ecg_plot and rsp_plot don't return fig

docs/examples/custom.ipynb

@@ -81,7 +81,7 @@
     "signals, info = nk.ecg_process(ecg, sampling_rate=1000)\n",
     "\n",
     "# Visualize\n",
-    "plot = nk.ecg_plot(signals)"
+    "nk.ecg_plot(signals)"
    ]
   },
   {
@@ -158,7 +158,7 @@
     "signals, info = my_processing(ecg)\n",
     "\n",
     "# Visualize\n",
-    "plot = nk.ecg_plot(signals)"
+    "nk.ecg_plot(signals)"
    ]
   },
   {
@@ -299,7 +299,7 @@
    ],
    "source": [
     "signals, info = my_processing(ecg)\n",
-    "plot = nk.ecg_plot(signals)"
+    "nk.ecg_plot(signals)"
    ]
   },
   {

docs/readme/README_examples.py

@@ -94,7 +94,7 @@
 nk.ecg_plot(signals, sampling_rate=250)
 
 # Save it
-plot = nk.ecg_plot(signals, sampling_rate=250)
+nk.ecg_plot(signals, sampling_rate=250)
 plt.tight_layout()
 plot.savefig("README_ecg.png", dpi=300)
 
@@ -112,7 +112,7 @@
 nk.rsp_plot(signals, sampling_rate=250)
 
 # Save it
-plot = nk.rsp_plot(signals, sampling_rate=250)
+nk.rsp_plot(signals, sampling_rate=250)
 plt.tight_layout()
 plt.savefig("README_rsp.png", dpi=300)
 

docs_readthedocs/examples/custom.ipynb

@@ -81,7 +81,7 @@
     "signals, info = nk.ecg_process(ecg, sampling_rate=1000)\n",
     "\n",
     "# Visualize\n",
-    "plot = nk.ecg_plot(signals)"
+    "nk.ecg_plot(signals)"
    ]
   },
   {
@@ -158,7 +158,7 @@
     "signals, info = my_processing(ecg)\n",
     "\n",
     "# Visualize\n",
-    "plot = nk.ecg_plot(signals)"
+    "nk.ecg_plot(signals)"
    ]
   },
   {
@@ -299,7 +299,7 @@
    ],
    "source": [
     "signals, info = my_processing(ecg)\n",
-    "plot = nk.ecg_plot(signals)"
+    "nk.ecg_plot(signals)"
    ]
   },
   {

docs_readthedocs/readme/README_examples.py

@@ -94,7 +94,7 @@
 nk.ecg_plot(signals, sampling_rate=250)
 
 # Save it
-plot = nk.ecg_plot(signals, sampling_rate=250)
+nk.ecg_plot(signals, sampling_rate=250)
 plt.tight_layout()
 plot.savefig("README_ecg.png", dpi=300)
 
@@ -112,7 +112,7 @@
 nk.rsp_plot(signals, sampling_rate=250)
 
 # Save it
-plot = nk.rsp_plot(signals, sampling_rate=250)
+nk.rsp_plot(signals, sampling_rate=250)
 plt.tight_layout()
 plt.savefig("README_rsp.png", dpi=300)
 

docs_wip/examples/bio_custom/bio_custom.ipynb

@@ -83,7 +83,7 @@
     "signals, info = nk.ecg_process(ecg, sampling_rate=1000)\n",
     "\n",
     "# Visualize\n",
-    "plot = nk.ecg_plot(signals)"
+    "nk.ecg_plot(signals)"
    ]
   },
   {
@@ -160,7 +160,7 @@
     "signals, info = my_processing(ecg)\n",
     "\n",
     "# Visualize\n",
-    "plot = nk.ecg_plot(signals)"
+    "nk.ecg_plot(signals)"
    ]
   },
   {
@@ -305,7 +305,7 @@
    ],
    "source": [
     "signals, info = my_processing(ecg)\n",
-    "plot = nk.ecg_plot(signals)"
+    "nk.ecg_plot(signals)"
    ]
   },
   {

docs_wip/examples/bio_intervalrelated/bio_intervalrelated.ipynb

@@ -125,7 +125,7 @@
     "# Process ecg\n",
     "ecg_signals, info = nk.ecg_process(data[\"ECG\"], sampling_rate=100)\n",
     "\n",
-    "plot = nk.ecg_plot(ecg_signals[:3000], sampling_rate=100)"
+    "nk.ecg_plot(ecg_signals[:3000], sampling_rate=100)"
    ]
   },
   {

docs_wip/readme/README_examples.py

@@ -94,7 +94,7 @@
 nk.ecg_plot(signals, sampling_rate=250)
 
 # Save it
-plot = nk.ecg_plot(signals, sampling_rate=250)
+nk.ecg_plot(signals, sampling_rate=250)
 plt.tight_layout()
 plot.savefig("README_ecg.png", dpi=300)
 
@@ -112,7 +112,7 @@
 nk.rsp_plot(signals, sampling_rate=250)
 
 # Save it
-plot = nk.rsp_plot(signals, sampling_rate=250)
+nk.rsp_plot(signals, sampling_rate=250)
 plt.tight_layout()
 plt.savefig("README_rsp.png", dpi=300)
 

neurokit2/ecg/ecg_plot.py

@@ -177,5 +177,3 @@ def ecg_plot(ecg_signals, rpeaks=None, sampling_rate=None, show_type="default"):
         fig = signal_fixpeaks(
             rpeaks, sampling_rate=sampling_rate, iterative=True, show=True, method="Kubios"
         )
-
-    return fig

neurokit2/rsp/rsp_plot.py

@@ -7,35 +7,35 @@
 def rsp_plot(rsp_signals, sampling_rate=None):
     """**Visualize respiration (RSP) data**
 
-        Parameters
-        ----------
-        rsp_signals : DataFrame
-            DataFrame obtained from :func:`.rsp_process`.
-        sampling_rate : int
-            The desired sampling rate (in Hz, i.e., samples/second).
+    Parameters
+    ----------
+    rsp_signals : DataFrame
+        DataFrame obtained from :func:`.rsp_process`.
+    sampling_rate : int
+        The desired sampling rate (in Hz, i.e., samples/second).
 
-        Examples
-        --------
-        .. ipython:: python
+    Examples
+    --------
+    .. ipython:: python
 
-          import neurokit2 as nk
+      import neurokit2 as nk
 
-          rsp = nk.rsp_simulate(duration=90, respiratory_rate=15)
-          rsp_signals, info = nk.rsp_process(rsp, sampling_rate=1000)
+      rsp = nk.rsp_simulate(duration=90, respiratory_rate=15)
+      rsp_signals, info = nk.rsp_process(rsp, sampling_rate=1000)
 
-          @savefig p_rsp_plot1.png scale=100%
-          fig = nk.rsp_plot(rsp_signals)
-          @suppress
-          plt.close()
+      @savefig p_rsp_plot1.png scale=100%
+      fig = nk.rsp_plot(rsp_signals)
+      @suppress
+      plt.close()
 
-        Returns
-        -------
-        fig
-            Figure representing a plot of the processed rsp signals.
+    Returns
+    -------
+    fig
+        Figure representing a plot of the processed rsp signals.
 
-        See Also
-        --------
-        rsp_process
+    See Also
+    --------
+    rsp_process
 
     """
     # Mark peaks, troughs and phases.
@@ -125,9 +125,6 @@ def rsp_plot(rsp_signals, sampling_rate=None):
         ax2.axhline(y=amplitude_mean, label="Mean", linestyle="--", color="#009688")
         ax2.legend(loc="upper right")
 
-    # plt.show()
-    return fig
-
 
 # =============================================================================
 # Internals