Copy in qucs Python files to process Qucs data in Python

pcb/discrete/discrete-rf-board/qucs/qucsdata.py

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+"""
+Module to handle a Qucs Dataset result file.
+"""
+
+import re
+import numpy as np
+import pprint as pp
+
+class QucsData:
+    """
+    Read an store a result file writen by Qucsator.
+    """
+    def __init__(self, filename):
+        # source dataset
+        self.filename = filename
+        # qucsator version that generated the data
+        self.version = ''
+        # list of all variable names
+        self.names = []
+        # data[name] = array
+        self.data = {}
+        # data dependent[name]=list(names)
+        self.dependent = {}
+
+        # parse
+        self.read(self.filename)
+
+    def __str__(self):
+        """
+        Print self.
+        """
+        pr  = ''
+        pr += 'File name: %s\n' %self.filename
+        pr += 'names:\n'
+        for name in self.names:
+            pr += '    \'%s\': shape %s\n' %(name, self.data[name].shape)
+        pr += 'dependent: \n'
+        pr += pp.pformat(self.dependent, indent=4)
+        pr += '\n'
+        return pr
+
+    def read(self,fileName):
+        """
+        Qucs Dataset parser.
+        """
+        variable = ''
+        with open(fileName) as qucsdata:
+            for line in qucsdata:
+                # header
+                r = re.match(r'\<Qucs Dataset (\d+\.\d+\.\d+)\>', line)
+                if r:
+                    self.version = r.group(1)
+
+                if '<indep' in line:
+                    # independent variables
+                    r = re.match(r'(\S+) (\S+) (\d+)', line.translate(None,"<>"))
+                    kind, identifier, size =  r.groups()
+                    # collect identifiers
+                    self.names.append(identifier)
+                    variable = identifier
+                    continue # next line
+
+                if '<dep' in line:
+                    # dependent variables
+                    # one or more independent, y=f(v,w,...)
+                    r = re.findall('(\S+)', line.translate(None,"<>"))
+                    identifier = r[1]
+                    self.dependent[identifier]= r[2:]
+                    self.names.append(identifier)
+                    variable = identifier
+                    continue # next line
+
+                if '</indep' in line:
+                    # reached end of independent variable
+                    # cast from list to numpy array
+                    values = np.array(self.data[variable])
+                    self.data[variable] = values
+                    variable = ''
+                    continue #  next line
+
+                if '</dep' in line:
+                    # reached end of dependent variable
+                    # dependencies are stacked on a single column
+                    # cast from list to 2D array
+                    # TODO check for multidimensional ndim > 2
+                    # <dep Variable axis1 axis2 axis3 ...>
+                    shape = []
+                    for dep in self.dependent[variable]:
+                        size = len(self.data[dep])
+                        shape.append (size)
+                    values = np.array(self.data[variable])
+                    self.data[variable] = values.reshape(tuple(shape),order='F')
+                    variable = ''
+                    continue #  next line
+
+                if variable:
+                    # collect data from line into temporary list
+                    if variable not in self.data.keys():
+                        self.data[variable] = []
+                    value = line.strip()
+                    if ('j' in value):
+                        # put imaginary to the end
+                        value = value.replace("j","")
+                        value = value+'j'
+                        value = complex(value)
+                    else:
+                        value = float(value)
+                    self.data[variable].append(value)
+
+
+
+