Add testing

src/tdastro/io_utils.py

@@ -2,7 +2,7 @@
 from astropy.table import Table
 
 
-def read_grid_data(input_file, format="ascii"):
+def read_grid_data(input_file, format="ascii", validate=False):
     """Read 2-d grid data from a text, csv, ecsv, or fits file.
 
     Each line is of the form 'x0 x1 value' where x0 and x1 are the grid
@@ -16,6 +16,10 @@ def read_grid_data(input_file, format="ascii"):
     format : `str`
         The file format. Should be one of ascii, csv, ecsv,
         or fits.
+        Default = 'ascii'
+    validate : `bool`
+        Perform additional validation on the input data.
+        Default = False
 
     Returns
     -------
@@ -26,24 +30,44 @@ def read_grid_data(input_file, format="ascii"):
     values : `numpy.ndarray`
         A 2-d array with the values at each point in the grid with
         shape (len(x0), len(x1)).
+
+    Raises
+    ------
+    ``ValueError`` if any data validation fails.
     """
-    data = Table.read(input_file, format=format)
+    data = Table.read(input_file, format=format, comment=r"\s*#")
     if len(data.colnames) != 3:
         raise ValueError(
             f"Incorrect format for grid data in {input_file} with format {format}. "
             f"Expected 3 columns but found {len(data.colnames)}."
         )
+    x0_col = data.colnames[0]
+    x1_col = data.colnames[1]
+    v_col = data.colnames[2]
 
     # Get the values along the x0 and x1 dimensions.
-    x0 = np.sort(np.unique(data[data.colnames[0]].data))
-    x1 = np.sort(np.unique(data[data.colnames[1]].data))
+    x0 = np.sort(np.unique(data[x0_col].data))
+    x1 = np.sort(np.unique(data[x1_col].data))
 
     # Get the array of values.
     if len(data) != len(x0) * len(x1):
         raise ValueError(
             f"Incomplete data for {input_file} with format {format}. Expected "
             f"{len(x0) * len(x1)} entries but found {len(data)}."
         )
-    values = data[data.colnames[2]].data.reshape((len(x0), len(x1)))
+
+    # If we are validating, loop through the entire table and check that
+    # the x0 and x1 values are in the expected order.
+    if validate:
+        counter = 0
+        for i in range(len(x0)):
+            for j in range(len(x1)):
+                if data[x0_col][counter] != x0[i]:
+                    raise ValueError(f"Incorrect x0 ordering in {input_file} at row={counter}.")
+                if data[x1_col][counter] != x1[j]:
+                    raise ValueError(f"Incorrect x0 ordering in {input_file} at row={counter}.")
+
+    # Build the values matrix.
+    values = data[v_col].data.reshape((len(x0), len(x1)))
 
     return x0, x1, values

tests/tdastro/conftest.py

@@ -0,0 +1,24 @@
+import os.path
+
+import pytest
+
+DATA_DIR_NAME = "data"
+TEST_DIR = os.path.dirname(__file__)
+
+
+@pytest.fixture
+def test_data_dir():
+    """Return the base test data directory."""
+    return os.path.join(TEST_DIR, DATA_DIR_NAME)
+
+
+@pytest.fixture
+def grid_data_good_file(test_data_dir):
+    """Return the file path for the good grid input file."""
+    return os.path.join(test_data_dir, "grid_input_good.ecsv")
+
+
+@pytest.fixture
+def grid_data_bad_file(test_data_dir):
+    """Return the file path for the bad grid input file."""
+    return os.path.join(test_data_dir, "grid_input_bad.txt")

tests/tdastro/data/grid_input_bad.txt

@@ -0,0 +1,6 @@
+0.0 1.0 0.0
+0.0 1.5 1.0
+1.0 1.0 2.0
+1.0 1.5 3.0
+2.0 1.5 5.0
+2.0 1.0 4.0

tests/tdastro/data/grid_input_good.ecsv

@@ -0,0 +1,8 @@
+# Comment up here.
+x0, x1, values
+0.0, 1.0, 0.0
+0.0, 1.5, 1.0
+1.0, 1.0, 2.0
+1.0, 1.5, 3.0
+2.0, 1.0, 4.0
+2.0, 1.5, 5.0

tests/tdastro/test_io_utils.py

@@ -0,0 +1,25 @@
+import numpy as np
+import pytest
+from tdastro.io_utils import read_grid_data
+
+
+def test_read_grid_data_good(grid_data_good_file):
+    """Test that we can read a well formatted grid data file."""
+    x0, x1, values = read_grid_data(grid_data_good_file, format="ascii.csv")
+    x0_expected = np.array([0.0, 1.0, 2.0])
+    x1_expected = np.array([1.0, 1.5])
+    values_expected = np.array([[0.0, 1.0], [2.0, 3.0], [4.0, 5.0]])
+
+    np.testing.assert_allclose(x0, x0_expected, atol=1e-5)
+    np.testing.assert_allclose(x1, x1_expected, atol=1e-5)
+    np.testing.assert_allclose(values, values_expected, atol=1e-5)
+
+
+def test_read_grid_data_bad(grid_data_bad_file):
+    """Test that we correctly handle a badly formatted grid data file."""
+    # We load without a problem is validation is off.
+    x0, x1, values = read_grid_data(grid_data_bad_file, format="ascii")
+    assert values.shape == (3, 2)
+
+    with pytest.raises(ValueError):
+        _, _, _ = read_grid_data(grid_data_bad_file, format="ascii", validate=True)