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237 | with System ;
with Ada.Text_IO; use Ada.Text_IO;
with Ada.Text_IO.C_Streams;
with Ada.Long_Float_Text_IO; use Ada.Long_Float_Text_IO;
with Ada.Integer_Text_IO; use Ada.Integer_Text_IO;
with Interfaces.C; use Interfaces.C;
with Interfaces.C.Strings; use Interfaces.C.Strings;
with Ada.Strings.Unbounded; use Ada.Strings.Unbounded;
with Ada.Command_Line; use Ada.Command_Line;
with Ada.Numerics.Elementary_Functions ; use Ada.Numerics.Elementary_Functions;
with GNAT.Source_Info; use GNAT.Source_Info;
with gsl;
with gsl.movstat ;
with gsl.rng ;
with gsl.randist ;
with gsl.vector_double ;
with math ;
with windowing ;
procedure Movstat is
N : Integer := 500 ; -- Length of time series
K : Integer := 11 ; -- Window Size
NN : Integer := 1000 ;
KK : Integer := 41 ;
Status : Int ;
function sign(x : double) return double is
begin
if x >= 0.0
then
return 1.0 ;
else
return -1.0 ;
end if ;
end sign ;
procedure Test1 is
ws : access gsl.movstat.gsl_movstat_workspace :=
gsl.movstat.alloc( size_t(K) );
x : access gsl.vector_double.gsl_vector :=
gsl.vector_double.alloc ( size_t(N) ) ;
xmean : access gsl.vector_double.gsl_vector :=
gsl.vector_double.alloc (size_t(N)) ;
xmin : access gsl.vector_double.gsl_vector :=
gsl.vector_double.alloc ( size_t(N) ) ;
xmax : access gsl.vector_double.gsl_vector :=
gsl.vector_double.alloc (size_t(N)) ;
rng : access gsl.rng.gsl_rng := gsl.rng.alloc(gsl.rng.default) ;
ei : double ;
xi : double ;
csvfilename : String := gnat.source_info.enclosing_entity & ".csv" ;
csvfile : File_Type ;
begin
Put_Line(gnat.source_info.enclosing_entity);
Create(csvfile,Out_File,csvfilename);
Set_Output(csvfile);
for i in 1..N
loop
xi := double(cos(4.0 * math.M_PI * Float(i) / Float(N))) ;
ei := gsl.randist.gaussian(rng,0.1);
gsl.vector_double.set(x , size_t(i-1) , xi + ei );
--Put(Long_Float(xi)); Put(" "); Put(Long_Float(ei)); Put(" "); New_Line;
end loop ;
Status := gsl.movstat.mean(gsl.movstat.GSL_MOVSTAT_END_PADVALUE,x , xmean, ws);
Status := gsl.movstat.minmax(gsl.movstat.GSL_MOVSTAT_END_PADVALUE,x , xmin, xmax, ws);
for i in 1..N
loop
Put(i) ; Put(" ; ");
Put(Long_Float(gsl.vector_double.get(x,size_t(i-1)))); Put(" ; ");
Put(Long_Float(gsl.vector_double.get(xmean,size_t(i-1)))); Put(" ; ");
Put(Long_Float(gsl.vector_double.get(xmin,size_t(i-1)))); Put(" ; ");
Put(Long_Float(gsl.vector_double.get(xmax,size_t(i-1)))); Put(" ");
New_Line;
end loop ;
Set_Output(Standard_Output);
Close(csvfile);
gsl.vector_double.free(xmax);
gsl.vector_double.free(xmin);
gsl.vector_double.free(xmean);
gsl.vector_double.free(x);
end Test1 ;
procedure Test2 is
rng : access gsl.rng.gsl_rng := gsl.rng.alloc(gsl.rng.default) ;
ws : access gsl.movstat.gsl_movstat_workspace :=
gsl.movstat.alloc( size_t(KK) );
x : access gsl.vector_double.gsl_vector :=
gsl.vector_double.alloc ( size_t(NN) ) ;
xmedian : access gsl.vector_double.gsl_vector :=
gsl.vector_double.alloc ( size_t(NN) ) ;
xmad : access gsl.vector_double.gsl_vector :=
gsl.vector_double.alloc ( size_t(NN) ) ;
xiqr : access gsl.vector_double.gsl_vector :=
gsl.vector_double.alloc ( size_t(NN) ) ;
xSn : access gsl.vector_double.gsl_vector :=
gsl.vector_double.alloc ( size_t(NN) ) ;
xQn : access gsl.vector_double.gsl_vector :=
gsl.vector_double.alloc ( size_t(NN) ) ;
xsd : access gsl.vector_double.gsl_vector :=
gsl.vector_double.alloc ( size_t(NN) ) ;
csvfilename : String := gnat.source_info.enclosing_entity & ".csv" ;
csvfile : File_Type ;
sigma : gsl.double_array := (1.0, 5.0, 1.0, 3.0, 5.0) ;
N_Sigma : array (1..5) of size_t := (200,450,600,850,1000) ;
gi, u, outlier, xi : double ;
varidx : size_t := 1 ; -- variance changes
begin
Put_Line(gnat.source_info.enclosing_entity);
Create(csvfile,Out_File,csvfilename);
Set_Output(csvfile);
for i in 1..NN
loop
gi := gsl.randist.gaussian(rng,sigma(Integer(varidx)-1)) ;
u := gsl.rng.uniform(rng);
if u < 0.01
then
outlier := 15.0 * sign(gi);
else
outlier := 0.0 ;
end if ;
xi := gi + outlier ;
gsl.vector_double.set(x,size_t(i-1),xi);
if size_t(i) = N_Sigma(Integer(varidx))
then
varidx := varidx + 1;
end if ;
end loop ;
Status := gsl.movstat.mad(gsl.movstat.GSL_MOVSTAT_END_TRUNCATE, x, xmedian, xmad, ws);
Status := gsl.movstat.qqr(gsl.movstat.GSL_MOVSTAT_END_TRUNCATE, x, 0.25, xiqr, ws);
Status := gsl.movstat.Sn(gsl.movstat.GSL_MOVSTAT_END_TRUNCATE, x, xSn, ws);
Status := gsl.movstat.Qn(gsl.movstat.GSL_MOVSTAT_END_TRUNCATE, x, xQn, ws);
Status := gsl.movstat.sd(gsl.movstat.GSL_MOVSTAT_END_TRUNCATE, x, xsd, ws);
Status := gsl.vector_double.scale(xiqr, 0.7413);
varidx := 1;
for i in 1..NN
loop
Put(i); Put(" ; ");
Put(Long_Float(gsl.vector_double.get(x,size_t(i-1)))); Put(" ; ");
Put(Long_Float(sigma(Integer(varidx)-1))); Put(" ; ");
Put(Long_Float(gsl.vector_double.get(xmad,size_t(i-1)))); Put(" ; ");
Put(Long_Float(gsl.vector_double.get(xiqr,size_t(i-1)))); Put(" ; ");
Put(Long_Float(gsl.vector_double.get(xSn,size_t(i-1)))); Put(" ; ");
Put(Long_Float(gsl.vector_double.get(xQn,size_t(i-1)))); Put(" ; ");
Put(Long_Float(gsl.vector_double.get(xsd,size_t(i-1)))); Put(" ; ");
New_Line;
if size_t(i) = N_Sigma(Integer(varidx))
then
varidx := varidx + 1;
end if ;
end loop ;
Set_Output(Standard_Output);
Close(csvfile);
gsl.vector_double.free(x);
gsl.vector_double.free(xmedian);
gsl.vector_double.free(xmad);
gsl.vector_double.free(xiqr);
gsl.vector_double.free(xSn);
gsl.vector_double.free(xQn);
gsl.vector_double.free(xsd);
gsl.rng.free(rng);
gsl.movstat.free(ws);
end Test2 ;
fn : aliased gsl.movstat.gsl_movstat_function ;
procedure Test3 is
proc : String := gnat.source_info.enclosing_entity ;
N3 : constant := 1000 ;
K3 : constant := 11 ;
alpha : double := 0.1 ;
x : access gsl.vector_double.gsl_vector := gsl.vector_double.alloc(N3) ;
y : access gsl.vector_double.gsl_vector := gsl.vector_double.alloc(N3) ;
rng : access gsl.rng.gsl_rng := gsl.rng.alloc(gsl.rng.default);
ws : access gsl.movstat.gsl_movstat_workspace :=
gsl.movstat.alloc( size_t(K3) );
ui, outlier : double ;
sum : double := 0.0 ;
temp : double ;
csvfile : File_Type ;
begin
Put_line(proc);
for i in 1..N3
loop
ui := gsl.randist.gaussian(rng,1.0);
temp := gsl.rng.uniform(rng);
if temp < 0.01
then
outlier := sign(ui) * 10.0;
else
outlier := 0.0 ;
end if;
sum := sum + ui ;
gsl.vector_double.set(x,size_t(i-1),sum+outlier);
end loop;
Create(csvfile,Out_File,proc & ".csv") ;
Set_Output(csvfile);
fn.c_function := windowing.windowingfn'access ;
fn.params := alpha'Address ;
Status := gsl.movstat.apply(gsl.movstat.GSL_MOVSTAT_END_PADVALUE , fn'access , x , y , ws );
for i in 1..N3
loop
Put(i) ; Put(" ; ");
Put(Long_Float(gsl.vector_double.get(x,size_t(i-1)))); Put(" ; ");
Put(Long_Float(gsl.vector_double.get(y,size_t(i-1)))); Put(" ; ");
New_Line;
end loop ;
Set_Output(Standard_Output);
Close(csvfile);
gsl.vector_double.free(x);
gsl.vector_double.free(y);
gsl.movstat.free(ws);
gsl.rng.free(rng);
end Test3 ;
begin
if Argument_Count > 0
then
N := Integer'Value( Argument(1) );
if Argument_Count > 1
then
K := Integer'Value( Argument(2) );
end if ;
end if ;
Ada.Long_Float_Text_IO.Default_aft := 4 ;
Ada.Long_Float_Text_IO.Default_exp := 0 ;
Test1 ;
Test2 ;
Test3 ;
end Movstat;
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