* Introducing "wpylib" which is the collection of my small python utilities.

* graph_digitizer: Utility to help me digitize numbers from a graph image
  files (JPG/PNG plots).

__init__.py

@@ -0,0 +1,13 @@
+# $Id: __init__.py,v 1.1 2009-12-04 19:30:26 wirawan Exp $
+#
+# wpylib main module
+# Created: 20091204
+# Wirawan Purwanto
+#
+# Main wpylib package. It is just a stub.
+# The "wpylib" namespace contains all simple tools that I am making
+# in the course of my research and hobby.
+# In the future, useful modules will continue their lives as separate
+# modules outside the "wpylib" jail. :-)
+#
+pass

graph_digitizer.py

@@ -0,0 +1,85 @@
+#!/usr/bin/ipython -pylab
+#
+# $Id: graph_digitizer.py,v 1.1 2009-12-04 19:30:26 wirawan Exp $
+#
+# Created: 20091204
+# Wirawan Purwanto
+#
+# Simple and dirty utility module to digitize a graph (e.g. those image files
+# obtained from a journal article PDF).
+#
+
+import numpy
+
+def make_matrix(Str, debug=None):
+  """Simple tool to convert a string like
+    '''1 2 3
+    4 5 6
+    7 8 9'''
+  into a numpy matrix (or, actually, an array object)."""
+  if isinstance(Str, numpy.matrix):
+    return numpy.array(Str)
+  elif isinstance(Str, numpy.ndarray):
+    if len(Str.shape) == 2:
+      return Str.copy()
+    else:
+      raise ValueError, "Cannot make matrix out of non-2D array"
+  Str2 = ";".join([ row.rstrip().rstrip(";") for row in Str.split("\n") if row.strip() != "" ])
+  rslt = numpy.matrix(Str2)
+  if debug: print rslt
+  return numpy.array(rslt)
+
+def get_axis_scaler(data, axis):
+  """Simple routine to obtain the scaling factor from pixel coordinate to
+  x or y value. The `data' string argument is a literal table like:
+      xpixel  ypixel   xvalue
+      ...
+  or
+      xpixel  ypixel   yvalue
+      ...
+  Only linear scale is supported."""
+  from scipy import stats
+  datamtx = make_matrix(data)
+
+  if axis == "x":
+    xx = datamtx[:,0]
+    yy = datamtx[:,2]
+  else:
+    xx = datamtx[:,1]
+    yy = datamtx[:,2]
+
+  # example from
+  # http://www2.warwick.ac.uk/fac/sci/moac/currentstudents/peter_cock/python/lin_reg
+  (gradient, intercept, r_value, p_value, std_err) = stats.linregress(xx,yy)
+  print gradient, intercept, r_value, p_value, std_err
+
+  #return (float(gradient[0]), float(intercept[0]))
+  return (gradient, intercept)
+
+
+class axes_scaler:
+  """The main engine to "unscale" the graph's data points from pixel (x,y) to
+  true axis (x,y) value. Only linear axis is supported here."""
+
+  def __init__(self, data_x, data_y):
+    """Initialize the axis scalers (x and y) from a given `pixel -> axis value'
+    mapping."""
+    self.init(data_x, data_y)
+
+  def init(self, data_x, data_y):
+    self.xscaler = get_axis_scaler(data_x, "x")
+    self.yscaler = get_axis_scaler(data_y, "y")
+
+  def __call__(self, x, y):
+    return ((self.xscaler[0]*x + self.xscaler[1]), \
+            (self.yscaler[0]*y + self.yscaler[1]))
+
+  def scale_many(self, data):
+    mtx = make_matrix(data)
+    rslt = []
+    for row in mtx:
+      (x, y) = row[0], row[1]
+      rslt.append(list( self(x, y) ))
+      #print x, y
+    return numpy.array(rslt)
+