Reduce complexity and don't hardcode plotting units

mhkit/acoustics/graphics.py

@@ -50,7 +50,7 @@ def plot_spectogram(spsdl, fmin=10, fmax=100000, fig=None, ax=None, **kwargs):
     h = ax.pcolormesh(
         spsdl[time].values, spsdl[freq].values, spsdl.T, shading="nearest", **kwargs
     )
-    fig.colorbar(h, ax=ax, label="dB re 1 uPa^2/Hz")
+    fig.colorbar(h, ax=ax, label=spsdl.units)
     ax.set(xlabel="Time", ylabel="Frequency [Hz]")
 
     return fig, ax
@@ -97,6 +97,6 @@ def plot_spectra(spsdl, fmin=10, fmax=100000, fig=None, ax=None, **kwargs):
             left=0.1, right=0.95, top=0.85, bottom=0.2, hspace=0.3, wspace=0.15
         )
     ax.plot(spsdl[freq], spsdl.T, **kwargs)
-    ax.set(xlim=(fmin, fmax), xlabel="Frequency [Hz]", ylabel="$dB re 1 uPa^2/Hz$")
+    ax.set(xlim=(fmin, fmax), xlabel="Frequency [Hz]", ylabel=spsdl.units)
 
     return fig, ax

mhkit/acoustics/io.py

@@ -128,52 +128,6 @@ def _calculate_voltage_and_time(
     return raw_voltage, time, max_count
 
 
-def _convert_to_pressure(
-    raw_voltage: np.ndarray,
-    sensitivity: Union[int, float],
-    gain: Union[int, float],
-) -> np.ndarray:
-    """
-    Converts the raw voltage data into sound pressure and calculates
-    the minimum resolution and saturation levels based on the hydrophone's
-    sensitivity and gain.
-
-    Parameters
-    ----------
-    raw_voltage: numpy.ndarray
-        The normalized voltage values corresponding to the raw data from the WAV file.
-    sensitivity: int or float
-        The hydrophone's sensitivity in dB re 1 V/uPa, entered as a negative value.
-    gain: int or float
-        Amplifier gain in dB. Default is 0.
-
-    Returns
-    -------
-    pressure: numpy.ndarray
-        Calculated sound pressure values in Pascals (Pa).
-    """
-
-    if not isinstance(raw_voltage, np.ndarray):
-        raise TypeError("'raw_voltage' must be a numpy.ndarray.")
-    if not isinstance(sensitivity, (int, float)):
-        raise TypeError("'sensitivity' must be numeric (int or float).")
-    if not isinstance(gain, (int, float)):
-        raise TypeError("'gain' must be numeric (int or float).")
-
-    # Subtract gain
-    # hydrophone with sensitivity of -177 dB and gain of -3 dB = sensitivity of -174 dB
-    if gain:
-        sensitivity -= gain
-    # Convert calibration from dB rel 1 V/uPa into ratio
-    sensitivity = 10 ** (sensitivity / 20)  # V/uPa
-
-    # Sound pressure
-    pressure = raw_voltage / sensitivity  # uPa
-    pressure = pressure / 1e6  # Pa
-
-    return pressure
-
-
 def read_hydrophone(
     filename: Union[str, Path],
     peak_voltage: Union[int, float],
@@ -236,13 +190,23 @@ def read_hydrophone(
 
     # If sensitivity is provided, convert to sound pressure
     if sensitivity is not None:
-        raw_pressure = _convert_to_pressure(raw_voltage, sensitivity, gain)
+        # Subtract gain
+        # Hydrophone with sensitivity of -177 dB and gain of -3 dB = sensitivity of -174 dB
+        if gain:
+            sensitivity -= gain
+        # Convert calibration from dB rel 1 V/uPa into ratio
+        sensitivity = 10 ** (sensitivity / 20)  # V/uPa
+
+        # Sound pressure
+        pressure = raw_voltage / sensitivity  # uPa
+        pressure = pressure / 1e6  # Pa
+
         out = xr.DataArray(
-            raw_pressure,
+            pressure,
             coords={"time": time[:-1]},
             attrs={
                 "units": "Pa",
-                "sensitivity": sensitivity,
+                "sensitivity": np.round(sensitivity, 12),
                 # Pressure min resolution
                 "resolution": np.round(peak_voltage / max_count / sensitivity / 1e6, 9),
                 # Minimum pressure sensor can read

mhkit/tests/acoustics/test_io.py

@@ -59,22 +59,6 @@ def test_calculate_voltage_and_time(self):
         )
         pd.testing.assert_index_equal(time, expected_time)
 
-    def test_pressure_conversion(self):
-        raw_voltage = np.array([0.0, 1.25, -1.25, 0.625, -0.625])
-        sensitivity = -160
-        gain = 0
-
-        processed_pressure = acoustics.io._convert_to_pressure(
-            raw_voltage, sensitivity, gain
-        )
-
-        # Calculate expected values
-        adjusted_sensitivity = sensitivity - gain
-        sensitivity_linear = 10 ** (adjusted_sensitivity / 20)  # V/μPa
-
-        expected_pressure = raw_voltage / sensitivity_linear / 1e6  # Convert to Pa
-        np.testing.assert_allclose(processed_pressure, expected_pressure, atol=1e-12)
-
     def test_read_iclisten_metadata(self):
         from mhkit.acoustics.io import _read_iclisten_metadata