My tools of the trade for python programming.
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#!/usr/bin/ipython -pylab
# $Id:,v 1.2 2009-12-04 19:57:22 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
from wpylib.text_tools import make_matrix
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
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]
xx = datamtx[:,1]
yy = datamtx[:,2]
# example from
(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'
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)