrt(sum(pred_y.Value-pred_yy.Value).^2)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"rename!(pred_y,:Value=>:MissingVals);"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<table class=\"data-frame\"><thead><tr><th></th><th>Date</th><th>MissingVals</th><th>Value</th><th>error</th></tr><tr><th></th><th>DateTime</th><th>Float64⍰</th><th>Float64⍰</th><th>Float64</th></tr></thead><tbody><p>49 rows × 4 columns</p><tr><th>1</th><td>2014-01-01T00:00:00</td><td>0.746646</td><td>1.36329</td><td>0.380248</td></tr><tr><th>2</th><td>2014-01-01T01:00:00</td><td>0.746646</td><td>1.19324</td><td>0.199444</td></tr><tr><th>3</th><td>2014-01-01T02:00:00</td><td>0.746646</td><td>0.804733</td><td>0.00337414</td></tr><tr><th>4</th><td>2014-01-01T03:00:00</td><td>-0.105454</td><td>0.289179</td><td>0.155736</td></tr><tr><th>5</th><td>2014-01-01T04:00:00</td><td>-0.957554</td><td>-0.272029</td><td>0.469945</td></tr><tr><th>6</th><td>2014-01-01T05:00:00</td><td>-0.957554</td><td>-0.790291</td><td>0.0279772</td></tr><tr><th>7</th><td>2014-01-01T06:00:00</td><td>-1.18563</td><td>-1.18378</td><td>3.40069e-6</td></tr><tr><th>8</th><td>2014-01-01T07:00:00</td><td>-1.4137</td><td>-1.39038</td><td>0.000543709</td></tr><tr><th>9</th><td>2014-01-01T08:00:00</td><td>-1.38614</td><td>-1.37747</td><td>7.52128e-5</td></tr><tr><th>10</th><td>2014-01-01T09:00:00</td><td>-1.05908</td><td>-1.14708</td><td>0.00774523</td></tr><tr><th>11</th><td>2014-01-01T10:00:00</td><td>-0.63353</td><td>-0.735601</td><td>0.0104185</td></tr><tr><th>12</th><td>2014-01-01T11:00:00</td><td>-0.207982</td><td>-0.207982</td><td>0.0</td></tr><tr><th>13</th><td>2014-01-01T12:00:00</td><td>0.526896</td><td>0.352472</td><td>0.0304236</td></tr><tr><th>14</th><td>2014-01-01T13:00:00</td><td>1.26177</td><td>0.857279</td><td>0.163616</td></tr><tr><th>15</th><td>2014-01-01T14:00:00</td><td>1.26177</td><td>1.22674</td><td>0.00122732</td></tr><tr><th>16</th><td>2014-01-01T15:00:00</td><td>0.658726</td><td>1.40253</td><td>0.55324</td></tr><tr><th>17</th><td>2014-01-01T16:00:00</td><td>0.0556771</td><td>1.35688</td><td>1.69314</td></tr><tr><th>18</th><td>2014-01-01T17:00:00</td><td>0.0556771</td><td>1.09702</td><td>1.0844</td></tr><tr><th>19</th><td>2014-01-01T18:00:00</td><td>0.0556771</td><td>0.663961</td><td>0.370009</td></tr><tr><th>20</th><td>2014-01-01T19:00:00</td><td>0.0556771</td><td>0.126076</td><td>0.00495603</td></tr><tr><th>21</th><td>2014-01-01T20:00:00</td><td>-0.499012</td><td>-0.431713</td><td>0.00452912</td></tr><tr><th>22</th><td>2014-01-01T21:00:00</td><td>-0.956576</td><td>-0.921344</td><td>0.00124128</td></tr><tr><th>23</th><td>2014-01-01T22:00:00</td><td>-1.41414</td><td>-1.26552</td><td>0.0220894</td></tr><tr><th>24</th><td>2014-01-01T23:00:00</td><td>-1.41414</td><td>-1.40708</td><td>4.99116e-5</td></tr><tr><th>25</th><td>2014-01-02T00:00:00</td><td>-1.30811</td><td>-1.33167</td><td>0.000555052</td></tr><tr><th>26</th><td>2014-01-02T01:00:00</td><td>-0.303306</td><td>-1.04321</td><td>0.547464</td></tr><tr><th>27</th><td>2014-01-02T02:00:00</td><td>0.701501</td><td>-0.590056</td><td>1.66812</td></tr><tr><th>28</th><td>2014-01-02T03:00:00</td><td>0.701501</td><td>-0.0437399</td><td>0.555384</td></tr><tr><th>29</th><td>2014-01-02T04:00:00</td><td>0.701501</td><td>0.509482</td><td>0.0368714</td></tr><tr><th>30</th><td>2014-01-02T05:00:00</td><td>1.03306</td><td>0.982267</td><td>0.00257969</td></tr><tr><th>⋮</th><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td></tr></tbody></table>"
],
"text/latex": [
"\\begin{tabular}{r|cccc}\n",
"\t& Date & MissingVals & Value & error\\\\\n",
"\t\\hline\n",
"\t& DateTime & Float64⍰ & Float64⍰ & Float64\\\\\n",
"\t\\hline\n",
"\t1 & 2014-01-01T00:00:00 & 0.746646 & 1.36329 & 0.380248 \\\\\n",
"\t2 & 2014-01-01T01:00:00 & 0.746646 & 1.19324 & 0.199444 \\\\\n",
"\t3 & 2014-01-01T02:00:00 & 0.746646 & 0.804733 & 0.00337414 \\\\\n",
"\t4 & 2014-01-01T03:00:00 & -0.105454 & 0.289179 & 0.155736 \\\\\n",
"\t5 & 2014-01-01T04:00:00 & -0.957554 & -0.272029 & 0.469945 \\\\\n",
"\t6 & 2014-01-01T05:00:00 & -0.957554 & -0.790291 & 0.0279772 \\\\\n",
"\t7 & 2014-01-01T06:00:00 & -1.18563 & -1.18378 & 3.40069e-6 \\\\\n",
"\t8 & 2014-01-01T07:00:00 & -1.4137 & -1.39038 & 0.000543709 \\\\\n",
"\t9 & 2014-01-01T08:00:00 & -1.38614 & -1.37747 & 7.52128e-5 \\\\\n",
"\t10 & 2014-01-01T09:00:00 & -1.05908 & -1.14708 & 0.00774523 \\\\\n",
"\t11 & 2014-01-01T10:00:00 & -0.63353 & -0.735601 & 0.0104185 \\\\\n",
"\t12 & 2014-01-01T11:00:00 & -0.207982 & -0.207982 & 0.0 \\\\\n",
"\t13 & 2014-01-01T12:00:00 & 0.526896 & 0.352472 & 0.0304236 \\\\\n",
"\t14 & 2014-01-01T13:00:00 & 1.26177 & 0.857279 & 0.163616 \\\\\n",
"\t15 & 2014-01-01T14:00:00 & 1.26177 & 1.22674 & 0.00122732 \\\\\n",
"\t16 & 2014-01-01T15:00:00 & 0.658726 & 1.40253 & 0.55324 \\\\\n",
"\t17 & 2014-01-01T16:00:00 & 0.0556771 & 1.35688 & 1.69314 \\\\\n",
"\t18 & 2014-01-01T17:00:00 & 0.0556771 & 1.09702 & 1.0844 \\\\\n",
"\t19 & 2014-01-01T18:00:00 & 0.0556771 & 0.663961 & 0.370009 \\\\\n",
"\t20 & 2014-01-01T19:00:00 & 0.0556771 & 0.126076 & 0.00495603 \\\\\n",
"\t21 & 2014-01-01T20:00:00 & -0.499012 & -0.431713 & 0.00452912 \\\\\n",
"\t22 & 2014-01-01T21:00:00 & -0.956576 & -0.921344 & 0.00124128 \\\\\n",
"\t23 & 2014-01-01T22:00:00 & -1.41414 & -1.26552 & 0.0220894 \\\\\n",
"\t24 & 2014-01-01T23:00:00 & -1.41414 & -1.40708 & 4.99116e-5 \\\\\n",
"\t25 & 2014-01-02T00:00:00 & -1.30811 & -1.33167 & 0.000555052 \\\\\n",
"\t26 & 2014-01-02T01:00:00 & -0.303306 & -1.04321 & 0.547464 \\\\\n",
"\t27 & 2014-01-02T02:00:00 & 0.701501 & -0.590056 & 1.66812 \\\\\n",
"\t28 & 2014-01-02T03:00:00 & 0.701501 & -0.0437399 & 0.555384 \\\\\n",
"\t29 & 2014-01-02T04:00:00 & 0.701501 & 0.509482 & 0.0368714 \\\\\n",
"\t30 & 2014-01-02T05:00:00 & 1.03306 & 0.982267 & 0.00257969 \\\\\n",
"\t$\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ \\\\\n",
"\\end{tabular}\n"
],
"text/plain": [
"49×4 DataFrame\n",
"│ Row │ Date │ MissingVals │ Value │ error │\n",
"│ │ \u001b[90mDateTime\u001b[39m │ \u001b[90mFloat64⍰\u001b[39m │ \u001b[90mFloat64⍰\u001b[39m │ \u001b[90mFloat64\u001b[39m │\n",
"├─────┼─────────────────────┼─────────────┼───────────┼─────────────┤\n",
"│ 1 │ 2014-01-01T00:00:00 │ 0.746646 │ 1.36329 │ 0.380248 │\n",
"│ 2 │ 2014-01-01T01:00:00 │ 0.746646 │ 1.19324 │ 0.199444 │\n",
"│ 3 │ 2014-01-01T02:00:00 │ 0.746646 │ 0.804733 │ 0.00337414 │\n",
"│ 4 │ 2014-01-01T03:00:00 │ -0.105454 │ 0.289179 │ 0.155736 │\n",
"│ 5 │ 2014-01-01T04:00:00 │ -0.957554 │ -0.272029 │ 0.469945 │\n",
"│ 6 │ 2014-01-01T05:00:00 │ -0.957554 │ -0.790291 │ 0.0279772 │\n",
"│ 7 │ 2014-01-01T06:00:00 │ -1.18563 │ -1.18378 │ 3.40069e-6 │\n",
"│ 8 │ 2014-01-01T07:00:00 │ -1.4137 │ -1.39038 │ 0.000543709 │\n",
"│ 9 │ 2014-01-01T08:00:00 │ -1.38614 │ -1.37747 │ 7.52128e-5 │\n",
"│ 10 │ 2014-01-01T09:00:00 │ -1.05908 │ -1.14708 │ 0.00774523 │\n",
"⋮\n",
"│ 39 │ 2014-01-02T14:00:00 │ -1.38786 │ -1.33 │ 0.00334763 │\n",
"│ 40 │ 2014-01-02T15:00:00 │ -1.41018 │ -1.40712 │ 9.38735e-6 │\n",
"│ 41 │ 2014-01-02T16:00:00 │ -1.23038 │ -1.26773 │ 0.00139453 │\n",
"│ 42 │ 2014-01-02T17:00:00 │ -0.730748 │ -0.925126 │ 0.0377827 │\n",
"│ 43 │ 2014-01-02T18:00:00 │ -0.231113 │ -0.436468 │ 0.0421707 │\n",
"│ 44 │ 2014-01-02T19:00:00 │ 0.552253 │ 0.121099 │ 0.185894 │\n",
"│ 45 │ 2014-01-02T20:00:00 │ 1.33562 │ 0.659546 │ 0.457074 │\n",
"│ 46 │ 2014-01-02T21:00:00 │ 1.33562 │ 1.09387 │ 0.0584445 │\n",
"│ 47 │ 2014-01-02T22:00:00 │ 1.33562 │ 1.35549 │ 0.000394795 │\n",
"│ 48 │ 2014-01-02T23:00:00 │ 1.41122 │ 1.40311 │ 6.58315e-5 │\n",
"│ 49 │ 2014-01-03T00:00:00 │ 1.19439 │ 1.26403 │ 0.00484856 │"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"jx = join(pred_y,pred_yy,on=:Date)\n",
"jx.error = (jx.MissingVals .- jx.Value).^2;jx"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"@webio": {
"lastCommId": null,
"lastKernelId": null
},
"kernelspec": {
"display_name": "Julia 1.2.0",
"language": "julia",
"name": "julia-1.2"
},
"language_info": {
"file_extension": ".jl",
"mimetype": "application/julia",
"name": "julia",
"version": "1.2.0"
}
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"nbformat": 4,
"nbformat_minor": 2
}