Update app.py

app.py

@@ -18,7 +18,7 @@ def gen_pulsive_noise(count, min_val, max_val):
         pulse = random.randint(min_val, max_val)
     
     return pulse
-def simulation(input_noise, output_noise, min_val, max_val, kp, ki):
+def simulation(input_noise, output_noise, min, max, std, mean, min_pul, max_pul, kp, ki):
     vrs = {}
     fmu = 'Pharmacokinetics_4_comportmental_model_PI_ref_FMU_base4_OAAS_lnx.fmu'
     model_description = read_model_description(fmu)
@@ -73,7 +73,7 @@ def simulation(input_noise, output_noise, min_val, max_val, kp, ki):
 
         bis = fmu.getReal([int(vr_output)])[0] if time > step_size else 95.6
         if input_noise:
-            bis += add_noise(5, 10, 2, 7)
+            bis += add_noise(min, max, std, mean)
         p = bis - target
         i = i + p
         infusion_rate = np.clip(kp*p + ki*i, 0, 200)
@@ -114,13 +114,18 @@ with gr.Blocks() as demo:
     with gr.Row():
         with gr.Column(scale=1):
             gr.Markdown("**BIS noise**")
-            input_noise = gr.inputs.Checkbox(label="Add noise")
+            input_noise = gr.inputs.Checkbox(label="Add Gaussian noise")
+            with gr.Accordion("noise range"):
+                    min = gr.inputs.Slider(minimum=0, maximum=20, step=1, default=5, label="noise min")
+                    max = gr.inputs.Slider(minimum=0, maximum=20, step=1, default=10, label="noise max")
+                    std = gr.inputs.Slider(minimum=0, maximum=10, step=1, default=2, label="noise standard deviation")
+                    mean = gr.inputs.Slider(minimum=0, maximum=20, step=1, default=7, label="noise mean")
             gr.Markdown("**Infusion noise**")
             with gr.Blocks():
-                output_noise = gr.inputs.Checkbox(label="Add noise")
+                output_noise = gr.inputs.Checkbox(label="Add Pulsive noise")
                 with gr.Accordion("noise range"):
-                    min_slider = gr.inputs.Slider(minimum=0, maximum=50, step=1, default=50, label="noise min")
-                    max_slider = gr.inputs.Slider(minimum=0, maximum=150, step=1, default=150, label="noise max")
+                    min_pul = gr.inputs.Slider(minimum=0, maximum=50, step=1, default=50, label="noise min")
+                    max_pul = gr.inputs.Slider(minimum=0, maximum=150, step=1, default=150, label="noise max")
             gr.Markdown("**PI controller paramters**")
             with gr.Blocks():
                 kp_slider = gr.inputs.Slider(minimum=0, maximum=19, default=4, label="kp")
@@ -129,5 +134,5 @@ with gr.Blocks() as demo:
         with gr.Column(scale=5):
             plot1 = gr.Plot(label="BIS evolution")
             plot2 = gr.Plot(label="Infusion evolution")
-    button.click(simulation, inputs=[input_noise, output_noise, min_slider, max_slider, kp_slider, ki_slider], outputs=[plot1, plot2])
+    button.click(simulation, inputs=[input_noise, output_noise, min, max, std, mean, min_slider, max_slider, kp_slider, ki_slider], outputs=[plot1, plot2])
 demo.launch()