Merge pull request #78 from jtgasparik/plot_norm_deriv

Function to plot the nomalized derivative

Author: rcjackson

pysp2/util/normalized_derivative_method.py

@@ -73,3 +73,47 @@ def central_difference(S, num_records=None, normalize=True):
 
     return xr.Dataset(dSdt)
 
+
+def plot_normalized_derivative(ds, record_no, chn=0):
+    """
+    Plots the normalized derivative of the scattering signal for a given record_no and channel.
+
+    Parameters
+    ----------
+    ds: xarray Dataset
+        The dataset containing the normalized derivative to plot.
+    record_no: int
+        The record number to plot.
+    chn: int
+        The channel number to plot (0 or 4).
+    Returns
+    -------
+    ax: matplotlib Axes
+        The axes object containing the plot.
+    """
+    import matplotlib.pyplot as plt
+
+    if chn not in [0, 4]:
+        raise ValueError("Channel number must be 0 or 4.")
+    
+    spectra = ds.isel(event_index=record_no)
+    time = spectra['time'].values
+    inp_data = {}
+    inp_data['time'] = xr.DataArray(np.array(time[np.newaxis]),
+                                    dims=['time'])
+    inp_data['Data_ch' + str(chn)] = xr.DataArray(
+        spectra['Data_ch' + str(chn)].values[np.newaxis, :],
+        dims=['time', 'bins'])
+    inp_data = xr.Dataset(inp_data)
+    bins = np.linspace(0, 100, 100)
+
+    ch_name = f'Data_ch{chn}'
+    plt.figure(figsize=(10, 6))
+    ax = plt.gca()
+    inp_data[ch_name].plot(ax=ax)
+    ax.set_title(f'Normalized Derivative of Scattering Signal - Channel {chn} Record {record_no}')
+    ax.set_xlabel('Time (s)')
+    ax.set_ylabel('Normalized Derivative')
+    plt.grid()
+
+    return ax

tests/baseline/test_plot_normalized_derivative.png

@@ -0,0 +1,7 @@
+import pytest
+import matplotlib.pyplot as plt
+
+@pytest.fixture(autouse=True)
+def close_figures():
+    yield
+    plt.close("all")

tests/conftest.py

@@ -21,4 +21,5 @@ def test_central_difference():
     np.testing.assert_almost_equal(dSdt_norm['Data_ch4'].isel(event_index=5876, time=99).item(), 
                                    7.166666666e7/-30152, decimal=2)
     np.testing.assert_almost_equal(dSdt_norm['Data_ch4'].isel(event_index=5876, time=19).item(), 
-                                   1.5e7/-30132, decimal=2)
+                                   1.5e7/-30132, decimal=2)
+    

tests/test_ndm.py

@@ -0,0 +1,23 @@
+import matplotlib
+import pytest
+import xarray as xr
+import numpy as np
+
+import pysp2
+from pysp2.util.normalized_derivative_method import plot_normalized_derivative
+
+matplotlib.use("Agg")
+
+@pytest.mark.mpl_image_compare(tolerance=10)
+def test_plot_normalized_derivative():
+
+    my_sp2b = pysp2.io.read_sp2(pysp2.testing.EXAMPLE_SP2B)
+    my_ini = pysp2.io.read_config(pysp2.testing.EXAMPLE_INI)
+    my_binary = pysp2.util.gaussian_fit(my_sp2b, my_ini, parallel=False)
+    dSdt_norm = pysp2.util.central_difference(my_binary, normalize=True)
+
+    # Test the plotting function for channel 0 and record number 2
+    ax = plot_normalized_derivative(dSdt_norm, record_no=304, chn=0)
+    fig = ax.figure
+    
+    return fig