Add a few vars, and support for rendering single flames

cuburn/code/iter.py

@@ -37,7 +37,7 @@ texture<uchar4, cudaTextureType2D, cudaReadModeNormalizedFloat> palTex;
         tmpl = tempita.Template("""
 __device__
 void apply_xf{{xfid}}(float *ix, float *iy, float *icolor,
-                      const iter_info *info) {
+                      const iter_info *info, mwc_st *rctx) {
     float tx, ty, ox = *ix, oy = *iy;
     {{apply_affine('ox', 'oy', 'tx', 'ty', px, 'xf.c', 'pre')}}
 
@@ -47,7 +47,7 @@ void apply_xf{{xfid}}(float *ix, float *iy, float *icolor,
     {{for v in xform.vars}}
     if (1) {
         float w = {{px.get('xf.var[%d]' % v)}};
-        {{variations.var_code[variations.var_nos[v]]()}}
+        {{variations.var_code[variations.var_nos[v]].substitute(locals())}}
     }
     {{endfor}}
 
@@ -82,7 +82,7 @@ void iter(mwc_st *msts, iter_info *infos, float *accbuf, float *denbuf) {
 
         {{for xfid, xform in enumerate(features.xforms)}}
         if (xfsel <= {{packer.get('cp.norm_density[%d]' % xfid)}}) {
-            apply_xf{{xfid}}(&x, &y, &color, info);
+            apply_xf{{xfid}}(&x, &y, &color, info, &rctx);
         } else
         {{endfor}}
         {
@@ -97,7 +97,7 @@ void iter(mwc_st *msts, iter_info *infos, float *accbuf, float *denbuf) {
 
         nsamps--;
 
-        if (x <= -1.0f || x >= 1.0f || y <= -1.0f || y >= 1.0f) {
+        if (x <= -0.5f || x >= 0.5f || y <= -0.5f || y >= 0.5f) {
             consec_bad++;
             if (consec_bad > {{features.max_oob}}) {
                 x = mwc_next_11(&rctx);
@@ -109,8 +109,8 @@ void iter(mwc_st *msts, iter_info *infos, float *accbuf, float *denbuf) {
         }
 
         // TODO: dither?
-        int i = ((int)((y + 1.0f) * 511.0f) * 1024)
+        int i = ((int)((y + 0.5f) * 1023.0f) * 1024)
-              +  (int)((x + 1.0f) * 511.0f) + 1025;
+              +  (int)((x + 0.5f) * 1023.0f) + 1025;
 
         // since info was declared const, C++ barfs unless it's loaded first
         float cp_step_frac = {{packer.get('cp_step_frac')}};
@@ -129,7 +129,7 @@ void iter(mwc_st *msts, iter_info *infos, float *accbuf, float *denbuf) {
 
 
 def silly(features, cps):
-    nsteps = 1000
+    nsteps = 500
     abuf = np.zeros((1024, 1024, 4), dtype=np.float32)
     dbuf = np.zeros((1024, 1024), dtype=np.float32)
     seeds = mwc.MWC.make_seeds(512 * nsteps)
@@ -139,28 +139,37 @@ def silly(features, cps):
 
     for lno, line in enumerate(code.split('\n')):
         print '%3d %s' % (lno, line)
-    mod = SourceModule(code, options=[], keep=True)
+    mod = SourceModule(code, options=['--use_fast_math'], keep=True)
 
     cps_as_array = (Genome * len(cps))()
     for i, cp in enumerate(cps):
         cps_as_array[i] = cp
 
-    cp = Genome()
-    memset(byref(cp), 0, sizeof(cp))
     infos = []
+    pal = np.empty((16, 256, 4), dtype=np.uint8)
 
     # TODO: move this into a common function
-    pal = np.empty((16, 256, 4), dtype=np.uint8)
+    if len(cps) > 1:
-    sampAt = [int(i/15.*(nsteps-1)) for i in range(16)]
+        cp = Genome()
+        memset(byref(cp), 0, sizeof(cp))
 
+        sampAt = [int(i/15.*(nsteps-1)) for i in range(16)]
         for n in range(nsteps):
-        flam3_interpolate(cps_as_array, 2, float(n)/nsteps - 0.5, 0, byref(cp))
+            flam3_interpolate(cps_as_array, 2, float(n)/nsteps - 0.5,
+                              0, byref(cp))
             cp._init()
             if n in sampAt:
                 pidx = sampAt.index(n)
                 for i, e in enumerate(cp.palette.entries):
                     pal[pidx][i] = np.uint8(np.array(e.color) * 255.0)
             infos.append(iter.packer.pack(cp=cp, cp_step_frac=float(n)/nsteps))
+    else:
+        for i, e in enumerate(cps[0].palette.entries):
+            pal[0][i] = np.uint8(np.array(e.color) * 255.0)
+        pal[1:] = pal[0]
+        infos.append(iter.packer.pack(cp=cps[0], cp_step_frac=0))
+        infos *= nsteps
+
     infos = np.concatenate(infos)
 
     dpal = cuda.make_multichannel_2d_array(pal, 'C')

cuburn/code/variations.py

@@ -1,40 +1,58 @@
+import tempita
 
 var_nos = {}
 var_code = {}
 
-def _var(num, name = None):
+def var(num, name, code):
-    def _var1(func):
+    var_nos[num] = name
-        if name:
+    var_code[name] = tempita.Template(code)
-            namelo = name
-        else:
-            namelo = func.__name__
-        var_nos[num] = namelo
-        var_code[namelo] = func
-    return _var1
 
 # Variables note: all functions will have their weights as 'w',
 # input variables 'tx' and 'ty', and output 'ox' and 'oy' available
 # from the calling context. Each statement will be placed inside brackets,
 # to avoid namespace pollution.
-@_var(0)
+var(0, 'linear', """
-def linear():
-    return """
     ox += tx * w;
     oy += ty * w;
-    """
+    """)
 
-@_var(1)
+var(1, 'sinusoidal', """
-def sinusoidal():
+    ox += w * sinf(tx);
-    return """
+    oy += w * sinf(ty);
-    ox += w * sin(tx);
+    """)
-    oy += w * sin(ty);
-    """
 
-@_var(2)
+var(2, 'spherical', """
-def spherical():
-    return """
     float r2 = w / (tx*tx + ty*ty + 1e-20);
     ox += tx * r2;
     oy += ty * r2;
-    """
+    """)
+
+var(5, 'polar', """
+    ox += w * atan2f(tx, ty) * M_1_PI;
+    oy += w * (sqrtf(tx * tx + ty * ty) - 1.0);
+    """)
+
+
+var(10, 'hyperbolic', """
+    float a = atan2f(tx, ty);
+    float r = sqrt(tx*tx + ty*ty) + 1e-20;
+    ox += w * sinf(a) / r;
+    oy += w * cosf(a) * r;
+    """)
+
+var(33, 'juliascope', """
+    float ang = atan2f(ty, tx);
+    float power = {{px.get('xf.juliascope_power', 'juscope_power')}};
+    float t_rnd = truncf(mwc_next_01(rctx) * fabsf(power));
+    // TODO: don't draw the extra random number
+    if (mwc_next(rctx) & 1) ang = -ang;
+    float tmpr = (2 * M_PI * t_rnd + ang) / power;
+
+    float cn = {{px.get('xf.juliascope_dist / xf.juliascope_power / 2',
+                         'juscope_cn')}};
+    float r = w * powf(tx * tx + ty * ty, cn);
+
+    ox += r * cosf(tmpr);
+    oy += r * sinf(tmpr);
+    """)
 

main.py

@@ -32,21 +32,18 @@ from cuburn.code.iter import silly, membench
 
 
 def main(args):
-    membench()
-    return
-
     #MWCTest.test_mwc()
     with open(args[-1]) as fp:
         genomes = Genome.from_string(fp.read())
     anim = Animation(genomes)
     accum, den = silly(anim.features, genomes)
 
-    if '-g' not in args:
-        return
-
     noalpha = np.delete(accum, 3, axis=2)
     scipy.misc.imsave('rendered.png', noalpha)
 
+    if '-g' not in args:
+        return
+
     imgbuf = (np.minimum(accum * 255, 255)).astype(np.uint8)
 
     image = pyglet.image.ImageData(1024, 1024, 'RGBA', imgbuf.tostring(), -4096)