diff --git a/src/callback.c b/src/callback.c
index 8a0028e4..aae76825 100644
--- a/src/callback.c
+++ b/src/callback.c
@@ -320,7 +320,7 @@ static int waves_callback(int event, int mx, int my, KeySym key, int button, int
       if(xctx->graph_flags & 64) {
         if( POINTINSIDE(xctx->mousex, xctx->mousey, gr->x1, gr->y1, gr->x2, gr->y2)) {
           char sx[100], sy[100];
-          double yval;
+          double xval, yval;
           if(gr->digital) { 
             double deltag = gr->gy2 - gr->gy1;
             double s1 = DIG_NWAVES; /* 1/DIG_NWAVES  waveforms fit in graph if unscaled vertically */
@@ -333,8 +333,18 @@ static int waves_callback(int event, int mx, int my, KeySym key, int button, int
           } else {
             yval = G_Y(xctx->mousey);
           }
-          my_snprintf(sx, S(sx), "%.4g", G_X(xctx->mousex));
-          my_snprintf(sy, S(sy), "%.4g", yval);
+
+          xval = G_X(xctx->mousex);
+          if(xctx->graph_sim_type == 3) xval = pow(10, xval);
+          if(gr->unitx != 0) 
+            my_snprintf(sx, S(sx), "%.4g%c", gr->unitx * xval, gr->unitx_suffix);
+          else
+            my_snprintf(sx, S(sx), "%.4g", xval);
+
+          if(gr->unitx != 0)
+            my_snprintf(sy, S(sy), "%.4g%c", gr->unity * yval, gr->unity_suffix);
+          else
+            my_snprintf(sy, S(sy), "%.4g", yval);
   
           tclvareval("set measure_text \"y=", sy, "\nx=", sx, "\"", NULL);
           tcleval("graph_show_measure");
diff --git a/src/draw.c b/src/draw.c
index 14317052..762c46fa 100644
--- a/src/draw.c
+++ b/src/draw.c
@@ -1528,7 +1528,7 @@ void drawtemprect(GC gc, int what, double rectx1,double recty1,double rectx2,dou
  *                  112   --> 100
  *                  6300  --> 10000
  */
-static double axis_increment(double a, double b, int div)
+static double axis_increment(double a, double b, int div, int freq)
 {
   double scale;
   double sign;
@@ -1545,10 +1545,16 @@ static double axis_increment(double a, double b, int div)
   delta = fabs(delta);
   scale = pow(10.0, floor(log10(delta)));
   scaled_delta =  delta / scale; /* 1 <= scaled_delta < 10 */
-  if(scaled_delta > 5.5) scaled_delta = 10.0;
+  dbg(1, "a=%g, b=%g, scale=%g, scaled_delta=%g --> ", a, b, scale, scaled_delta);
+  if(freq && scaled_delta > 2.5) scaled_delta = 10.0;
+  else if(freq && scaled_delta > 1.9) scaled_delta = 5.0;
+  else if(freq && scaled_delta > 1.4) scaled_delta = 2.0;
+  else if(freq) scaled_delta = 1.0;
+  else if(scaled_delta > 5.5) scaled_delta = 10.0;
   else if(scaled_delta > 2.2) scaled_delta = 5.0;
   else if(scaled_delta > 1.1) scaled_delta = 2.0;
   else scaled_delta = 1.0;
+  dbg(1, "scaled_delta = %g, scaled_delta * scale * sign=%g\n", scaled_delta, scaled_delta * scale * sign);
   return scaled_delta * scale * sign;
 }
 
@@ -1810,12 +1816,16 @@ static void draw_graph_grid(Graph_ctx *gr)
   bbox(ADD, gr->rx1, gr->ry1, gr->rx2, gr->ry2);
   bbox(SET_INSIDE, 0.0, 0.0, 0.0, 0.0);
   /* vertical grid lines */
-  deltax = axis_increment(gr->gx1, gr->gx2, gr->divx);
+  deltax = axis_increment(gr->gx1, gr->gx2, gr->divx, (xctx->graph_sim_type == 3));
   startx = axis_start(gr->gx1, deltax, gr->divx);
   for(j = -1;; j++) { /* start one interval before to allow sub grids at beginning */
     wx = startx + j * deltax;
     if(gr->subdivx > 0) for(k = 1; k <=gr->subdivx; k++) {
-      double subwx = wx + k * deltax / (gr->subdivx + 1);
+      double subwx;
+      if(xctx->graph_sim_type == 3)  {
+        subwx = wx + deltax * log10(1.0 + (double)k * 9.0 / ((double)gr->subdivx + 1.0)); 
+      } else
+        subwx = wx + deltax * (double)k / ((double)gr->subdivx + 1.0);
       if(!axis_within_range(subwx, gr->gx1, gr->gx2)) continue;
       if(axis_end(subwx, deltax, gr->gx2)) break;
       drawline(GRIDLAYER, ADD, W_X(subwx),   W_Y(gr->gy2), W_X(subwx),   W_Y(gr->gy1), dash_sizey);
@@ -1826,7 +1836,11 @@ static void draw_graph_grid(Graph_ctx *gr)
     drawline(GRIDLAYER, ADD, W_X(wx),   W_Y(gr->gy2), W_X(wx),   W_Y(gr->gy1), dash_sizey);
     drawline(GRIDLAYER, ADD, W_X(wx),   W_Y(gr->gy1), W_X(wx),   W_Y(gr->gy1) + mark_size, 0); /* axis marks */
     /* X-axis labels */
-    draw_string(3, NOW, dtoa(wx * gr->unitx), 0, 0, 1, 0, W_X(wx), gr->y2 + mark_size + 5 * gr->txtsizex,
+    if(xctx->graph_sim_type == 3) 
+      draw_string(3, NOW, dtoa(pow(10, wx ) * gr->unitx), 0, 0, 1, 0, W_X(wx), gr->y2 + mark_size + 5 * gr->txtsizex,
+                gr->txtsizex, gr->txtsizex);
+    else
+      draw_string(3, NOW, dtoa(wx * gr->unitx), 0, 0, 1, 0, W_X(wx), gr->y2 + mark_size + 5 * gr->txtsizex,
                 gr->txtsizex, gr->txtsizex);
   }
   /* first and last vertical box delimiters */
@@ -1834,7 +1848,7 @@ static void draw_graph_grid(Graph_ctx *gr)
   drawline(GRIDLAYER, ADD, W_X(gr->gx2),   W_Y(gr->gy2), W_X(gr->gx2),   W_Y(gr->gy1), 0);
   /* horizontal grid lines */
   if(!gr->digital) {
-    deltay = axis_increment(gr->gy1, gr->gy2, gr->divy);
+    deltay = axis_increment(gr->gy1, gr->gy2, gr->divy, 0);
     starty = axis_start(gr->gy1, deltay, gr->divy);
     for(j = -1;; j++) { /* start one interval before to allow sub grids at beginning */
       wy = starty + j * deltay;
@@ -1922,8 +1936,13 @@ void setup_graph_data(int i, const int flags, int skip, Graph_ctx *gr)
   gr->unitx_suffix = val[0];
   gr->unitx = get_unit(val);
   val = get_tok_value(r->prop_ptr,"unity",0);
-  gr->unity_suffix = val[0];
-  gr->unity = get_unit(val);
+  if(xctx->graph_sim_type == 3) { /* AC */
+    gr->unity_suffix = '1';
+    gr->unity = 1.0;
+  } else {
+    gr->unity_suffix = val[0];
+    gr->unity = get_unit(val);
+  }
   val = get_tok_value(r->prop_ptr,"subdivx",0);
   if(val[0]) gr->subdivx = atoi(val);
   val = get_tok_value(r->prop_ptr,"subdivy",0);
@@ -2020,6 +2039,7 @@ static void draw_cursor(double active_cursorx, double other_cursorx, int cursor_
 
   if(xx >= gr->x1 && xx <= gr->x2) {
     drawline(cursor_color, NOW, xx, gr->ry1, xx, gr->ry2, 1);
+    if(xctx->graph_sim_type == 3) active_cursorx = pow(10, active_cursorx);
     if(gr->unitx != 1.0)
        my_snprintf(tmpstr, S(tmpstr), "%.4g%c", gr->unitx * active_cursorx , gr->unitx_suffix);
     else
@@ -2046,6 +2066,7 @@ static void draw_cursor_difference(Graph_ctx *gr)
   double yy = gr->ry2 - 1;
   double tmpd;
   double yline;
+  if(xctx->graph_sim_type == 3) return;
   if(gr->unitx != 1.0)
      my_snprintf(tmpstr, S(tmpstr), "%.4g%c", gr->unitx * diffw , gr->unitx_suffix);
   else
@@ -2085,7 +2106,13 @@ static void draw_graph_variables(int wcnt, int wave_color, int n_nodes, int swee
     if(gr->unity != 1.0) my_snprintf(tmpstr, S(tmpstr), "%s[%c]", find_nth(ntok, ',', 1), gr->unity_suffix);
     else  my_snprintf(tmpstr, S(tmpstr), "%s",find_nth(ntok, ',', 1));
   } else {
-    if(gr->unity != 1.0) my_snprintf(tmpstr, S(tmpstr), "%s[%c]", ntok, gr->unity_suffix);
+    if(xctx->graph_sim_type == 3) {
+      if(strstr(ntok, "ph(") == ntok)
+        my_snprintf(tmpstr, S(tmpstr), "%s[Phase]", ntok);
+      else
+        my_snprintf(tmpstr, S(tmpstr), "%s[dB]", ntok);
+    }
+    else if(gr->unity != 1.0) my_snprintf(tmpstr, S(tmpstr), "%s[%c]", ntok, gr->unity_suffix);
     else  my_snprintf(tmpstr, S(tmpstr), "%s", ntok);
   }
   if(gr->digital) {
diff --git a/src/save.c b/src/save.c
index 54a24339..8e7e8254 100644
--- a/src/save.c
+++ b/src/save.c
@@ -222,16 +222,15 @@ unsigned char *base64_decode(const char *data, const size_t input_length, size_t
  * data layout in memory arranged to maximize cache locality 
  * when looking up data 
  */
-static void read_binary_block(FILE *fd, int sim_type)
+static void read_binary_block(FILE *fd)
 {
   int p, v;
   double *tmp;
   size_t size = 0;
   int offset = 0;
-  int m = 0;
-  double val;
+  int ac = 0;
 
-  if(sim_type == 3) m = 1; /* AC analysis, complex numbers twice the size */
+  if(xctx->graph_sim_type == 3) ac = 1; /* AC analysis, complex numbers twice the size */
 
   for(p = 0 ; p < xctx->graph_datasets; p++) {
     size += xctx->graph_nvars * xctx->graph_npoints[p];
@@ -239,7 +238,7 @@ static void read_binary_block(FILE *fd, int sim_type)
   }
 
   /* read buffer */
-  tmp = my_calloc(1405, xctx->graph_nvars, (sizeof(double *) << m));
+  tmp = my_calloc(1405, xctx->graph_nvars, (sizeof(double *) ));
   /* allocate storage for binary block */
   if(!xctx->graph_values) xctx->graph_values = my_calloc(118, xctx->graph_nvars, sizeof(SPICE_DATA *));
   for(p = 0 ; p < xctx->graph_nvars; p++) {
@@ -248,13 +247,19 @@ static void read_binary_block(FILE *fd, int sim_type)
   }
   /* read binary block */
   for(p = 0; p < xctx->graph_npoints[xctx->graph_datasets]; p++) {
-    if(fread(tmp, (sizeof(double) << m), xctx->graph_nvars, fd) != xctx->graph_nvars) {
+    if(fread(tmp, sizeof(double) , xctx->graph_nvars, fd) != xctx->graph_nvars) {
        dbg(0, "Warning: binary block is not of correct size\n");
     }
     /* assign to xschem struct, memory aligned per variable, for cache locality */
-    if(m) for(v = 0; v < xctx->graph_nvars; v++) { /*AC analysis: calculate magnitude */
-      xctx->graph_values[v][offset + p] = 
-         sqrt( tmp[v << m] * tmp[v << m] + tmp[(v << m) + 1] * tmp[(v << m) + 1]);
+    if(ac) {
+      for(v = 0; v < xctx->graph_nvars; v += 2) { /*AC analysis: calculate magnitude */
+        if( v == 0 ) 
+          xctx->graph_values[v][offset + p] = log10(sqrt( tmp[v] * tmp[v] + tmp[v + 1] * tmp[v + 1]));
+        else
+          xctx->graph_values[v][offset + p] = 20 * log10(sqrt(tmp[v] * tmp[v] + tmp[v + 1] * tmp[v + 1]));
+
+        xctx->graph_values[v + 1] [offset + p] = atan2(tmp[v + 1], tmp[v]) * 180.0 / XSCH_PI;
+      }
     } 
     else for(v = 0; v < xctx->graph_nvars; v++) {
       xctx->graph_values[v][offset + p] = tmp[v];
@@ -291,16 +296,17 @@ static int read_dataset(FILE *fd)
   int variables = 0, i, done_points = 0;
   char line[PATH_MAX], varname[PATH_MAX];
   char *ptr;
-  int sim_type = 0; /* 1: transient, 2: dc, 4: ... */
   int done_header = 0;
   int exit_status = 0;
+  xctx->graph_sim_type = 0;
+  
   while((ptr = fgets(line, sizeof(line), fd)) ) {
     /* after this line comes the binary blob made of nvars * npoints * sizeof(double) bytes */
     if(!strcmp(line, "Binary:\n")) {
       int npoints = xctx->graph_npoints[xctx->graph_datasets];
-      if(sim_type) {
+      if(xctx->graph_sim_type) {
         done_header = 1;
-        read_binary_block(fd, sim_type); 
+        read_binary_block(fd); 
         dbg(1, "read_dataset(): read binary block, nvars=%d npoints=%d\n", xctx->graph_nvars, npoints);
         xctx->graph_datasets++;
         exit_status = 1;
@@ -311,19 +317,19 @@ static int read_dataset(FILE *fd)
       done_points = 0;
     }
     else if(!strncmp(line, "Plotname: Transient Analysis", 28)) {
-      if(sim_type && sim_type != 1) sim_type = 0;
-      else sim_type = 1;
+      if(xctx->graph_sim_type && xctx->graph_sim_type != 1) xctx->graph_sim_type = 0;
+      else xctx->graph_sim_type = 1;
     }
     else if(!strncmp(line, "Plotname: DC transfer characteristic", 36)) {
-      if(sim_type && sim_type != 2) sim_type = 0;
-      else sim_type = 2;
+      if(xctx->graph_sim_type && xctx->graph_sim_type != 2) xctx->graph_sim_type = 0;
+      else xctx->graph_sim_type = 2;
     }
     else if(!strncmp(line, "Plotname: AC Analysis", 21)) {
-      if(sim_type && sim_type != 3) sim_type = 0;
-      else sim_type = 3;
+      if(xctx->graph_sim_type && xctx->graph_sim_type != 3) xctx->graph_sim_type = 0;
+      else xctx->graph_sim_type = 3;
     }
     else if(!strncmp(line, "Plotname:", 9)) {
-      sim_type = 0;
+      xctx->graph_sim_type = 0;
     }
     /* points and vars are needed for all sections (also ones we are not interested in)
      * to skip binary blobs */
@@ -335,6 +341,7 @@ static int read_dataset(FILE *fd)
     }
     else if(!strncmp(line, "No. Variables:", 14)) {
       sscanf(line, "No. Variables: %d", &xctx->graph_nvars);
+      if(xctx->graph_sim_type == 3) xctx->graph_nvars <<= 1; /* mag and phase */
     }
     else if(!done_points && !strncmp(line, "No. Points:", 11)) {
       my_realloc(1415, &xctx->graph_npoints, (xctx->graph_datasets+1) * sizeof(int));
@@ -344,14 +351,24 @@ static int read_dataset(FILE *fd)
       /* get the list of lines with index and node name */
       if(!xctx->graph_names) xctx->graph_names = my_calloc(426, xctx->graph_nvars, sizeof(char *));
       sscanf(line, "%d %s", &i, varname); /* read index and name of saved waveform */
-      xctx->graph_names[i] = my_malloc(415, strlen(varname) + 1);
-      strcpy(xctx->graph_names[i], varname);
+      if(xctx->graph_sim_type == 3) { /* AC */
+        my_strcat(414, &xctx->graph_names[i << 1], varname);
+        int_hash_lookup(xctx->raw_table, xctx->graph_names[i << 1], (i << 1), XINSERT_NOREPLACE);
+        if(strstr(varname, "v(") == varname || strstr(varname, "i(") == varname ||
+           strstr(varname, "V(") == varname || strstr(varname, "I(") == varname)
+          my_mstrcat(540, &xctx->graph_names[(i << 1) + 1], "ph(", varname + 2, NULL);
+        else
+          my_mstrcat(540, &xctx->graph_names[(i << 1) + 1], varname, "_ph", NULL);
+        int_hash_lookup(xctx->raw_table, xctx->graph_names[(i << 1) + 1], (i << 1) + 1, XINSERT_NOREPLACE);
+      } else {
+        my_strcat(541, &xctx->graph_names[i], varname);
+        int_hash_lookup(xctx->raw_table, xctx->graph_names[i], i, XINSERT_NOREPLACE);
+      }
       /* use hash table to store index number of variables */
-      int_hash_lookup(xctx->raw_table, xctx->graph_names[i], i, XINSERT_NOREPLACE);
       dbg(1, "read_dataset(): get node list -> names[%d] = %s\n", i, xctx->graph_names[i]);
     }
     /* after this line comes the list of indexes and associated nodes */
-    if(sim_type && !strncmp(line, "Variables:", 10)) {
+    if(xctx->graph_sim_type && !strncmp(line, "Variables:", 10)) {
       variables = 1 ;
     }
   }
diff --git a/src/xinit.c b/src/xinit.c
index 0e368813..7b3be538 100644
--- a/src/xinit.c
+++ b/src/xinit.c
@@ -447,6 +447,7 @@ static void alloc_xschem_data(const char *top_path, const char *win_path)
   xctx->graph_bottom = 0;
   xctx->graph_left = 0;
   xctx->graph_lastsel = -1;
+  xctx->graph_sim_type = 0; /* type of sim, 1: Tran, 2: Dc, 3: Ac */
   xctx->graph_struct.hilight_wave[0] = -1; /* graph index of hilight wave */
   xctx->graph_struct.hilight_wave[1] = -1; /* index of wave */
   xctx->raw_schname = NULL;
diff --git a/src/xschem.h b/src/xschem.h
index ff422d3e..353d48b9 100644
--- a/src/xschem.h
+++ b/src/xschem.h
@@ -900,6 +900,7 @@ typedef struct {
   int graph_bottom; 
   int graph_left;
   int graph_lastsel; /* last graph that was clicked (selected) */
+  int graph_sim_type; /* type of sim, 1: Tran, 2: Dc, 3: Ac */
   Int_hashentry **raw_table;
   char *raw_schname;
   /*     */
diff --git a/src/xschem.tcl b/src/xschem.tcl
index 5629f22e..b3e38a81 100644
--- a/src/xschem.tcl
+++ b/src/xschem.tcl
@@ -1449,6 +1449,7 @@ proc graph_get_signal_list {siglist pattern } {
   if {$graph_sort} {set direction {-increasing}}
   set result {}
   set siglist [join [lsort $direction -dictionary $siglist] \n]
+  # just check if pattern is a valid regexp
   set err [catch {regexp $pattern {12345}} res]
   if {$err} {set pattern {}}
   foreach i $siglist {
diff --git a/xschem_library/examples/0_examples_top.sch b/xschem_library/examples/0_examples_top.sch
index f16d7cba..22140837 100644
--- a/xschem_library/examples/0_examples_top.sch
+++ b/xschem_library/examples/0_examples_top.sch
@@ -1457,3 +1457,4 @@ xwtAgA9ve8fHC0Dod8blIpQLQJBdgRgxavQ/AAAAgEslwD6d7SiMdxwqP41maeirFRxABH/Rb+tVM0DO
 cwtAyKwqggMC8z8AAABAXz/APixDHOviNio/cIyWTt0GHEAHmaX3NW0zQHJvU5F/bTNA3V5CW3kqoL85tJeeXUIJQIB/waNeQglAcFfF8JIdC0DY7tjwBPjxPwAAALCc
 UsA+"
 }
+C {test_ac.sym} 160 -90 0 0 {name=x15}
diff --git a/xschem_library/examples/cmos_example.sch b/xschem_library/examples/cmos_example.sch
index e1d48ebd..c9bf6049 100644
--- a/xschem_library/examples/cmos_example.sch
+++ b/xschem_library/examples/cmos_example.sch
@@ -4,7 +4,7 @@ K {}
 V {}
 S {}
 E {}
-B 2 1210 -510 1840 -30 {flags=graph
+B 2 1060 -550 1690 -70 {flags=graph
 y1=1.16665
 y2=5.05705
 divy=4
@@ -19,17 +19,14 @@ v(minus)"
 color="7 8 10"
 
 }
-B 2 1230 -1050 1807 -523 {flags=image,unscaled
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}
 T {CMOS DIFFERENTIAL AMPLIFIER
-EXAMPLE} 250 -650 0 0 0.4 0.4 {}
+EXAMPLE. DC simulation} 140 -730 0 0 0.4 0.4 {}
 T {This is an example of a code block that will
 be placed as a header in the netlist.
 use 'place=header' attribute and set the
 header text as a 'value' attribute} 720 -720 0 0 0.4 0.4 {}
 T {Select one or more graphs (and no other objects)
-and use arrow keys to zoom / pan waveforms} 740 -800 0 0 0.3 0.3 {}
-T {gain AC plot at 1uA, 10uA, 100uA bias current} 1250 -1090 0 0 0.4 0.4 {layer=5}
+and use arrow keys to zoom / pan waveforms} 1250 -60 0 0 0.3 0.3 {}
 N 30 -310 30 -280 {lab=VCC}
 N 30 -310 60 -310 {lab=VCC}
 N 260 -240 260 -190 {lab=GN}
@@ -110,6 +107,7 @@ value=".temp 30
 ** models are generally not free: you must download
 ** SPICE models for active devices and put them into the below 
 ** referenced file in netlist/simulation directory.
+** http://bwrcs.eecs.berkeley.edu/Classes/icdesign/ee241_s00/ASSIGNMENTS/TSMC035-n96g-params.txt
 .include \\"models_cmos_example.txt\\"
 .option savecurrents
 .save all @m4[gm] @m5[gm] @m1[gm]
@@ -137,15 +135,15 @@ C {ngspice_probe.sym} 600 -260 0 0 {name=r3}
 C {ngspice_probe.sym} 770 -420 0 0 {name=r4}
 C {ngspice_get_value.sym} 620 -160 0 0 {name=r5 node=i(@$\{path\}m1[id])
 descr="I="}
-C {code.sym} 920 -580 0 0 {name=HEADER
+C {code.sym} 890 -580 0 0 {name=HEADER
 place=header
 only_toplevel=true
 value="** ======================== **
 ** This is a netlist header **
 ** ======================== **"}
-C {launcher.sym} 755 -835 0 0 {name=h3 
+C {launcher.sym} 1195 -595 0 0 {name=h3 
 descr="Select arrow and 
-Ctrl-Left-Click to load/unload waveforms" 
+Ctrl key + Left-button-Click to load/unload waveforms" 
 tclcommand="
 xschem raw_read $netlist_dir/[file tail [file rootname [xschem get current_name]]].raw
 "
diff --git a/xschem_library/examples/test_ac.sch b/xschem_library/examples/test_ac.sch
new file mode 100644
index 00000000..121baf1a
--- /dev/null
+++ b/xschem_library/examples/test_ac.sch
@@ -0,0 +1,827 @@
+v {xschem version=3.0.0 file_version=1.2 }
+G {}
+K {}
+V {}
+S {}
+E {}
+B 2 1030 -330 1570 -130 {flags=graph
+y1=-5.7
+y2=44
+ypos1=0
+ypos2=2
+divy=10
+subdivy=1
+unity=1
+x1=3
+x2=10
+
+subdivx=8
+node=diffout
+color=4
+
+unitx=M
+divx=10
+dataset=1}
+B 2 1030 -550 1570 -350 {flags=graph
+y1=-180
+y2=180
+ypos1=0
+ypos2=2
+divy=10
+subdivy=1
+unity=1
+x1=3
+x2=10
+
+subdivx=8
+node=ph(diffout)
+color=7
+
+unitx=M
+divx=10
+dataset=1}
+T {CMOS DIFFERENTIAL AMPLIFIER
+EXAMPLE} 40 -680 0 0 0.4 0.4 {}
+T {Feedback
+network 
+loading} 870 -490 0 0 0.4 0.4 {}
+T {gain AC plot at 1uA, 10uA, 100uA bias current} 1030 -120 0 0 0.4 0.4 {layer=5}
+N 30 -240 30 -210 {lab=VCC}
+N 30 -240 60 -240 {lab=VCC}
+N 190 -230 190 -180 {lab=GN}
+N 190 -180 230 -180 {lab=GN}
+N 230 -180 230 -150 {lab=GN}
+N 230 -150 410 -150 {lab=GN}
+N 450 -220 450 -180 {lab=D}
+N 380 -250 400 -250 {lab=0}
+N 500 -250 520 -250 {lab=0}
+N 380 -220 520 -220 {lab=D}
+N 320 -250 340 -250 {lab=PLUS}
+N 560 -250 580 -250 {lab=MINUS}
+N 520 -400 570 -400 {lab=VCC}
+N 330 -400 380 -400 {lab=VCC}
+N 420 -400 480 -400 {lab=#net1}
+N 420 -400 420 -370 {lab=#net1}
+N 380 -370 420 -370 {lab=#net1}
+N 380 -370 380 -280 {lab=#net1}
+N 520 -370 520 -280 {lab=DIFFOUT}
+N 520 -470 520 -430 {lab=VCC}
+N 380 -470 520 -470 {lab=VCC}
+N 380 -470 380 -430 {lab=VCC}
+N 450 -490 450 -470 {lab=VCC}
+N 520 -330 900 -330 {lab=DIFFOUT}
+N 30 -370 30 -340 {lab=PLUS}
+N 30 -370 60 -370 {lab=PLUS}
+N 450 -120 450 -90 {lab=0}
+N 450 -120 470 -120 {lab=0}
+N 470 -150 470 -120 {lab=0}
+N 450 -150 470 -150 {lab=0}
+N 190 -120 190 -90 {lab=0}
+N 170 -120 190 -120 {lab=0}
+N 170 -150 170 -120 {lab=0}
+N 170 -150 190 -150 {lab=0}
+N 830 -600 830 -580 {lab=DIFFOUT_L}
+N 830 -520 830 -500 {lab=0}
+N 750 -250 750 -220 { lab=#net2}
+N 750 -160 750 -140 { lab=0}
+N 580 -250 580 -230 { lab=MINUS}
+N 720 -230 750 -230 { lab=#net2}
+N 650 -600 650 -580 {lab=D_L}
+N 650 -520 650 -500 {lab=0}
+N 790 -470 790 -450 { lab=DIFFOUT_L}
+N 790 -390 790 -370 { lab=D_L}
+N 830 -420 850 -420 { lab=DIFFOUT}
+N 850 -420 850 -330 { lab=DIFFOUT}
+N 580 -230 660 -230 { lab=MINUS}
+N 890 -330 890 -250 { lab=DIFFOUT}
+N 850 -250 890 -250 { lab=DIFFOUT}
+N 750 -250 790 -250 { lab=#net2}
+C {lab_pin.sym} 30 -150 0 0 {name=p17 lab=0  net_name=true}
+C {title.sym} 160 -30 0 0 {name=l1 author="Stefan Schippers"  net_name=true}
+C {nmos4.sym} 430 -150 0 0 {name=m1 model=cmosn w=5u l=2u m=1  net_name=true}
+C {pmos4.sym} 500 -400 0 0 {name=mtop_2nd model=cmosp w=5u l=2u m=1  net_name=true}
+C {vsource.sym} 30 -180 0 0 {name=VVCC value=5  net_name=true}
+C {lab_pin.sym} 450 -90 0 0 {name=p1 lab=0  net_name=true}
+C {lab_pin.sym} 60 -240 0 1 {name=p2 lab=VCC  net_name=true}
+C {nmos4.sym} 210 -150 0 1 {name=m3 model=cmosn w=5u l=2u m=1  net_name=true}
+C {lab_pin.sym} 190 -90 0 0 {name=p3 lab=0  net_name=true}
+C {isource.sym} 190 -260 0 0 {name=IBIAS value=IBIAS  net_name=true}
+C {lab_pin.sym} 190 -290 0 0 {name=p4 lab=0  net_name=true}
+C {nmos4.sym} 360 -250 0 0 {name=m4 model=cmosn w=10u l=1u m=1  net_name=true}
+C {lab_pin.sym} 400 -250 0 1 {name=p5 lab=0  net_name=true}
+C {nmos4.sym} 540 -250 0 1 {name=m5 model=cmosn w=10u l=1u m=1  net_name=true}
+C {lab_pin.sym} 500 -250 0 0 {name=p0 lab=0  net_name=true}
+C {lab_pin.sym} 570 -400 0 1 {name=p6 lab=VCC  net_name=true}
+C {pmos4.sym} 400 -400 0 1 {name=mtop_1st model=cmosp w=5u l=2u m=1  net_name=true}
+C {lab_pin.sym} 330 -400 0 0 {name=p7 lab=VCC  net_name=true}
+C {lab_pin.sym} 450 -490 0 0 {name=p8 lab=VCC  net_name=true}
+C {lab_pin.sym} 320 -250 0 0 {name=p9 lab=PLUS  net_name=true}
+C {lab_pin.sym} 580 -250 0 1 {name=p10 lab=MINUS  net_name=true}
+C {lab_pin.sym} 900 -330 0 1 {name=p11 lab=DIFFOUT  net_name=true}
+C {lab_pin.sym} 190 -200 0 0 {name=p13 lab=GN  net_name=true}
+C {lab_pin.sym} 30 -280 0 0 {name=p14 lab=0  net_name=true}
+C {vsource.sym} 30 -310 0 0 {name=VPLUS value="dc 2.5"
+}
+C {lab_pin.sym} 60 -370 0 1 {name=p15 lab=PLUS  net_name=true}
+C {code.sym} 10 -550 0 0 {name=STIMULI
+only_toplevel=true
+value="
+** ngspice
+.temp 30
+
+** models are generally not free: you must download
+** SPICE models for active devices and put them  into the below 
+** referenced file in netlist/simulation directory.
+** http://bwrcs.eecs.berkeley.edu/Classes/icdesign/ee241_s00/ASSIGNMENTS/TSMC035-n96g-params.txt
+.include \\"models_cmos_example.txt\\"
+
+.param IBIAS=1u
+.control
+let C=180/PI
+ac dec 10 1000 10G
+write test_ac.raw
+set appendwrite
+alter IBIAS=10u
+ac dec 10 1000 10G
+write test_ac.raw
+alter IBIAS=100u
+ac dec 10 1000 10G
+write test_ac.raw
+* plot vdb(ac1.diffout)
+* plot C*phase(ac1.diffout)
+plot vdb(ac2.diffout)
+plot C*phase(ac2.diffout)
+* plot vdb(ac3.diffout)
+* plot C*phase(ac3.diffout)
+.endc
+
+** ngspice
+* .save all
+
+** xyce, not needed if -r given om cmdline
+* .print tran format=raw v(diffout) v(plus) v(minus)
+"  net_name=true}
+C {lab_pin.sym} 790 -570 0 0 {name=l18 lab=DIFFOUT}
+C {lab_pin.sym} 790 -530 0 0 {name=l19 lab=0}
+C {lab_pin.sym} 830 -500 0 0 {name=l20 lab=0}
+C {lab_pin.sym} 830 -600 0 1 {name=l21 lab=DIFFOUT_L}
+C {vcvs.sym} 830 -550 0 0 {name=e1 value=1}
+C {lab_pin.sym} 750 -140 0 0 {name=p12 lab=0  net_name=true}
+C {lab_pin.sym} 450 -200 0 0 {name=p16 lab=D}
+C {lab_pin.sym} 610 -570 0 0 {name=l2 lab=D}
+C {lab_pin.sym} 610 -530 0 0 {name=l3 lab=0}
+C {lab_pin.sym} 650 -500 0 0 {name=l4 lab=0}
+C {lab_pin.sym} 650 -600 0 1 {name=l5 lab=D_L}
+C {vcvs.sym} 650 -550 0 0 {name=e2 value=1}
+C {nmos4.sym} 810 -420 0 1 {name=m7 model=cmosn w=10u l=1u m=1  net_name=true}
+C {lab_pin.sym} 790 -470 0 0 {name=l6 lab=DIFFOUT_L}
+C {lab_pin.sym} 790 -370 0 0 {name=l7 lab=D_L}
+C {lab_pin.sym} 790 -420 0 0 {name=p18 lab=0  net_name=true}
+C {vsource.sym} 690 -230 3 0 {name=VLOOP value="dc 0 ac 1 0"}
+C {res_ac.sym} 750 -190 0 0 {name=R2
+value=10G
+ac=0.1
+m=1}
+C {ind.sym} 820 -250 1 0 {name=L1
+m=1
+value=100k
+footprint=1206
+device=inductor}
+C {launcher.sym} 1040 -650 0 0 {name=h1 
+descr="Select arrow and 
+Ctrl key + Left Button-Click to load/unload waveforms
+from .raw file" 
+tclcommand="
+xschem raw_read $netlist_dir/[file tail [file rootname [xschem get current_name]]].raw
+"
+}
+C {launcher.sym} 1040 -580 0 0 {name=h2
+descr="View raw file"
+tclcommand="textwindow $netlist_dir/[file tail [file rootname [xschem get current_name]]].raw"
+}
+C {launcher.sym} 1040 -720 0 0 {name=h5 
+descr=" Ctrl-Left-Click to load/unload
+embedded waveforms" 
+tclcommand="xschem raw_read_from_attr"
+spice_data="
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diff --git a/xschem_library/examples/test_ac.sym b/xschem_library/examples/test_ac.sym
new file mode 100644
index 00000000..4c14e985
--- /dev/null
+++ b/xschem_library/examples/test_ac.sym
@@ -0,0 +1,11 @@
+v {xschem version=3.0.0 file_version=1.2}
+K {type=subcircuit
+format="@name @pinlist @symname"
+template="name=x1"
+}
+T {@symname} -49.5 -6 0 0 0.3 0.3 {}
+T {@name} 135 -22 0 0 0.2 0.2 {}
+L 4 -130 -10 130 -10 {}
+L 4 -130 10 130 10 {}
+L 4 -130 -10 -130 10 {}
+L 4 130 -10 130 10 {}