#!/usr/bin/env python3
"""Produce 10 fully deterministic, illustrative scientific SVGs and CSV tables for COMPLEXA C161–C170.
All curves follow explicitly stated equations in the respective manuscripts; no clinical,
observational or empirical dataset is asserted. Python 3.10+ standard library only.
python make_figures.py --out DIR
python make_figures.py --check DIR # reproducibility validation against checked-in output
"""
from __future__ import annotations
import argparse
import csv
import io
import math
import pathlib
import tempfile
from html import escape
INK, SUB, GRID, TEAL, ORANGE, BLUE, MUTED = '#173039', '#465f69', '#dfe9e7', '#187f76', '#cf7655', '#546fbb', '#64777b'
WIDTH, HEIGHT = 1060, 610
PI = math.pi
def f(v):
return f'{v:.2f}'
def fmt_value(v):
return f'{v:.8g}'
def xml(s):
return escape(str(s), quote=True)
class Svg:
def __init__(self, number, title, description, footer):
self.n = number
self.raw_title = title
self.parts = [f'',''])).encode('utf-8')
class Panel:
def __init__(self, g:Svg, x,y,w,h, xmin,xmax,ymin,ymax, xlabel='',ylabel='',xticks=None,yticks=None, logy=False):
self.g,self.x,self.y,self.w,self.h,self.xmin,self.xmax = g,x,y,w,h,xmin,xmax
self.ymin,self.ymax,self.logy=ymin,ymax,logy
self.plotx,self.ploty=x+67,y+23
self.plotw,self.ploth=w-92,h-70
g.rect(x,y,w,h,'#ffffff',10,'#e4eeeb')
if logy:
if ymin<=0: raise ValueError('log y requires positive range')
self.ymin=math.log10(ymin);self.ymax=math.log10(ymax)
xticks=xticks if xticks is not None else [xmin,(xmin+xmax)/2,xmax]
yticks=yticks if yticks is not None else [ymin,(ymin+ymax)/2,ymax]
for v in yticks:
if v<=0 and logy:continue
yy=self.mapy(v)
g.line(self.plotx,yy,self.plotx+self.plotw,yy,'#e4ebe9')
g.text(self.plotx-10,yy+4,f'{v:g}',12,MUTED,anchor='end')
for v in xticks:
xx=self.mapx(v)
g.line(xx,self.ploty,xx,self.ploty+self.ploth,'#f1f4f3')
g.text(xx,self.ploty+self.ploth+20,f'{v:g}',12,MUTED,anchor='middle')
g.line(self.plotx,self.ploty,self.plotx,self.ploty+self.ploth,'#92a9aa',1.6)
g.line(self.plotx,self.ploty+self.ploth,self.plotx+self.plotw,self.ploty+self.ploth,'#92a9aa',1.6)
if xlabel:g.text(self.plotx+self.plotw/2,y+h-10,xlabel,13,SUB,anchor='middle')
if ylabel:g.text(x+7,y+20,ylabel,13,SUB)
def mapx(self,v): return self.plotx+(v-self.xmin)/(self.xmax-self.xmin)*self.plotw
def mapy(self,v):
vv=math.log10(v) if self.logy else v
return self.ploty+self.ploth-(vv-self.ymin)/(self.ymax-self.ymin)*self.ploth
def plot(self,pairs,color=TEAL,width=3,dash=None,opacity=1):
pts=' '.join(f'{f(self.mapx(x))},{f(self.mapy(y))}' for x,y in pairs)
tag=f'')
def points(self,pairs,color=ORANGE,r=4.5,open=False):
for x,y in pairs:self.g.circle(self.mapx(x),self.mapy(y),r,'#ffffff' if open else color,color if open else 'none',2)
def horizontal(self,y,color=ORANGE,dash='6 4'):
self.g.line(self.mapx(self.xmin),self.mapy(y),self.mapx(self.xmax),self.mapy(y),color,1.7,dash)
def vertical(self,x,color=ORANGE,dash='6 4'):
self.g.line(self.mapx(x),self.mapy(self.ymin if not self.logy else 10**self.ymin),self.mapx(x),self.mapy(self.ymax if not self.logy else 10**self.ymax),color,1.5,dash)
def linspace(lo,hi,n): return [lo+(hi-lo)*k/(n-1) for k in range(n)]
def legend(g:Svg,items,x=135,y=540,step=244):
for i,(label,color,dashed) in enumerate(items):
xx=x+i*step
g.line(xx,y,xx+29,y,color,3,'7 5' if dashed else None)
g.text(xx+38,y+5,label,14,SUB)
def render161():
# Figure directly demonstrates exact aliasing for cosines with phase zero at fs=1 Hz.
tt=linspace(0,10,1001)
high=[(t,math.cos(2*PI*.8*t)) for t in tt]
low=[(t,math.cos(2*PI*.2*t)) for t in tt]
sample=[(n,math.cos(2*PI*.8*n)) for n in range(11)]
g=Svg(161,'La misma muestra, dos frecuencias','Muestreo a 1 Hz: 0,8 Hz y 0,2 Hz dan lecturas idénticas.','Señales ideales sin ruido · ecuación y condición de fase de C161, sección 161.5')
p=Panel(g,55,150,950,357,0,10,-1.2,1.2,'Tiempo (s)','Amplitud relativa',xticks=[0,2,4,6,8,10],yticks=[-1,0,1])
p.plot(high,BLUE,2.7);p.plot(low,TEAL,2.7,'7 5');p.points(sample,ORANGE,5.1)
legend(g,[('Señal real: 0,8 Hz',BLUE,False),('Alternativa: 0,2 Hz',TEAL,True),('Lecturas cada 1 s',ORANGE,False)],x=120,y=532,step=295)
return g,{'t':tt,'senal_0_8':[y for _,y in high],'senal_0_2':[y for _,y in low]}
def render162():
nn=list(range(13));q0=[1/3-(1/3)*(.4**n) for n in nn];q1=[1/3+(2/3)*(.4**n) for n in nn]
g=Svg(162,'La agregación conserva la dinámica','Probabilidad del bloque B bajo dos preparaciones microscópicas compatibles.','Cadena agregable exacta de C162 · P(B→B)=0,6 y P(A→B)=0,2')
p=Panel(g,55,150,950,357,0,12,0,1.05,'Paso de la cadena','Probabilidad de B',xticks=[0,2,4,6,8,10,12],yticks=[0,.25,.5,.75,1])
p.plot(list(zip(nn,q0)),TEAL,3);p.plot(list(zip(nn,q1)),ORANGE,3);p.horizontal(1/3,BLUE,'7 6');p.points(list(zip(nn,q0)),TEAL,3);p.points(list(zip(nn,q1)),ORANGE,3)
legend(g,[('Inicio en A',TEAL,False),('Inicio en B',ORANGE,False),('Equilibrio: 1/3',BLUE,True)],x=115,y=532,step=295)
return g,{'paso':nn,'desde_A':q0,'desde_B':q1,'equilibrio':[1/3]*len(nn)}
def rg(k):return .5*math.log(math.cosh(2*k))
def render163():
ks=list(range(10));a=[.5];b=[1.]
for _ in range(9):a.append(rg(a[-1]));b.append(rg(b[-1]))
g=Svg(163,'Decimación exacta: el acoplamiento fluye','Cadena de Ising 1D, sin campo: K siguiente = ½ ln cosh(2K).','Identidad exacta del manuscrito C163 · K inicial 0,5 y 1,0 · sin datos empíricos')
p=Panel(g,55,150,950,357,0,9,0,1.05,'Número de decimaciones','Acoplamiento K',xticks=[0,1,3,5,7,9],yticks=[0,.25,.5,.75,1])
p.plot(list(zip(ks,a)),TEAL,3);p.plot(list(zip(ks,b)),ORANGE,3);p.points(list(zip(ks,a)),TEAL,3.3);p.points(list(zip(ks,b)),ORANGE,3.3)
legend(g,[('K inicial = 0,5',TEAL,False),('K inicial = 1',ORANGE,False)],x=160,y=532,step=350)
return g,{'paso':ks,'K_inicial_0_5':a,'K_inicial_1':b}
def render164():
nn=list(range(6));u=[.01*2**n for n in nn];v=[.8*2**(-n) for n in nn]
g=Svg(164,'Dos direcciones cerca del punto fijo','El acoplamiento relevante crece; el irrelevante se contrae al reescalar.','Mapa didáctico C164: u siguiente = 2u; v siguiente = v/2')
p=Panel(g,55,150,950,357,0,5,.005,1,'Iteraciones de escala n','Magnitud (escala log)',xticks=nn,yticks=[.01,.03,.1,.3,1],logy=True)
p.plot(list(zip(nn,u)),ORANGE,3);p.plot(list(zip(nn,v)),TEAL,3);p.points(list(zip(nn,u)),ORANGE,4);p.points(list(zip(nn,v)),TEAL,4)
legend(g,[('u relevante (0,01 → 0,32)',ORANGE,False),('v irrelevante (0,8 → 0,025)',TEAL,False)],x=110,y=532,step=425)
return g,{'paso':nn,'u_relevante':u,'v_irrelevante':v}
def m_ising(t):
if t>=1:return 0.
Kc=math.log(1+math.sqrt(2))/2
a=2*Kc/t
if a>700:return 1.
value=1-1/math.sinh(a)**4
return max(0,value)**(1/8)
def render165():
tt=linspace(.07,1.15,350);m=[m_ising(t) for t in tt]
g=Svg(165,'Orden espontáneo y temperatura crítica','Magnetización exacta del Ising cuadrado infinito, en la rama positiva.','Ley exacta de Yang (1952), C165 · campo externo nulo · orden termodinámico')
p=Panel(g,55,150,950,357,0,1.2,-.05,1.1,'Temperatura T / Tc','Magnetización',xticks=[0,.2,.4,.6,.8,1,1.2],yticks=[0,.25,.5,.75,1])
p.plot(list(zip(tt,m)),TEAL,3.2);p.vertical(1,ORANGE,'6 5');g.text(p.mapx(1)+10,p.mapy(.97),'Tc',14,ORANGE)
legend(g,[('m espontánea (rama +)',TEAL,False),('Umbral T / Tc = 1',ORANGE,True)],x=185,y=532,step=420)
return g,{'T_sobre_Tc':tt,'m_spontanea':m}
def render166():
# Intentionally synthetic family from C166: chi_L(t)=L^7/4/[1+(tL-1)^2].
ll=[16,32,64];colors=[TEAL,ORANGE,BLUE];xs=linspace(-2,5,141)
g=Svg(166,'El colapso de curvas está impuesto','Tres tamaños sintéticos coinciden al normalizar la susceptibilidad.','Familia didáctica de C166 · χ = L^(7/4) / [1 + (tL−1)²] · no es simulación')
p=Panel(g,55,150,950,357,-2,5,0,1.05,'Variable reescalada x = t·L','χ · L^(-7/4)',xticks=[-2,-1,0,1,2,3,4,5],yticks=[0,.25,.5,.75,1])
for l,c,step in zip(ll,colors,[7,11,15]):
values=[1/(1+(x-1)**2) for x in xs]
p.plot(list(zip(xs,values)),c,1.9)
p.points([(xs[i],values[i]) for i in range(0,len(xs),step)],c,2.9,True)
legend(g,[('L = 16',TEAL,False),('L = 32',ORANGE,False),('L = 64',BLUE,False)],x=210,y=532,step=270)
return g,{'x_tL':xs,'L16_normalizada':[1/(1+(x-1)**2) for x in xs],'L32_normalizada':[1/(1+(x-1)**2) for x in xs],'L64_normalizada':[1/(1+(x-1)**2) for x in xs]}
def render167():
# Exact spectrum of A=[[-2,1],[10,-20]]; new illustrated IC x0=1, y0=0.
slow=(-22+math.sqrt(364))/2;fast=(-22-math.sqrt(364))/2
cs=(-2-fast)/(slow-fast);cf=1-cs
tt=linspace(0,4,220);actual=[cs*math.exp(slow*t)+cf*math.exp(fast*t) for t in tt];simple=[math.exp(-1.5*t) for t in tt];corrected=[math.exp((-1.5/1.025)*t) for t in tt]
g=Svg(167,'Eliminar el estado rápido no borra su memoria','Comparación desde una preparación ilustrativa x(0)=1, y(0)=0.','Parámetros del sistema C167 · ε = 0,1; condiciones iniciales declaradas aquí')
p=Panel(g,55,150,554,357,0,4,0,1.05,'Tiempo','Estado x(t)',xticks=[0,1,2,3,4],yticks=[0,.25,.5,.75,1])
p.plot(list(zip(tt,actual)),BLUE,3.4);p.plot(list(zip(tt,simple)),ORANGE,2.5,'7 5');p.plot(list(zip(tt,corrected)),TEAL,2.5,'3 4')
q=Panel(g,622,150,384,357,0,2,-.01,.03,'Tiempo','Error vs exacta',xticks=[0,.5,1,1.5,2],yticks=[-.01,0,.01,.02,.03])
q.horizontal(0,BLUE,'2 5')
q.plot([(t,b-a) for t,a,b in zip(tt,actual,simple) if t<=2],ORANGE,2.4,'7 5')
q.plot([(t,b-a) for t,a,b in zip(tt,actual,corrected) if t<=2],TEAL,2.4,'3 4')
legend(g,[('Sistema completo',BLUE,False),('Cierre algebraico',ORANGE,True),('Cierre corregido',TEAL,True)],x=92,y=532,step=295)
return g,{'tiempo':tt,'x_completo':actual,'x_cierre_algebraico':simple,'x_cierre_corregido':corrected}
def render168():
xx=linspace(0,1,201)
hetero=[1-1.8*x if x<=.5 else .2*(1-x) for x in xx]
homog=[1-x for x in xx]
g=Svg(168,'Capas en serie: el gradiente cambia','D₁ = 1, D₂ = 9, espesores iguales; el flujo permanece constante.','Caso analítico C168 · D efectivo en serie = 1,8; referencia homogénea')
p=Panel(g,55,150,950,357,0,1,0,1.05,'Posición / longitud total','Concentración',xticks=[0,.25,.5,.75,1],yticks=[0,.25,.5,.75,1])
# Layers: unobtrusive drawing below curves (transparent via opacity)
g.rect(p.mapx(0),p.ploty,p.plotw/2,p.ploth,'#edf7f5')
g.rect(p.mapx(.5),p.ploty,p.plotw/2,p.ploth,'#fff2eb')
# Re-grid as layer backgrounds are above initial grids
for value in [0,.25,.5,.75,1]:g.line(p.mapx(0),p.mapy(value),p.mapx(1),p.mapy(value),'#e1e8e6',.8)
p.plot(list(zip(xx,hetero)),TEAL,3.5);p.plot(list(zip(xx,homog)),ORANGE,2.3,'7 6');p.vertical(.5,BLUE,'4 5')
g.text(p.mapx(.18),p.ploty+27,'Capa D₁ = 1',14,SUB,anchor='middle')
g.text(p.mapx(.78),p.ploty+27,'Capa D₂ = 9',14,SUB,anchor='middle')
legend(g,[('Perfil en capas (flujo 1,8)',TEAL,False),('Perfil homogéneo',ORANGE,True)],x=180,y=532,step=450)
return g,{'x':xx,'concentracion_serie':hetero,'referencia_homogenea':homog}
def render169():
nn=list(range(1,301));ind=[4/n for n in nn];corr=[4*(.1+.9/n) for n in nn]
g=Svg(169,'Una fluctuación común resiste al promedio','La correlación ρ = 0,1 mantiene una varianza colectiva positiva.','Identidad exacta C169 · varianza individual σ² = 4; N de 1 a 300')
p=Panel(g,55,150,950,357,1,300,.008,5,'Número de unidades N','Varianza de la media (log)',xticks=[1,50,100,150,200,250,300],yticks=[.01,.04,.1,.4,1,4],logy=True)
p.plot(list(zip(nn,ind)),TEAL,3);p.plot(list(zip(nn,corr)),ORANGE,3);p.horizontal(.4,BLUE,'6 4')
g.circle(p.mapx(100),p.mapy(4/100),5,TEAL);g.circle(p.mapx(100),p.mapy(4*(.1+.9/100)),5,ORANGE)
legend(g,[('ρ = 0: varianza 4/N',TEAL,False),('ρ = 0,1: suelo 0,4',ORANGE,False)],x=155,y=532,step=435)
return g,{'N':nn,'varianza_independencia':ind,'varianza_rho_0_1':corr}
def render170():
tt=linspace(0,60,241)
initial=[20+40*math.exp(-.1*t) for t in tt]
new=[100/3-40/3*math.exp(-.12*t) for t in tt]
g=Svg(170,'Dos experimentos con la misma población','N = 100: relajación desde 60 activos e intervención desde equilibrio.','C170 · k+ original 0,02; intervenido 0,04; k− = 0,08 (s⁻¹)')
p=Panel(g,55,150,950,357,0,60,0,65,'Tiempo (s)','Activos esperados E[n]',xticks=[0,10,20,30,40,50,60],yticks=[0,20,40,60])
p.plot(list(zip(tt,initial)),TEAL,3);p.plot(list(zip(tt,new)),ORANGE,3);p.horizontal(20,BLUE,'6 5');p.horizontal(100/3,ORANGE,'4 6')
legend(g,[('Desde n(0) = 60 (sin intervenir)',TEAL,False),('Intervención desde E[n(0)] = 20',ORANGE,False)],x=104,y=532,step=445)
return g,{'tiempo_s':tt,'relajacion_desde_60':initial,'intervencion_desde_20':new}
RENDERS={161:render161,162:render162,163:render163,164:render164,165:render165,166:render166,167:render167,168:render168,169:render169,170:render170}
def build(out):
figures=out/'figures';data=out/'repro'/'c161-170'
figures.mkdir(parents=True,exist_ok=True);data.mkdir(parents=True,exist_ok=True)
for n,gen in RENDERS.items():
drawing,table=gen()
fields=list(table)
widths={len(v) for v in table.values()}
assert len(widths)==1 and next(iter(widths))>0
figure=figures/f'complexa-c{n}-fig01.svg'
figure.write_bytes(drawing.output())
buf=io.StringIO(newline='');writer=csv.writer(buf,lineterminator='\n')
writer.writerow(fields)
for row in zip(*table.values()):writer.writerow([fmt_value(v) for v in row])
(data/f'c{n}.csv').write_text(buf.getvalue(),encoding='utf-8')
# Control calculations repeated independently of graphics.
assert abs(math.cos(2*PI*.8*5)-math.cos(2*PI*.2*5))<1e-12
assert abs(render162()[1]['desde_A'][1]-.2)<1e-12
assert abs(rg(.5)-.2168904)<1e-6
assert abs(render164()[1]['u_relevante'][-1]-.32)<1e-12
assert m_ising(1)==0
assert abs(render166()[1]['L16_normalizada'][60]-render166()[1]['L64_normalizada'][60])<1e-12
assert abs((-22+math.sqrt(364))/2-(-1.46060799))<1e-7
assert abs(render168()[1]['concentracion_serie'][100]-.1)<1e-12
assert abs(4*(.1+.9/100)-.436)<1e-12
assert abs(20+40*math.exp(-1)-34.7151776)<1e-6
print('PASS: 10 SVG and 10 numerical CSV files; 10 independent analytic checks')
def main():
p=argparse.ArgumentParser(description=__doc__)
ex=p.add_mutually_exclusive_group(required=True)
ex.add_argument('--out',type=pathlib.Path)
ex.add_argument('--check',type=pathlib.Path)
args=p.parse_args()
if args.out:
build(args.out)
else:
with tempfile.TemporaryDirectory() as tmp:
generated=pathlib.Path(tmp)
build(generated)
for sub in ['figures','repro/c161-170']:
for file in (generated/sub).iterdir():
target=args.check/sub/file.name
assert target.exists(),f'Missing tracked figure/data: {target}'
assert file.read_bytes()==target.read_bytes(),f'Non-reproducible figure/data: {target}'
print('PASS: byte-for-byte scientific graphics and CSV regeneration')
if __name__=='__main__':main()