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<h2>test-data.lua</h2>
<pre>
<span class="comment">--_DEBUG=true
</span>data = <span class="global">require</span> <span class="string">'pl.data'</span>
List = <span class="global">require</span> <span class="string">'pl.List'</span>
array = <span class="global">require</span> <span class="string">'pl.array2d'</span>
seq = <span class="global">require</span> <span class="string">'pl.seq'</span>
utils = <span class="global">require</span> <span class="string">'pl.utils'</span>
stringio = <span class="global">require</span> <span class="string">'pl.stringio'</span>
open = stringio. open
asserteq = <span class="global">require</span> <span class="string">'pl.test'</span> . asserteq
T = <span class="global">require</span> <span class="string">'pl.test'</span>. tuple
<span class="comment">--[=[
dat,err = data.read(open [[
1.0 0.1
0.2 1.3
]])
if err then print(err) end
require 'pl.pretty'.dump(dat)
os.exit(0)
--]=]</span>
<span class="comment">-- tab-separated data, explicit column names
</span>t1f = open <span class="string">[[
EventID Magnitude LocationX LocationY LocationZ LocationError EventDate DataFile
981124001 2.0 18988.4 10047.1 4149.7 33.8 24/11/1998 11:18:05 981124DF.AAB
981125001 0.8 19104.0 9970.4 5088.7 3.0 25/11/1998 05:44:54 981125DF.AAB
981127003 0.5 19012.5 9946.9 3831.2 46.0 27/11/1998 17:15:17 981127DF.AAD
981127005 0.6 18676.4 10606.2 3761.9 4.4 27/11/1998 17:46:36 981127DF.AAF
981127006 0.2 19109.9 9716.5 3612.0 11.8 27/11/1998 19:29:51 981127DF.AAG
]]</span>
t1 = data.read (t1f)
<span class="comment">-- column_by_name returns a List
</span>asserteq(t1:column_by_name <span class="string">'Magnitude'</span>,List{<span class="number">2</span>,<span class="number">0.8</span>,<span class="number">0.5</span>,<span class="number">0.6</span>,<span class="number">0.2</span>})
<span class="comment">-- can use array.column as well
</span>asserteq(array.column(t1,<span class="number">2</span>),{<span class="number">2</span>,<span class="number">0.8</span>,<span class="number">0.5</span>,<span class="number">0.6</span>,<span class="number">0.2</span>})
<span class="comment">-- only numerical columns (deduced from first data row) are converted by default
</span><span class="comment">-- can look up indices in the list fieldnames.
</span>EDI = t1.fieldnames:index <span class="string">'EventDate'</span>
<span class="global">assert</span>(<span class="global">type</span>(t1[<span class="number">1</span>][EDI]) == <span class="string">'string'</span>)
<span class="comment">-- select method returns a sequence, in this case single-valued.
</span><span class="comment">-- (Note that seq.copy returns a List)
</span>asserteq(seq(t1:<span class="global">select</span> <span class="string">'LocationX where Magnitude > 0.5'</span>):copy(),List{<span class="number">18988.4</span>,<span class="number">19104</span>,<span class="number">18676.4</span>})
<span class="comment">--[[
--a common select usage pattern:
for event,mag in t1:select 'EventID,Magnitude sort by Magnitude desc' do
print(event,mag)
end
--]]</span>
<span class="comment">-- space-separated, but with last field containing spaces.
</span>t2f = open <span class="string">[[
USER PID %MEM %CPU COMMAND
sdonovan 2333 0.3 0.1 background --n=2
root 2332 0.4 0.2 fred --start=yes
root 2338 0.2 0.1 backyard-process
]]</span>
t2,err = data.read(t2f,{last_field_collect=<span class="keyword">true</span>})
<span class="keyword">if</span> <span class="keyword">not</span> t2 <span class="keyword">then</span> <span class="keyword">return</span> <span class="global">print</span> (err) <span class="keyword">end</span>
<span class="comment">-- the last_field_collect option is useful with space-delimited data where the last
</span><span class="comment">-- field may contain spaces. Otherwise, a record count mismatch should be an error!
</span>lt2 = List(t2[<span class="number">2</span>])
asserteq(lt2:join <span class="string">','</span>,<span class="string">'root,2332,0.4,0.2,fred --start=yes'</span>)
<span class="comment">-- fieldnames are converted into valid identifiers by substituting _
</span><span class="comment">-- (we do this to make select queries parseable by Lua)
</span>asserteq(t2.fieldnames,List{<span class="string">'USER'</span>,<span class="string">'PID'</span>,<span class="string">'_MEM'</span>,<span class="string">'_CPU'</span>,<span class="string">'COMMAND'</span>})
<span class="comment">-- select queries are NOT SQL so remember to use == ! (and no 'between' operator, sorry)
</span><span class="comment">--s,err = t2:select('_MEM where USER="root"')
</span><span class="comment">--assert(err == [[[string "tmp"]:9: unexpected symbol near '=']])
</span>
s = t2:<span class="global">select</span>(<span class="string">'_MEM where USER=="root"'</span>)
<span class="global">assert</span>(s() == <span class="number">0.4</span>)
<span class="global">assert</span>(s() == <span class="number">0.2</span>)
<span class="global">assert</span>(s() == <span class="keyword">nil</span>)
<span class="comment">-- CSV, Excel style. Double-quoted fields are allowed, and they may contain commas!
</span>t3f = open <span class="string">[[
"Department Name","Employee ID",Project,"Hours Booked"
sales,1231,overhead,4
sales,1255,overhead,3
engineering,1501,development,5
engineering,1501,maintenance,3
engineering,1433,maintenance,10
]]</span>
t3 = data.read(t3f,{csv=<span class="keyword">true</span>})
<span class="comment">-- although fieldnames are turned in valid Lua identifiers, there is always <code>original_fieldnames</code>
</span>asserteq(t3.fieldnames,List{<span class="string">'Department_Name'</span>,<span class="string">'Employee_ID'</span>,<span class="string">'Project'</span>,<span class="string">'Hours_Booked'</span>})
asserteq(t3.original_fieldnames,List{<span class="string">'Department Name'</span>,<span class="string">'Employee ID'</span>,<span class="string">'Project'</span>,<span class="string">'Hours Booked'</span>})
<span class="comment">-- a common operation is to select using a given list of columns, and each row
</span><span class="comment">-- on some explicit condition. The select() method can take a table with these
</span><span class="comment">-- parameters
</span>keepcols = {<span class="string">'Employee_ID'</span>,<span class="string">'Hours_Booked'</span>}
q = t3:<span class="global">select</span> { fields = keepcols,
where = <span class="keyword">function</span>(row) <span class="keyword">return</span> row[<span class="number">1</span>]==<span class="string">'engineering'</span> <span class="keyword">end</span>
}
asserteq(seq.copy2(q),{{<span class="number">1501</span>,<span class="number">5</span>},{<span class="number">1501</span>,<span class="number">3</span>},{<span class="number">1433</span>,<span class="number">10</span>}})
<span class="comment">-- another pattern is doing a select to restrict rows & columns, process some
</span><span class="comment">-- fields and write out the modified rows.
</span>
utils.import <span class="string">'pl.func'</span>
outf = stringio.create()
names = {[<span class="number">1501</span>]=<span class="string">'don'</span>,[<span class="number">1433</span>]=<span class="string">'dilbert'</span>}
t3:write_row (outf,{<span class="string">'Employee'</span>,<span class="string">'Hours_Booked'</span>})
q = t3:select_row {fields=keepcols,where=Eq(_1[<span class="number">1</span>],<span class="string">'engineering'</span>)}
<span class="keyword">for</span> row <span class="keyword">in</span> q <span class="keyword">do</span>
row[<span class="number">1</span>] = names[row[<span class="number">1</span>]]
t3:write_row(outf,row)
<span class="keyword">end</span>
asserteq(outf:value(),
<span class="string">[[
Employee,Hours_Booked
don,5
don,3
dilbert,10
]]</span>)
<span class="comment">-- data may not always have column headers. When creating a data object
</span><span class="comment">-- from a two-dimensional array, may specify the fieldnames, as a list or a string.
</span><span class="comment">-- The delimiter is deduced from the fieldname string, so a string just containing
</span><span class="comment">-- the delimiter will set it, and the fieldnames will be empty.
</span><span class="keyword">local</span> dat = List()
<span class="keyword">local</span> row = List.range(<span class="number">1</span>,<span class="number">10</span>)
<span class="keyword">for</span> i = <span class="number">1</span>,<span class="number">10</span> <span class="keyword">do</span>
dat:append(row:map(<span class="string">'*'</span>,i))
<span class="keyword">end</span>
dat = data.new(dat,<span class="string">','</span>)
<span class="keyword">local</span> out = stringio.create()
dat:write(out,<span class="string">','</span>)
asserteq(out:value(), <span class="string">[[
1,2,3,4,5,6,7,8,9,10
2,4,6,8,10,12,14,16,18,20
3,6,9,12,15,18,21,24,27,30
4,8,12,16,20,24,28,32,36,40
5,10,15,20,25,30,35,40,45,50
6,12,18,24,30,36,42,48,54,60
7,14,21,28,35,42,49,56,63,70
8,16,24,32,40,48,56,64,72,80
9,18,27,36,45,54,63,72,81,90
10,20,30,40,50,60,70,80,90,100
]]</span>)
<span class="comment">-- you can always use numerical field indices, AWK-style;
</span><span class="comment">-- note how the copy_select method gives you a data object instead of an
</span><span class="comment">-- iterator over the fields
</span><span class="keyword">local</span> res = dat:copy_select <span class="string">'$1,$3 where $1 > 5'</span>
<span class="keyword">local</span> L = List
asserteq(L(res),L{
L{<span class="number">6</span>, <span class="number">18</span>},
L{<span class="number">7</span>,<span class="number">21</span>},
L{<span class="number">8</span>,<span class="number">24</span>},
L{<span class="number">9</span>,<span class="number">27</span>},
L{<span class="number">10</span>,<span class="number">30</span>},
})
<span class="comment">-- the column_by_name method may take a fieldname or an index
</span>asserteq(dat:column_by_name(<span class="number">2</span>), L{<span class="number">2</span>,<span class="number">4</span>,<span class="number">6</span>,<span class="number">8</span>,<span class="number">10</span>,<span class="number">12</span>,<span class="number">14</span>,<span class="number">16</span>,<span class="number">18</span>,<span class="number">20</span>})
<span class="comment">-- the field list may contain expressions or even constants
</span><span class="keyword">local</span> q = dat:<span class="global">select</span> <span class="string">'$3,2*$4 where $1 == 8'</span>
asserteq(T(q()),T(<span class="number">24</span>,<span class="number">64</span>))
dat,err = data.read(open <span class="string">[[
1.0 0.1
0.2 1.3
]]</span>)
<span class="keyword">if</span> err <span class="keyword">then</span> <span class="global">print</span>(err) <span class="keyword">end</span>
<span class="comment">-- if a method cannot be found, then we look up in array2d
</span><span class="comment">-- array2d.flatten(t) makes a 1D list out of a 2D array,
</span><span class="comment">-- and then List.minmax() gets the extrema.
</span>
asserteq(T(dat:flatten():minmax()),T(<span class="number">0.1</span>,<span class="number">1.3</span>))
f = open <span class="string">[[
Time Message
1266840760 +# EE7C0600006F0D00C00F06010302054000000308010A00002B00407B00
1266840760 closure data 0.000000 1972 1972 0
1266840760 ++ 1266840760 EE 1
1266840760 +# EE7C0600006F0D00C00F06010302054000000408020A00002B00407B00
1266840764 closure data 0.000000 1972 1972 0
1266840764 ++ 1266840764 EE 1
1266840764 +# EE7C0600006F0D00C00F06010302054000000508030A00002B00407B00
1266840768 duplicate?
1266840768 +# EE7C0600006F0D00C00F06010302054000000508030A00002B00407B00
1266840768 closure data 0.000000 1972 1972 0
]]</span>
<span class="comment">-- the <code>convert</code> option provides custom converters for each specified column.
</span><span class="comment">-- Here we convert the timestamps into Date objects and collect everything
</span><span class="comment">-- else into one field
</span><span class="keyword">local</span> Date = <span class="global">require</span> <span class="string">'pl.Date'</span>
<span class="keyword">local</span> <span class="keyword">function</span> date_convert (ds)
<span class="keyword">return</span> Date(<span class="global">tonumber</span>(ds))
<span class="keyword">end</span>
d = data.read(f,{convert={[<span class="number">1</span>]=date_convert},last_field_collect=<span class="keyword">true</span>})
asserteq(#d[<span class="number">1</span>],<span class="number">2</span>)
asserteq(d[<span class="number">2</span>][<span class="number">1</span>]:year(),<span class="number">2010</span>)</pre>
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