validate


anc
fac        field
genetic
image        interaction        inv
law        limit        local
menu        message        motif        mouse
normal        network        network_vol
obj
palette        particle        pers        pixel        poi        properties
see        speed        sphere
view
win
Voir aussi.

validate anc

Recalculates the anchor matrices.

validate field

validate field(id)

        Returns the field id validation.

validate field(id)=v

        Changes this validation.
Notes:
1) v=1: active (default).
v=0: passive.
2) all fields by default.

validate fac

validate fac(f) vol(id)

        Returns the facet f of volume id validation.

validate fac(f) vol(id)=v

        Validates the facet f of the volume id.
v=-1: inhibits facet f (not displayed).
v=1: validates facet f (default).
All facets by default.

validate fac(f)ext vol(id)

        Returns the extension facet f of volume id validation.

validate fac(f)ext vol(id)=v

        Validates the extension facet f of the volume id.

validate genetic

validate validate genetic(id)

        Returns the validation flag of genetic(id) and NIL if tne genetic does not exist.

validate validate genetic(id)=v

        Change this flag.

validate genetic(id)

        Evaluates genetic id (all by default) that is calculated in scale particle genetic(id) the returns of the evaluation function for each individual of the population id.
Options:
particle(num): evluates only particles num.
var: returns the average evaluatiuon of the genetic (or of the particles num if option particle(num) is present).

validate image

validate image(id)

        Returns the validation flag of the image id.

validate image(id)=v

        Changes this flag.
Note:
v = 0: invalid, image not displayed (default).
v = 1: valid, image displayed.
v = -1: image not displayed but possibly animated.

validate(1)image(id)

        Saves the image id in the block validate.

validate(-1)image(id)

        Restores the image id if it has been saved.
Note: not be confused with validate image(id)=v.

validate interaction

validate interaction write name("nnn")

        Returns 0 if animation (initiated by interaction write name'"nnn") is completed.

validate inv law network

validate inv law(L) network(r1,r2,...)

        Determines the network ri which a law was closest to L and returns the motif correcpondant.
Useful in environement multi networks.

validate law CG vol(id)

        Returns the power 1/3 law evaluation of the law CG vol(id).

validate limit

validate(x)limit(x1,x2,y1,y2)

        Returns y = y1 + (x - x1) * (y2 - y1) / (x2 - x1)

validate(x)limit(x1,x2,y1,y2)inv

        Returns x = x1 + (y - y1) * (x2 - x1) / (y2 - y1)
Note:
Used to code motif and decode law of a neural network.
Examples:
motif(0)network(1)=validate(.25*PI)limit(-P1,PI,0,1);
        codes an angle.
an=validate(0.625)limit(-P1,PI,0,1)inv;
        decodes an angle.
motif(0)network(1)=validate(-1,0,1)limit(-1,1,0,1);
        codes an axis.
ax=validate(0,.5,1)limit(-1,1,0,1)inv;
        decodes an axis.

validate local

validate local obj(id)

        Returns the validate flag of the 1st local function of the object id of type obj.

validate local obj(id)=b

        Changes this flag.
Notes:
All objects of type obj by default.
This command allows you to ignore (validate = 0) or make it active (validate = 1) local functions of the object id.

validate menu

validate menu

        Returns the validation flags of menus..

validate menu=v

v=1: visible menus (default) equivalent to yes menu.
v=0: invisible menus equivalent to no menu.

validate menu("MEN")

        Returns the validation flag of the menu "MEN"

validate menu("MEN")=v

v=1: menu "MEN" visible (default). v=0: menu "MEN" invisible .

validate menu("f0")menu("fi")

     Returns the validation flag of the function fi of the menu f0. (>0 if active, <0 if passive, 0 si neutral).

validate menu("f0")menu("fi")=1

     Makes active function fi of the menu f0.

validate menu("f0")menu("fi")=0

     Makes passive function fi of menu f0.
Note:
validate menu("f0")menu("*")=v
     Change the flag of all functions of menu f0.

validate menu interaction

     Regenerates the interaction menus.

validate message

validate message(id)

        Returns the validation flag of the message identifier id.

validate message(id)=v

        Changes this flag.
v=1: active message (default).
v=0: inhibited message.

validate motif

validate motif(in) network(id)

        Returns the output of the neural network id for the input in.

validate motif(in) network(id)speed

        Returns the output speed of the id for network in.

validate motif(m)network(1)neuronne

       Returns the number of the winner neuron and its activation when the network is of type Kohonen.

validate motif(m) network(r1,r2,...)

        Determines, the network ri, for which a motif is nearest of m and do: validate motif(m) network(ri), returning the correspondant law.

validate motif(m) average network(r1,r2,...)

       Determines, for each network ri, the minimum distance di from m to all learning motifs, and returns the weighted (by di) sum of outputs of these networks for input m.
Useful in environement of multi networks.
See also:
validate network
validate inv law network

validate motif(m)network(id)roll

        Returns the output of the network id for input m, the motifs block works like a circular stack in which is inserted m (useful fornetworks of type near).

validate normal

validate normal vol(id)

        If the vertices of the volume id have no normal, they are created null (0,0,0).

validate obj

validate obj(id)

        Returns the validation flag of the object id of type obj:
1 validated.
0 invalidated (inactive and not viewable, but its followers are displayed).
-1 if object is invalidated as well as its followers.
-2 if object is invalidated but not its motifs.
-3 if object is invalidated as well as its followers, but not its motifs.
-4 inhibites the dynamic for this object.
-5 taken into account but not displayed;.
NIL if object does not exist.
Notes:
1) validate obj=v; validated (v=1), or invalidated (v=0) all objects of type obj.
2) For a network validate network has another meaning, use validate validate network(id).
NP motif network(id) returns NIL if network id does not exist, 0 if it exists but does not has motif, otherwise returns the number of the motifs.
3) For a genetic validate genetic has another meaning, use validate validate genetic(id).
NP particle genetic(id) returns NIL if genetic id does not exist, 0 if it exists but has no particle, otherwise returne the number of the particles.
4) For a volumes structure anchored id0,id1,id2,... of root id0, if you want to view only the volume idi, write:
       validate vol(id0,id1,id2,...)=0;validate vol(id0,idi)=1;

validate obj(id)=v

        Changes this flag.
Note:
v = 1: object is active.
v = 0: object is inactive.
validate obj: all objects obj.

validate palette

Validates the palette mode: useful before display.

validate particle

validate particle(p) genetic(id)

        Evaluates the individual p of the genetic id, ie computes in scale particle(p) genetic(g) the return of the evaluation function func genetic(g) for individual p of the population id.

validate pers

validate pers(x,y,z)

        In a local function, this cammand validates the perspective at point (x,y,z).
Notes:
See procedural perspective.
Must do: yes local and yes pers

validate pers vol(id)


        The algorithm implementation classical perspective (conical) using homogeneous coordinates (4D). In principle it is up to deform the database as if it were cylindrical perspective (from an eye to infinity). The advantage of this method is to reduce the conical projection to a cylindrical projection (easier especially with regard to the clipping). The validate pers vol actually generates the modified database. For another point of view we get strange effects ...

pers validate vertex (s) vol (id)


        Only the vertices numbered s of thevolume id will be treated.

validate pixel

validate(1) pixel image(id)

        Saves the image id pixels.

validate(-1) pixel image(id)

        Restores the image id pixels.

validate poi

validate(1) poi vol(id)

        Saves the volume id points in thevalidate poi block.

validate(-1) poi vol(id)

        Restores the volume id points.
Options:
poi(n): restores only points number n.
frac ext or generate: processes with the extension points or with the fractal points.
Note: if the validate poi block does nt exist, validate(-1) poi vol(id) builds it by duplication of poi block.

validate properties

validate propr1 propr2 vol(id)

        Transmits as inputs of the network network propr1 propr2 vol(id) parameters of the property propr1, the output provides the parameters boundaries of the property propr2 which then forced inside this interval.
Note: First must be
built networks by:
r=network propr1 propr2 vol(id)
defined learning pairs:
motif propr1 propr2 vol(id)=M1,M2,....
law propr1 propr2 vol(id)=L1,L2,....
and trained the networks by:
validate(n)network(r).

validate network

validate(n,i0,nc) network(id)

        Adapts the network id weights to the set of pairs (motif, law) in n passes maximum.
If i0 is absent or i0=0: nb evaluations.
Otherwise if i0 > ;0: parallel processing image i0
If nc is present: depth of the recurrence (network near).
Returns cpt,err,stat
        cpt = number of steps actually realized
        err = maximum error committed
        stat = 1 if end of a parallel processing

validate(n,i0,nc)error(max_err)coe(c1,c2)time(t)network(id)

        Allows specify some parameters:
1) Learning is stopped as soon as the error is less than max_err.
2) c1 and c2 are the learning constants. (1.0, 0.01 default).
time(t) for network of type near.

validate network number

        Returns the network number ri which a pattern is closest to m, see: validate motif(m)network(r1,r2,..)
Example of use (in a program loop):
nb=validate(n,1)network(1)error(.02)read("r");
nb=validate(n,2)network(1)error(.02);
....................................
nb=validate(n,n)network(1)error(.02);
if(nb[2]): end
validate(n) coe(c1,c2) error(eps) network(num)
        The "eta" value of errors correction varies from c1 (step 1) to c2 (step n). By default c1=c2=0.5
validate(n) law(0,c1,0,.1,c2,0,...,1,cn,0) error(eps) network(num)
        The "eta" value of the errors correction varies according a law
Example:
validate(5000) law(0,1,0, .5,.2,0, 1,.1,0) network(1)
Learning stops as soon as the error is less than eps
by default eps=0.1
validate(n) network(num) edit
        Couples (output-desired, output-calculated) are published
        Errors are highlighted by: ********
        The errors number and the maximum error are published.
        The steps number and the maximum error are returned see
network
validate(n) network(id) read("F")
        F is a file of the form:
x1,x2,...,xn
y1,y2,...,ym
x1,x2,...,xn
y1,y2,...,ym
....
Inputs motifs are: (x1,x2,...,xn)

The network id is created ans trained in n steps.
Options:
write("R"): the adapted network is saved in file R.res
mass(m1,m2): weights are randomly generated between m1 and m2. (-1,1 defult)
rand: no reproductible random (default)
alea: reproductible random
alea(ind): reproductible of seed num
error(eps): the tolerated error is eps (0.1 par défaut)
validate(n) network(num) read("F") format(m1,m2,l1,l2)
        Default motifs and laws must be normalized between 0 and 1. format (m1, m2, l1, l2) can return motifs between m1 and m2, and laws between l1 and l2.
See also:
validate motif network
validate inv law network

validate network vol

validate(n,i0,nc) network vol(id)

        Built an internal network with 7 neurons to volume id:
(1,2,3) the input layer receiving the axes (x, y, z).
(4.5) of the hidden layer.
(6.7) of the output layer outputting boundaries (a1, a2).
The network is trained on n passes.

validate network vol(id)

At each image of the animation (typically a function func func(4,"F4") passes the axis (x, y, z) of the volume id as entry of the network which provides an output (a1, a2), the rotation angle a of the volume is forced id between a1 and a2.

validate validate network(id)

        Returns the validation flag of network id and NIL if tne network does not exist.

validate validate network(id)=v

        Change this flag.

validate mouse

validate mouse

Returns the 3D polygonal line entry by mouse.

validate mouse speed

       Returns the 3D polygonal line entry by mouse speed (x1,y1,0,x2,y2,t1,...,xn,yn,tn) with ti = input time.

validate see

validate see

        Switches in see mode: see bar appears at the top right corner of the screen, if you click on the dash is activated see.

validate(0)see

        Inhibits see mode.

validate speed

validate speed vol(id)

        If the volume has no mass, or if no dynamic is set, the speed of volume id is computed.
Options:
validate(v): multiplier of speed (1 default).

validate speed rota vol(id)

        If the volume has no mass, or if no dynamic is set, the speed rota of volume id is computed.
Options:
validate(v): multiplier of speed (1 default).

validate sphere

validate sphere

        Returns the display flag of the object sphere.

validate sphere=v

       Gives value v to the display flag of the object sphere.
v=1: displayable.
v=0: no displayable.

validate view

validate view(id)

        Returns the view id flag (all views by default).

validate view(id)=v

        Gives to view id flag the v value:
v=1: active.
b=0: passive.
All views by default.
Notes:
For several activated views, must do yes view

validate win

validate win(id)

        Returns the window id validation.

validate win(id)=v

        Validates (v=1) or inhibits (v=0) the window id.

See also:


validate a transformation