Collect paired moving-pinball Fig2 research material

research/fig2_collection/plot.py

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+"""Shared scientific plots of retained fields; no solver or synthetic fields."""
+import argparse
+import json
+from pathlib import Path
+import sys
+
+import numpy as np
+import matplotlib
+matplotlib.use('Agg')
+import matplotlib.pyplot as plt
+from matplotlib.colors import BoundaryNorm
+from matplotlib.patches import Circle,Rectangle
+
+ROOT=Path(__file__).resolve().parents[2]
+sys.path.insert(0,str(ROOT))
+from research.continuous_viv.render import vorticity
+
+
+def decorate(ax,scene,role,y,*,mean=False):
+    if not mean:
+        if scene=='karman':ax.add_patch(Circle((-20,0),1,facecolor='white',edgecolor='#253544',lw=.7))
+        if role!='target':
+            for x,dy in ((0,0),(1.3,.75),(1.3,-.75)):
+                ax.add_patch(Circle((x,dy+y),.5,facecolor='white',edgecolor='#253544',lw=.7))
+    ax.add_patch(Rectangle((4,-5),20,10,fill=False,ls='--',lw=.6,edgecolor='#555'))
+    ax.set_xlim(-23.6,27.6);ax.set_ylim(-6.4,6.4)
+    ax.set_xlabel('(x - pinball-front equilibrium centre) / D',fontsize=8)
+    ax.set_ylabel('(y - channel centre) / D',fontsize=8)
+    ax.tick_params(labelsize=8)
+
+
+def main():
+    ap=argparse.ArgumentParser(description=__doc__);ap.add_argument('directory',type=Path)
+    args=ap.parse_args();p=args.directory
+    case=json.loads((p/'case.json').read_text());scene=case['scene']
+    cmap=plt.get_cmap('RdBu_r',21).copy();cmap.set_bad('#DDE2E5')
+    norm=BoundaryNorm(np.linspace(-3,3,22),21,clip=True)
+    prefix='SMOKE — plumbing only | ' if case['plan']['smoke'] else ''
+    roles=('target','zero','controlled')
+    data={};motion={}
+    for role in roles:
+        with np.load(p/role/'fields.npz') as z:data[role]={k:z[k] for k in z.files}
+        with np.load(p/role/'native.npz') as z:
+            motion[role]=z['rows'][:,1].copy()/40.
+    shape=data['target']['ux'].shape[-2:]
+    extent=((-0.5-1200)/40,(shape[1]-.5-1200)/40,
+            (-.5-510.5)/40,(shape[0]-.5-510.5)/40)
+    fig,axs=plt.subplots(3,1,figsize=(13,10),constrained_layout=True)
+    for ax,role in zip(axs,roles):
+        d=data[role];flags=d['common_fluid_all_boundaries'].astype(np.uint16)
+        w=vorticity(d['fixed_window_mean_ux'],d['fixed_window_mean_uy'],flags)
+        image=ax.imshow(w,origin='lower',extent=extent,cmap=cmap,norm=norm,interpolation='nearest')
+        decorate(ax,scene,role,0,mean=True)
+        label='no pinball reference' if role=='target' else ('zero rotation' if role=='zero' else ('constant rotations' if scene=='steady' else 'frozen PPO'))
+        ax.set_title(f'{role}: {label} | arithmetic fixed-window mean',fontsize=10)
+    fig.suptitle(prefix+f'{scene}: modern Re_D=50, m*=4, zero structural damping\n'
+                 'Gray: cells outside the common fluid support; mean fields are not instantaneous geometry',fontsize=12)
+    fig.colorbar(image,ax=list(axs),shrink=.65,label='vorticity D/U, fixed limits [-3,3]')
+    fig.savefig(p/'mean-flow.png',dpi=160);plt.close(fig)
+    slots=max(len(data[r]['ux']) for r in roles)
+    fig,axs=plt.subplots(3,slots,figsize=(max(8,3*slots),7),squeeze=False,constrained_layout=True)
+    for row,role in enumerate(roles):
+        d=data[role]
+        for col,ax in enumerate(axs[row]):
+            if col>=len(d['ux']):ax.axis('off');continue
+            w=vorticity(d['ux'][col],d['uy'][col],d['flags'][col])
+            image=ax.imshow(w,origin='lower',extent=extent,cmap=cmap,norm=norm,interpolation='nearest')
+            step=int(d['selected_response_steps'][col]);y=float(motion[role][step-1])
+            decorate(ax,scene,role,y)
+            ax.set_xlim(-3,14);ax.set_ylim(-3,3)
+            ax.set_xlabel('x/D relative to equilibrium front',fontsize=7)
+            ax.set_title(f'{role} | slot {col+1}\ntU/D={step*.005/40:.2f}',fontsize=8)
+    family={'karman':'independently phased diagnostic snapshots (different real times)',
+            'steady':'late snapshots at matching real times',
+            'taylor':'common event-relative snapshots at matching real times'}[scene]
+    fig.suptitle(prefix+f'{scene}: {family}\nFixed lab coordinates; same vorticity normalization/limits; source '+case['source'][:8],fontsize=12)
+    fig.colorbar(image,ax=list(axs.ravel()),shrink=.7,label='vorticity D/U [-3,3]')
+    fig.savefig(p/'selected-flow.png',dpi=160);plt.close(fig)
+    fig,ax=plt.subplots(figsize=(11,3.5),constrained_layout=True)
+    for role,color in (('zero','#5A6570'),('controlled','#147D73')):
+        y=motion[role];stride=max(1,len(y)//12000)
+        time=(np.arange(len(y))+1)*.005/40
+        ax.plot(time[::stride],y[::stride],lw=.8,label=role,color=color)
+    ax.set(xlabel='response time tU/D',ylabel='transverse y/D',ylim=(-1,1))
+    ax.legend();ax.grid(alpha=.2)
+    ax.set_title(prefix+scene+': independent paired releases; full retained duration')
+    fig.savefig(p/'motion.png',dpi=160);plt.close(fig)
+    print(json.dumps(dict(scene=scene,plots=['mean-flow.png','selected-flow.png','motion.png'],
+                          vorticity_limits=[-3,3],normalization='curl(u) D/U; five-node fluid stencil',
+                          mean_mask='intersection over collected boundary fields',display_interpolation='nearest')))
+
+
+if __name__=='__main__':main()