Add Xyce .prn file support to cicsim plot & wave

cicsim/plot.py

@@ -5,6 +5,7 @@
 import numpy as np
 import pandas as pd
 import sys
+import os
 from .command import *
 import math
 from .ngraw import *
@@ -47,14 +48,18 @@ def plot(df,xname,yname,ptype=None,ax=None,label=""):
 
 def rawplot(fraw,xname,yname,ptype=None,axes=None,fname=None):
 
-
-    dfs = toDataFrames(ngRawRead(fraw))
-
-
-    if(len(dfs) == 0):
-        raise ValueError("No plots found in .raw file")
-
-    df = dfs[0]
+    ext = os.path.splitext(fraw)[1].lower()
+    if ext == '.raw':
+        dfs = toDataFrames(ngRawRead(fraw))
+        if len(dfs) == 0:
+            raise ValueError("No plots found in .raw file")
+        df = dfs[0]
+    else:
+        from .wavefiles import WaveFile
+        wf = WaveFile(fraw, xaxis=xname)
+        df = wf.df
+        if df is None or df.empty:
+            raise ValueError("No data found in %s" % fraw)
 
     if("," in yname):
         names = yname.split(",")

cicsim/wavefiles.py

@@ -2,6 +2,7 @@
 
 import cicsim as cs
 import os
+import re
 import numpy as np
 import pandas as pd
 from matplotlib.ticker import EngFormatter
@@ -133,6 +134,7 @@ def reload(self):
                 self.modified = newmodified
 
     PANDAS_READERS = {
+        '.prn':     lambda self: self._read_prn(),
         '.csv':     lambda self: self._read_csv(','),
         '.tsv':     lambda self: self._read_csv('\t'),
         '.txt':     lambda self: self._read_csv('\t'),
@@ -175,6 +177,66 @@ def _read_excel(self):
         df.columns = [c.strip() for c in df.columns]
         return df
 
+    def _read_prn(self):
+        """Parse Xyce .prn (print) waveform file into a DataFrame."""
+        sweep_var = "time"
+        var_names = []
+        times = []
+        data_rows = []
+
+        with open(self.fname, 'r') as f:
+            in_header = False
+            in_nodes = False
+            pending_time = None
+
+            for line in f:
+                line_s = line.strip()
+
+                if line_s.startswith('#H'):
+                    in_header = True
+                    in_nodes = False
+                    continue
+
+                if line_s.startswith('#N'):
+                    in_header = False
+                    in_nodes = True
+                    continue
+
+                if line_s.startswith('#C'):
+                    in_nodes = False
+                    in_header = False
+                    parts = line_s.split()
+                    pending_time = float(parts[1])
+                    continue
+
+                if line_s.startswith('#'):
+                    in_header = False
+                    in_nodes = False
+                    pending_time = None
+                    continue
+
+                if in_header:
+                    m = re.search(r"SWEEPVAR='([^']+)'", line_s)
+                    if m:
+                        sweep_var = m.group(1).lower()
+                    continue
+
+                if in_nodes:
+                    var_names.extend(re.findall(r"'([^']+)'", line_s))
+                    continue
+
+                if pending_time is not None and line_s:
+                    vals = [float(v.split(':')[0]) for v in line_s.split()]
+                    if vals:
+                        times.append(pending_time)
+                        data_rows.append(vals)
+                    pending_time = None
+
+        n_vars = len(var_names)
+        cols = [sweep_var] + [v.lower() for v in var_names]
+        rows = [[t] + d[:n_vars] for t, d in zip(times, data_rows)]
+        return pd.DataFrame(rows, columns=cols)
+
     @staticmethod
     def excel_sheet_names(fname):
         xl = pd.ExcelFile(fname)