Modifiction to ipf_read and added test.

plio/examples/SocetSet/P20_008845_1894_XN_09N203W.csv

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+P03_002226_1895_XI_09N203W_1,1,0,0,-1197.647949,-569.925598,0.0,0.0,-0.070627,0.194853,0.0,0.0
+P03_002226_1895_XI_09N203W_2,1,0,0,-1241.685791,-499.006836,0.0,0.0,-0.066482,0.270447,0.0,0.0

plio/io/io_bae.py

 import json
 import re
+from functools import singledispatch
 
 import numpy as np
 import pandas as pd
@@ -52,14 +53,19 @@ def socetset_keywords_to_json(keywords, ell=None):
         parse(ell)
     return json.dumps(stream)
 
-def read_ipfs(input_data_list):
+@singledispatch
+def read_ipf(arg): # pragma: no cover
+    return str(arg)
+
+@read_ipf.register(str)
+def read_ipf_str(input_data):
     """
     Read a socet ipf file into a pandas data frame
 
     Parameters
     ----------
-    input_data_list : list
-                 list of paths to the a set of input data files
+    input_data : str
+                 path to the an input data file
 
     Returns
     -------
@@ -67,102 +73,56 @@ def read_ipfs(input_data_list):
          containing the ipf data with appropriate column names and indices
     """
 
-    default_columns = np.genfromtxt(input_data_list[0], skip_header=2, dtype='unicode',
-                                    max_rows = 1, delimiter = ',')
-
-    columns = []
-
-    for column in default_columns:
-
-        if '(' in column and ')' in column:
-            column_name ,suffix = column.split('(')
-            num = int(suffix.split(')')[0])
+    # Check that the number of rows is matching the expected number
+    with open(input_data, 'r') as f:
+        for i, l in enumerate(f):
+            if i == 1:
+                cnt = int(l)
+            elif i == 2:
+                col = l
+                break
 
-            for column_num in range(int(num)):
-                new_column = '{}{}'.format(column_name, column_num)
-                columns.append(new_column);
+    columns = np.genfromtxt(input_data, skip_header=2, dtype='unicode',
+                            max_rows = 1, delimiter = ',')
 
-        else:
-            columns.append(column)
+    # TODO: Add unicode conversion
+    d = [line.split() for line in open(input_data, 'r')]
+    d = np.hstack(np.array(d[3:]))
 
-    d_total = []
+    d = d.reshape(-1, 12)
 
-    for input_file in input_data_list:
-        d = read_ipf(input_file)
-        for point in d:
-            d_total.append(point)
+    df = pd.DataFrame(d, columns=columns)
 
-    df = pd.DataFrame(d_total, columns=columns)
+    assert int(cnt) == len(df), 'Dataframe length {} does not match point length {}.'.format(int(cnt), len(df))
 
     # Soft conversion of numeric types to numerics, allows str in first col for point_id
     df = df.apply(pd.to_numeric, errors='ignore')
 
-    # Validate the read data with the header point count
-    # assert int(cnt) == len(df), 'Dataframe length {} does not match point length {}.'.format(int(cnt), len(df))
-
     return df
 
-def read_ipf(input_data):
+@read_ipf.register(list)
+def read_ipf_list(input_data_list):
     """
     Read a socet ipf file into a pandas data frame
 
     Parameters
     ----------
-    input_data : str
-                 path to the an input data file
+    input_data_list : list
+                 list of paths to the a set of input data files
 
     Returns
     -------
     df : pd.DataFrame
          containing the ipf data with appropriate column names and indices
     """
+    frames = []
 
-    # Check that the number of rows is matching the expected number
-    with open(input_data, 'r') as f:
-        for i, l in enumerate(f):
-            if i == 1:
-                cnt = int(l)
-            elif i == 2:
-                col = l
-                break
-
-    # default_columns = np.genfromtxt(input_data, skip_header=2, dtype='unicode',
-    #                                 max_rows = 1, delimiter = ',')
-    #
-    # columns = []
-    #
-    # for column in default_columns:
-    #
-    #     if '(' in column and ')' in column:
-    #         column_name ,suffix = column.split('(')
-    #         num = int(suffix.split(')')[0])
-    #
-    #         for column_num in range(int(num)):
-    #             new_column = '{}{}'.format(column_name, column_num)
-    #             columns.append(new_column);
-    #
-    #     else:
-    #         columns.append(column)
-
-    # TODO: Add unicode conversion
-
-    d = [line.split() for line in open(input_data, 'r')]
-    d = np.hstack(np.array(d[3:]))
-    d = d.reshape(-1, 12)
-
-    assert int(cnt) == len(d), 'Dataframe length {} does not match point length {}.'.format(int(cnt), len(df))
+    for input_file in input_data_list:
+        frames.append(read_ipf(input_file))
 
-    return d
+    df = pd.concat(frames)
 
-    # df = pd.DataFrame(d, columns=columns)
-    #
-    # # Soft conversion of numeric types to numerics, allows str in first col for point_id
-    # df = df.apply(pd.to_numeric, errors='ignore')
-    #
-    # # Validate the read data with the header point count
-    # assert int(cnt) == len(df), 'Dataframe length {} does not match point length {}.'.format(int(cnt), len(df))
-    #
-    # return df
+    return df
 
 def read_gpf(input_data):
     """
@@ -242,7 +202,7 @@ def save_gpf(df, output_file):
     try:
         outGPF = open(output_file, 'w', newline='\r\n')
     except:
-        print ('Unable to open output gpf file: {0}'.format(output_file))
+        print('Unable to open output gpf file: {0}'.format(output_file))
         return 1
 
     #grab number of rows in pandas dataframe

plio/io/tests/test_io_bae.py

 import json
+
 import numpy as np
 import pandas as pd
 from pandas.util.testing import assert_frame_equal
 
-from plio.io.io_bae import socetset_keywords_to_json, read_gpf, save_gpf
+from plio.io.io_bae import socetset_keywords_to_json, read_gpf, save_gpf, read_ipf
 from plio.examples import get_path
 
 import pytest
@@ -13,27 +14,40 @@ def insight_gpf():
     return get_path('InSightE08_XW.gpf')
 
 @pytest.fixture()
-def insight_expected():
+def insight_expected_gpf():
     return pd.read_csv(get_path('InSightE08_XW.csv'))
 
-@pytest.mark.parametrize('gpf, expected', [(insight_gpf(),insight_expected())])
+@pytest.fixture
+def insight_ipf():
+    return get_path('P20_008845_1894_XN_09N203W.ipf')
+
+@pytest.fixture()
+def insight_expected_ipf():
+    return pd.read_csv(get_path('P20_008845_1894_XN_09N203W.csv'))
+
+@pytest.mark.parametrize('gpf, expected', [(insight_gpf(),insight_expected_gpf())])
 def test_read_gfp(gpf, expected):
     df = read_gpf(gpf)
     assert_frame_equal(df, expected)
 
-@pytest.mark.parametrize('gpf', [(insight_gpf())])
-def test_write_gpf(gpf):
+@pytest.mark.parametrize('ipf, expected', [([insight_ipf()],insight_expected_ipf())])
+def test_read_ifp(ipf, expected):
+    df = read_ipf(ipf)
+    assert_frame_equal(df, expected)
+
+@pytest.mark.parametrize('gpf, file', [(insight_gpf(), 'out.gpf')])
+def test_write_gpf(gpf, file):
     """
     We test by manually comparing files and not using filecmp so that we
     are not testing float point precision differences, e.g. 0.0 == 0.00000000.
     """
     df = read_gpf(gpf)
-    save_gpf(df, 'out.gpf')
+    save_gpf(df, file)
 
     with open(gpf) as f:
         fl = f.readlines()
 
-    with open('out.gpf') as f:
+    with open(file) as f:
         fs = f.readlines()
 
     # Check that the header is the same
@@ -41,7 +55,7 @@ def test_write_gpf(gpf):
         assert fl[i] == fs[i]
 
     truth_arr = np.genfromtxt(gpf, skip_header=3)
-    test_arr = np.genfromtxt('out.gpf', skip_header=3)
+    test_arr = np.genfromtxt(file, skip_header=3)
     np.testing.assert_array_almost_equal(truth_arr, test_arr)
 
 def test_create_from_socet_lis():
@@ -49,8 +63,8 @@ def test_create_from_socet_lis():
     socetell = get_path('ellipsoid.ell')
     js = json.loads(socetset_keywords_to_json(socetlis))
     assert isinstance(js, dict)  # This is essentially a JSON linter
-    # Manually validated 
+    # Manually validated
     assert 'RECTIFICATION_TERMS' in js.keys()
     assert 'SEMI_MAJOR_AXIS' in js.keys()  # From ellipsoid file
     assert 'NUMBER_OF_EPHEM' in js.keys()
-    assert len(js['EPHEM_PTS']) / 3 == js['NUMBER_OF_EPHEM'] 
+    assert len(js['EPHEM_PTS']) / 3 == js['NUMBER_OF_EPHEM']
\ No newline at end of file