Merge pull request #5 from smartsammler/fix-python3

Make kafe run with python3

.gitignore

@@ -7,6 +7,8 @@
 *.log
 #.kafe
 *.egg-info
+*.cache
+*.eggs
 
 ##########
 # Images #

CHANGELOG

@@ -2,6 +2,12 @@ master
 ======
     %  [TODO] add unit test for input file parser
 
+v1.3.0
+======
+
+    %  [FIX] make code Python 3 compatible. 
+       Imports solved with try: Python2 variant; except ImportError: Python3 variant
+
 v1.1.0
 ======
 
@@ -18,6 +24,7 @@ v1.1.0
 
 v1.0.1
 ======
+
     %  [BUG] in fit.py (color name "darmagenta" -> "darkmagenta")
     %  [FIX] for matplotlib vers. 1.5.x : bbox parameters in plot.py
     %  [NOTE] set_color_cycle in fit.py is deprecated in matplotlib 1.5,

install.sh

@@ -2,7 +2,7 @@
 
 # Install script for kafe using pip
 
-function check_python_2 () {
+function check_python_2_3 () {
     echo "Checking Python version for executable '$1'..."
     if ! [[ `which $1` ]]; then
         echo "Python executable '$1' not found in PATH!"
@@ -13,15 +13,15 @@ function check_python_2 () {
         echo "Python executable '$1' in Python 2: ok"
         return 0
     elif [[ PYTHON_VERSION -eq 3 ]]; then
-        echo "Python executable '$1' is Python 3: not supported"
-        return 1
+        echo "Python executable '$1' in Python 3: ok"
+        return 0
     else
         echo "Python executable '$1' not found in PATH!"
         return 1
     fi
 }
 
-function check_pip_python_2 () {
+function check_pip_python_2_3 () {
     echo "Checking Python version for pip executable '$1'..."
     if ! [[ `which $1` ]]; then
         echo "Pip executable '$1' not found in PATH!"
@@ -32,8 +32,8 @@ function check_pip_python_2 () {
         echo "Pip executable '$1' uses Python 2: ok"
         return 0
     elif [[ PIP_PYTHON_VERSION -eq 3 ]]; then
-        echo "Pip executable '$1' uses Python 3: not supported"
-        return 1
+        echo "Pip executable '$1' uses Python 3: ok"
+        return 0
     else
         echo "Pip executable '$1' not found in PATH!"
         return 1
@@ -43,26 +43,26 @@ function check_pip_python_2 () {
 ## -- main -- ##
 
 # pip executables to try out
-PIP_EXEC_LIST="pip pip2 pip2.7"
+PIP_EXEC_LIST="pip pip2 pip2.7 pip3 pip3.1 pip3.2 pip3.3 pip3.4 pip3.5 pip3.6 pip3.7"
 PY_EXEC="python"
 
-check_python_2 $PY_EXEC
-found_python_2=$?
+check_python_2_3 $PY_EXEC
+found_python_2_3=$?
 
-if [[ found_python_2 -eq 0 ]]; then
+if [[ found_python_2_3 -eq 0 ]]; then
     for pip_exec in $PIP_EXEC_LIST; do
-        check_pip_python_2 $pip_exec
-        found_pip_python_2=$?
-        if [[ found_pip_python_2 -eq 0 ]]; then
+        check_pip_python_2_3 $pip_exec
+        found_pip_python_2_3=$?
+        if [[ found_pip_python_2_3 -eq 0 ]]; then
             break
         fi
     done
-    if [[ found_pip_python_2 -ne 0 ]]; then
+    if [[ found_pip_python_2_3 -ne 0 ]]; then
         echo "None of the executables '$PIP_EXEC_LIST' seem to be valid. Aborting."
         exit 1
     fi
 else
-    echo "Python 2 executable not found on system. Aborting."
+    echo "Python 2 or Python 3 executable not found on system. Aborting."
     exit 1
 fi
 

kafe/__init__.py

@@ -15,29 +15,29 @@
 Fitting with **kafe** in a nutshell goes like this:
 
     1) create a `Dataset` object from your measurement data
-    
+
     >>> my_d = kafe.Dataset(data=[[0., 1., 2.], [1.23, 3.45, 5.62]])
-    
+
     2) add errors (uncertainties) to your `Dataset`
-    
+
     >>> my_d.add_error_source('y', 'simple', 0.5)  # y errors, all +/- 0.5
-    
+
     3) import a model function from `kafe.function_library` (or define one
        yourself)
-       
+
     >>> from kafe.function_library import linear_2par
-    
+
     4) create a `Fit` object from your `Dataset` and your model function
-    
+
     >>> my_f = kafe.Fit(my_d, linear_2par)
-    
+
     5) do the fit
-    
+
     >>> my_f.do_fit()
-    
+
     6) *(optional)* if you want to see a plot of the result, use the `Plot`
        object
-       
+
     >>> my_p = kafe.Plot(my_f)
     >>> my_p.plot_all()
     >>> my_p.show()
@@ -50,7 +50,7 @@
 """
 
 # Import config variables
-import config
+from . import config
 
 # Import version info
 from . import _version_info
@@ -88,7 +88,7 @@
 import matplotlib
 try:
     matplotlib.use(config.G_MATPLOTLIB_BACKEND)
-except ValueError, e:
+except ValueError as e:
     # matplotlib does not provide requested backend
     _logger.error("matplotlib error: %s" % (e,))
     _logger.warning("Failed to load requested backend '%s' for matplotlib. "

kafe/_version_info.py

@@ -1,14 +1,14 @@
 '''
 .. module:: _version_info
    :platform: Unix
-   :synopsis: Version 1.2.0 of kafe, release Jun. 2016
+   :synopsis: Version 1.3.0 of kafe, release Feb. 2017
 
 .. moduleauthor:: Daniel Savoiu <danielsavoiu@gmail.com>
                   Guenter Quast <g.quast@kit.edu>
 '''
 
 major = 1
-minor = 2
+minor = 3
 revision = 0
 
 def _get_version_tuple():

kafe/config.py

@@ -8,7 +8,10 @@
 
 import sys
 import os
-import ConfigParser
+try:
+    import ConfigParser
+except ImportError:
+    import configparser as ConfigParser
 import kafe
 
 # import main logger for kafe
@@ -80,7 +83,7 @@ def create_config_file(config_type, force=False):
                      "from '%s' to '%s'." \
                      % (kafe_default_config_file, _file))
     else:
-        raise Exception("Cannot create config file at '%s': file exists" \
+        raise Exception("Cannot create config file at '%s': file exists"
                         % (_file,))
 
 
@@ -101,11 +104,11 @@ def create_config_file(config_type, force=False):
 
 # Raise Error is no default config file found
 if not os.path.exists(os.path.join(*kafe_configs['system'])):
-    raise IOError, "No default config file for kafe was " \
-                   "found on the system but there should " \
-                   "be one at '%s'. Please check your " \
-                   "installation. " \
-                   % (os.path.join(*kafe_configs['system']),)
+    raise IOError("No default config file for kafe was "
+                  "found on the system but there should "
+                  "be one at '%s'. Please check your "
+                  "installation. "
+                   % (os.path.join(*kafe_configs['system']),))
 
 # Load all found config files into the ConfigParser
 kafe_config_file = None

kafe/dataset.py

@@ -15,13 +15,11 @@
 # DS 150610: add ErrorSource object
 # ---------------------------------------------
 
-from string import join, split
-
 import numpy as np
 from scipy.linalg import LinAlgError
 import os
 
-from numeric_tools import cov_to_cor, cor_to_cov, extract_statistical_errors, \
+from .numeric_tools import cov_to_cor, cor_to_cov, extract_statistical_errors, \
     zero_pad_lower_triangle, make_symmetric_lower
 
 NUMBER_OF_AXES = 2
@@ -190,8 +188,8 @@ def get_matrix(self, size=None):
                 try:
                     iter(self.error_value)
                 except:
-                    raise ValueError, ("Given error `%r' is not iterable."
-                                       % (self.error_value,))
+                    raise ValueError("Given error `%r' is not iterable."
+                                     % (self.error_value,))
                 else:
                     # use value given
                     _val = np.asarray(self.error_value)  # size is implicit
@@ -211,7 +209,7 @@ def get_matrix(self, size=None):
             return _mat
 
         else:
-            raise ValueError, "Unknown error type `%s'" % (self.error_type,)
+            raise ValueError("Unknown error type `%s'" % (self.error_type,))
 
 
 class Dataset(object):
@@ -389,7 +387,7 @@ def set_data(self, data):
                 #data = data
                 pass
 
-        for axis in xrange(self.__n_axes):  # go through the axes
+        for axis in range(self.__n_axes):  # go through the axes
             self.set_axis_data(axis, data[axis])  # load data for axis
 
     def set_axis_data(self, axis, data):
@@ -616,7 +614,7 @@ def calc_cov_mats(self, axis='all'):
                  np.matrix(np.zeros((_size, _size)))]
 
         if axis is 'all':
-            _axes_list = range(self.__n_axes)
+            _axes_list = list(range(self.__n_axes))
         else:
             _axes_list = [self.get_axis(axis)]
 
@@ -1072,7 +1070,7 @@ def get_formatted(self, format_string=".06e", delimiter='\t'):
         output_list = []
 
         # go through the axes
-        for axis in xrange(self.__n_axes):
+        for axis in range(self.__n_axes):
             # define a helper list which we will fill out
             helper_list = []
 
@@ -1123,7 +1121,7 @@ def get_formatted(self, format_string=".06e", delimiter='\t'):
                     # if there are also correlations (syst errors)
                     if self.__query_has_correlations[axis]:
                         # go through the columns of the correlation matrix
-                        for col in xrange(idx):
+                        for col in range(idx):
                             # append corr. coefficients to the helper list
                             helper_list[-1].append(
                                 format(cor_mat[idx, col], format_string)
@@ -1136,7 +1134,7 @@ def get_formatted(self, format_string=".06e", delimiter='\t'):
         tmp_string = ''
         for row in output_list:
             for entry in row:
-                tmp_string += join(entry, delimiter) + '\n'
+                tmp_string += delimiter.join(entry) + '\n'
 
         return tmp_string
 
@@ -1237,7 +1235,7 @@ def read_from_file(self, input_file):
             tmp_linenumber += 1                 # update the line number
 
             if '#' in line:
-                line = split(line, '#')[0]      # ignore anything after
+                line = line.split('#')[0]      # ignore anything after
                                                 # a comment sign (#)
 
             if (not line) or (line.isspace()):  # if empty line encountered
@@ -1293,7 +1291,7 @@ def read_from_file(self, input_file):
                     tmp_reading_data_block = True
 
                 # get the entries on the line as a list (whitespace-delimited)
-                tmp_fields = split(line)
+                tmp_fields = line.split()
 
                 # if there is only one entry,
                 # we know it's just the measurement data
@@ -1314,7 +1312,7 @@ def read_from_file(self, input_file):
                 if tmp_has_syst_errors:
                     # other fields are correlation coefficients
                     # (add 1.0 on main diagonal)
-                    tmp_cormat.append(map(float, tmp_fields[2:]) + [1.0])
+                    tmp_cormat.append(list(map(float, tmp_fields[2:]) + [1.0]))
 
                 # if there are not enough entries
                 # for a valid correlation matrix
@@ -1358,11 +1356,11 @@ def read_from_file(self, input_file):
                 self.set_cov_mat(tmp_axis, None)  # unset cov mat
 
         # Turn covariance matrices into ErrorSource objects
-        for axis in xrange(self.__n_axes):
+        for axis in range(self.__n_axes):
             _mat = self.get_cov_mat(axis)
 
             # remove existing error model (all error sources)
-            for err_src_id in xrange(len(self.err_src[axis])):
+            for err_src_id in range(len(self.err_src[axis])):
                 self.remove_error_source(axis, err_src_id, recompute_cov_mat=False)
 
             if _mat is not None:

kafe/dataset_tools.py

@@ -137,7 +137,7 @@ def build_dataset(xdata, ydata, cov_mats=None,
                       'yabscor': yabscor, 'yrelcor': yrelcor}
 
     # go through the keyword arguments
-    for key, val in error_keywords.iteritems():
+    for key, val in error_keywords.items():
 
         err_spec = key
         err_val = val