add compute_arr_desc

Author: TomDonoghue

specparam/tests/utils/test_data.py

@@ -65,6 +65,18 @@ def test_compute_presence():
     assert compute_presence(data2_full, average=True) == 1.0
     assert compute_presence(data2_nan, average=True) == 0.6
 
+def test_compute_arr_desc():
+
+    data1_full = np.array([1., 2., 3., 4., 5.])
+    minv, maxv, meanv = compute_arr_desc(data1_full)
+    for val in [minv, maxv, meanv]:
+        assert isinstance(val, float)
+
+    data1_nan = np.array([np.nan, 2., 3., np.nan, 5.])
+    minv, maxv, meanv = compute_arr_desc(data1_nan)
+    for val in [minv, maxv, meanv]:
+        assert isinstance(val, float)
+
 def test_trim_spectrum():
 
     f_in = np.array([0., 1., 2., 3., 4., 5.])

specparam/utils/data.py

@@ -120,6 +120,31 @@ def compute_presence(data, average=False, output='ratio'):
     return presence
 
 
+def compute_arr_desc(data):
+    """Compute descriptive measures of an array of data.
+
+    Parameters
+    ----------
+    data : array
+        Array of numeric data.
+
+    Returns
+    -------
+    min_val : float
+        Minimum value of the array.
+    max_val : float
+        Maximum value of the array.
+    mean_val : float
+        Mean value of the array.
+    """
+
+    min_val = np.nanmin(data)
+    max_val = np.nanmax(data)
+    mean_val = np.nanmean(data)
+
+    return min_val, max_val, mean_val
+
+
 def trim_spectrum(freqs, power_spectra, f_range):
     """Extract a frequency range from power spectra.