Upload app.py

app.py

@@ -427,149 +427,149 @@ def infer_chest_cf(*args):
 
 with gr.Blocks(theme=gr.themes.Default()) as demo:
     with gr.Tabs():
-        with gr.TabItem("Morpho-MNIST") as mnist_tab:
-            mnist_id = gr.Textbox(value=mnist_tab.label, visible=False)
-
-            with gr.Row(): #.style(equal_height=True):
-                idx = gr.Number(value=0, visible=False)
-                with gr.Column(scale=1, min_width=200):
-                    x = gr.Image(label="Observation", interactive=False, height=HEIGHT) #.style(
-                        #height=HEIGHT
-                    #)
-                with gr.Column(scale=1, min_width=200):
-                    cf_x = gr.Image(label="Counterfactual", interactive=False, height=HEIGHT) #).style(
-                        # height=HEIGHT
-                    # )
-                with gr.Column(scale=1, min_width=200):
-                    cf_x_std = gr.Image(
-                        label="Counterfactual Uncertainty", interactive=False
-                    , height=HEIGHT) #).style(height=HEIGHT)
-                with gr.Column(scale=1, min_width=200):
-                    effect = gr.Image(
-                        label="Direct Causal Effect", interactive=False
-                    , height=HEIGHT) #).style(height=HEIGHT)
-            with gr.Row(): #.style(equal_height=True):
-                with gr.Column(scale=1):#.75):
-                    gr.Markdown(
-                        "**Intervention**"
-                        + 20 * " "
-                        + "[arXiv paper](https://arxiv.org/abs/2306.15764)   |   [GitHub code](https://github.com/biomedia-mira/causal-gen)"
-                        + "  |   Hint: try 90% zoom"
-                    )
-                    with gr.Column():
-                        do_y = gr.Checkbox(label="do(digit)", value=False)
-                        y = gr.Radio(DIGITS, label="", interactive=False)
-                        with gr.Row():
-                            with gr.Column(min_width=100):
-                                do_t = gr.Checkbox(label="do(thickness)", value=False)
-                                t = gr.Slider(
-                                    label="\u00A0",
-                                    minimum=0.9,
-                                    maximum=5.5,
-                                    step=0.01,
-                                    interactive=False,
-                                )
-                            with gr.Column(min_width=100):
-                                do_i = gr.Checkbox(label="do(intensity)", value=False)
-                                i = gr.Slider(
-                                    label="\u00A0",
-                                    minimum=50,
-                                    maximum=255,
-                                    step=0.01,
-                                    interactive=False,
-                                )
-                    with gr.Row():
-                        new = gr.Button("New Observation")
-                        reset = gr.Button("Reset", variant="stop")
-                        submit = gr.Button("Submit", variant="primary")
-                with gr.Column(scale=1):
-                    gr.Markdown("###  ")
-                    causal_graph = gr.Image(
-                        label="Causal Graph", interactive=False
-                    , height=300) #).style(height=300)
-
-        with gr.TabItem("Brain MRI") as brain_tab:
-            brain_id = gr.Textbox(value=brain_tab.label, visible=False)
-
-            with gr.Row(): #.style(equal_height=True):
-                idx_brain = gr.Number(value=0, visible=False)
-                with gr.Column(scale=1, min_width=200):
-                    x_brain = gr.Image(label="Observation", interactive=False, height=HEIGHT) #).style(
-                        # height=HEIGHT
-                    # )
-                with gr.Column(scale=1, min_width=200):
-                    cf_x_brain = gr.Image(
-                        label="Counterfactual", interactive=False
-                    , height=HEIGHT) #).style(height=HEIGHT)
-                with gr.Column(scale=1, min_width=200):
-                    cf_x_std_brain = gr.Image(
-                        label="Counterfactual Uncertainty", interactive=False
-                    , height=HEIGHT) #).style(height=HEIGHT)
-                with gr.Column(scale=1, min_width=200):
-                    effect_brain = gr.Image(
-                        label="Direct Causal Effect", interactive=False
-                    , height=HEIGHT) #).style(height=HEIGHT)
-            with gr.Row():
-                with gr.Column(scale=2):#.55):
-                    gr.Markdown(
-                        "**Intervention**"
-                        + 20 * " "
-                        + "[arXiv paper](https://arxiv.org/abs/2306.15764)   |   [GitHub code](https://github.com/biomedia-mira/causal-gen)"
-                        + "  |   Hint: try 90% zoom"
-                    )
-                    with gr.Row():
-                        with gr.Column(min_width=200):
-                            do_m = gr.Checkbox(label="do(MRI sequence)", value=False)
-                            m = gr.Radio(
-                                ["T1", "T2-FLAIR"], label="", interactive=False
-                            )
-                        with gr.Column(min_width=200):
-                            do_s = gr.Checkbox(label="do(sex)", value=False)
-                            s = gr.Radio(
-                                ["female", "male"], label="", interactive=False
-                            )
-                    with gr.Row():
-                        with gr.Column(min_width=100):
-                            do_a = gr.Checkbox(label="do(age)", value=False)
-                            a = gr.Slider(
-                                label="\u00A0",
-                                value=50,
-                                minimum=44,
-                                maximum=73,
-                                step=1,
-                                interactive=False,
-                            )
-                        with gr.Column(min_width=100):
-                            do_b = gr.Checkbox(label="do(brain volume)", value=False)
-                            b = gr.Slider(
-                                label="\u00A0",
-                                value=1000,
-                                minimum=850,
-                                maximum=1550,
-                                step=20,
-                                interactive=False,
-                            )
-                        with gr.Column(min_width=100):
-                            do_v = gr.Checkbox(
-                                label="do(ventricle volume)", value=False
-                            )
-                            v = gr.Slider(
-                                label="\u00A0",
-                                value=40,
-                                minimum=10,
-                                maximum=125,
-                                step=2,
-                                interactive=False,
-                            )
-                    with gr.Row():
-                        new_brain = gr.Button("New Observation")
-                        reset_brain = gr.Button("Reset", variant="stop")
-                        submit_brain = gr.Button("Submit", variant="primary")
-                with gr.Column(scale=1):
-                    # gr.Markdown("###  ")
-                    causal_graph_brain = gr.Image(
-                        label="Causal Graph", interactive=False
-                    , height=340) #).style(height=340)
+        # with gr.TabItem("Morpho-MNIST") as mnist_tab:
+        #     mnist_id = gr.Textbox(value=mnist_tab.label, visible=False)
+        #
+        #     with gr.Row(): #.style(equal_height=True):
+        #         idx = gr.Number(value=0, visible=False)
+        #         with gr.Column(scale=1, min_width=200):
+        #             x = gr.Image(label="Observation", interactive=False, height=HEIGHT) #.style(
+        #                 #height=HEIGHT
+        #             #)
+        #         with gr.Column(scale=1, min_width=200):
+        #             cf_x = gr.Image(label="Counterfactual", interactive=False, height=HEIGHT) #).style(
+        #                 # height=HEIGHT
+        #             # )
+        #         with gr.Column(scale=1, min_width=200):
+        #             cf_x_std = gr.Image(
+        #                 label="Counterfactual Uncertainty", interactive=False
+        #             , height=HEIGHT) #).style(height=HEIGHT)
+        #         with gr.Column(scale=1, min_width=200):
+        #             effect = gr.Image(
+        #                 label="Direct Causal Effect", interactive=False
+        #             , height=HEIGHT) #).style(height=HEIGHT)
+        #     with gr.Row(): #.style(equal_height=True):
+        #         with gr.Column(scale=1):#.75):
+        #             gr.Markdown(
+        #                 "**Intervention**"
+        #                 + 20 * " "
+        #                 + "[arXiv paper](https://arxiv.org/abs/2306.15764)   |   [GitHub code](https://github.com/biomedia-mira/causal-gen)"
+        #                 + "  |   Hint: try 90% zoom"
+        #             )
+        #             with gr.Column():
+        #                 do_y = gr.Checkbox(label="do(digit)", value=False)
+        #                 y = gr.Radio(DIGITS, label="", interactive=False)
+        #                 with gr.Row():
+        #                     with gr.Column(min_width=100):
+        #                         do_t = gr.Checkbox(label="do(thickness)", value=False)
+        #                         t = gr.Slider(
+        #                             label="\u00A0",
+        #                             minimum=0.9,
+        #                             maximum=5.5,
+        #                             step=0.01,
+        #                             interactive=False,
+        #                         )
+        #                     with gr.Column(min_width=100):
+        #                         do_i = gr.Checkbox(label="do(intensity)", value=False)
+        #                         i = gr.Slider(
+        #                             label="\u00A0",
+        #                             minimum=50,
+        #                             maximum=255,
+        #                             step=0.01,
+        #                             interactive=False,
+        #                         )
+        #             with gr.Row():
+        #                 new = gr.Button("New Observation")
+        #                 reset = gr.Button("Reset", variant="stop")
+        #                 submit = gr.Button("Submit", variant="primary")
+        #         with gr.Column(scale=1):
+        #             gr.Markdown("###  ")
+        #             causal_graph = gr.Image(
+        #                 label="Causal Graph", interactive=False
+        #             , height=300) #).style(height=300)
+        #
+        # with gr.TabItem("Brain MRI") as brain_tab:
+        #     brain_id = gr.Textbox(value=brain_tab.label, visible=False)
+        #
+        #     with gr.Row(): #.style(equal_height=True):
+        #         idx_brain = gr.Number(value=0, visible=False)
+        #         with gr.Column(scale=1, min_width=200):
+        #             x_brain = gr.Image(label="Observation", interactive=False, height=HEIGHT) #).style(
+        #                 # height=HEIGHT
+        #             # )
+        #         with gr.Column(scale=1, min_width=200):
+        #             cf_x_brain = gr.Image(
+        #                 label="Counterfactual", interactive=False
+        #             , height=HEIGHT) #).style(height=HEIGHT)
+        #         with gr.Column(scale=1, min_width=200):
+        #             cf_x_std_brain = gr.Image(
+        #                 label="Counterfactual Uncertainty", interactive=False
+        #             , height=HEIGHT) #).style(height=HEIGHT)
+        #         with gr.Column(scale=1, min_width=200):
+        #             effect_brain = gr.Image(
+        #                 label="Direct Causal Effect", interactive=False
+        #             , height=HEIGHT) #).style(height=HEIGHT)
+        #     with gr.Row():
+        #         with gr.Column(scale=2):#.55):
+        #             gr.Markdown(
+        #                 "**Intervention**"
+        #                 + 20 * " "
+        #                 + "[arXiv paper](https://arxiv.org/abs/2306.15764)   |   [GitHub code](https://github.com/biomedia-mira/causal-gen)"
+        #                 + "  |   Hint: try 90% zoom"
+        #             )
+        #             with gr.Row():
+        #                 with gr.Column(min_width=200):
+        #                     do_m = gr.Checkbox(label="do(MRI sequence)", value=False)
+        #                     m = gr.Radio(
+        #                         ["T1", "T2-FLAIR"], label="", interactive=False
+        #                     )
+        #                 with gr.Column(min_width=200):
+        #                     do_s = gr.Checkbox(label="do(sex)", value=False)
+        #                     s = gr.Radio(
+        #                         ["female", "male"], label="", interactive=False
+        #                     )
+        #             with gr.Row():
+        #                 with gr.Column(min_width=100):
+        #                     do_a = gr.Checkbox(label="do(age)", value=False)
+        #                     a = gr.Slider(
+        #                         label="\u00A0",
+        #                         value=50,
+        #                         minimum=44,
+        #                         maximum=73,
+        #                         step=1,
+        #                         interactive=False,
+        #                     )
+        #                 with gr.Column(min_width=100):
+        #                     do_b = gr.Checkbox(label="do(brain volume)", value=False)
+        #                     b = gr.Slider(
+        #                         label="\u00A0",
+        #                         value=1000,
+        #                         minimum=850,
+        #                         maximum=1550,
+        #                         step=20,
+        #                         interactive=False,
+        #                     )
+        #                 with gr.Column(min_width=100):
+        #                     do_v = gr.Checkbox(
+        #                         label="do(ventricle volume)", value=False
+        #                     )
+        #                     v = gr.Slider(
+        #                         label="\u00A0",
+        #                         value=40,
+        #                         minimum=10,
+        #                         maximum=125,
+        #                         step=2,
+        #                         interactive=False,
+        #                     )
+        #             with gr.Row():
+        #                 new_brain = gr.Button("New Observation")
+        #                 reset_brain = gr.Button("Reset", variant="stop")
+        #                 submit_brain = gr.Button("Submit", variant="primary")
+        #         with gr.Column(scale=1):
+        #             # gr.Markdown("###  ")
+        #             causal_graph_brain = gr.Image(
+        #                 label="Causal Graph", interactive=False
+        #             , height=340) #).style(height=340)
 
         with gr.TabItem("Chest X-ray") as chest_tab:
             chest_id = gr.Textbox(value=chest_tab.label, visible=False)
@@ -647,47 +647,53 @@ with gr.Blocks(theme=gr.themes.Default()) as demo:
     cf_out_chest = [cf_x_chest, cf_x_std_chest, effect_chest]
 
     # on start: load new observations & causal graph
-    demo.load(fn=get_mnist_obs, inputs=None, outputs=obs)
-    demo.load(fn=mnist_graph, inputs=do, outputs=causal_graph)
-    demo.load(fn=load_model, inputs=mnist_id, outputs=None)
-    demo.load(fn=get_brain_obs, inputs=None, outputs=obs_brain)
+    # demo.load(fn=get_mnist_obs, inputs=None, outputs=obs)
+    # demo.load(fn=mnist_graph, inputs=do, outputs=causal_graph)
+    # demo.load(fn=load_model, inputs=mnist_id, outputs=None)
+    # demo.load(fn=get_brain_obs, inputs=None, outputs=obs_brain)
+    # demo.load(fn=get_chest_obs, inputs=None, outputs=obs_chest)
+
     demo.load(fn=get_chest_obs, inputs=None, outputs=obs_chest)
+    demo.load(fn=load_model, inputs=chest_id, output=None)
+
 
-    demo.load(fn=brain_graph, inputs=do_brain, outputs=causal_graph_brain)
+    # demo.load(fn=brain_graph, inputs=do_brain, outputs=causal_graph_brain)
     demo.load(fn=chest_graph, inputs=do_chest, outputs=causal_graph_chest)
 
     # on tab select: load models
-    brain_tab.select(fn=load_model, inputs=brain_id, outputs=None)
-    chest_tab.select(fn=load_model, inputs=chest_id, outputs=None)
+    # brain_tab.select(fn=load_model, inputs=brain_id, outputs=None)
+    # chest_tab.select(fn=load_model, inputs=chest_id, outputs=None)
 
     # "new" button: load new observations
-    new.click(fn=get_mnist_obs, inputs=None, outputs=obs)
+    # new.click(fn=get_mnist_obs, inputs=None, outputs=obs)
     new_chest.click(fn=get_chest_obs, inputs=None, outputs=obs_chest)
-    new_brain.click(fn=get_brain_obs, inputs=None, outputs=obs_brain)
+    # new_brain.click(fn=get_brain_obs, inputs=None, outputs=obs_brain)
 
     # "new" button: reset causal graphs
-    new.click(fn=mnist_graph, inputs=do, outputs=causal_graph)
-    new_brain.click(fn=brain_graph, inputs=do_brain, outputs=causal_graph_brain)
+    # new.click(fn=mnist_graph, inputs=do, outputs=causal_graph)
+    # new_brain.click(fn=brain_graph, inputs=do_brain, outputs=causal_graph_brain)
     new_chest.click(fn=chest_graph, inputs=do_chest, outputs=causal_graph_chest)
 
     # "new" button: reset cf output panels
-    for _k, _v in zip(
-        [new, new_brain, new_chest], [cf_out, cf_out_brain, cf_out_chest]
-    ):
-        _k.click(fn=lambda: (gr.update(value=None),) * 3, inputs=None, outputs=_v)
+    # for _k, _v in zip(
+    #     [new, new_brain, new_chest], [cf_out, cf_out_brain, cf_out_chest]
+    # ):
+    #     _k.click(fn=lambda: (gr.update(value=None),) * 3, inputs=None, outputs=_v)
+    new_chest.click(fn=lambda:(gr.update(value=None),) * 3, inputs=None, outputs=cf_out_chest)
+
 
     # "reset" button: reload current observations
-    reset.click(fn=get_mnist_obs, inputs=idx, outputs=obs)
-    reset_brain.click(fn=get_brain_obs, inputs=idx_brain, outputs=obs_brain)
+    # reset.click(fn=get_mnist_obs, inputs=idx, outputs=obs)
+    # reset_brain.click(fn=get_brain_obs, inputs=idx_brain, outputs=obs_brain)
     reset_chest.click(fn=get_chest_obs, inputs=idx_chest, outputs=obs_chest)
 
     # "reset" button: deselect intervention checkboxes
-    reset.click(fn=lambda: (gr.update(value=False),) * len(do), inputs=None, outputs=do)
-    reset_brain.click(
-        fn=lambda: (gr.update(value=False),) * len(do_brain),
-        inputs=None,
-        outputs=do_brain,
-    )
+    # reset.click(fn=lambda: (gr.update(value=False),) * len(do), inputs=None, outputs=do)
+    # reset_brain.click(
+    #     fn=lambda: (gr.update(value=False),) * len(do_brain),
+    #     inputs=None,
+    #     outputs=do_brain,
+    # )
     reset_chest.click(
         fn=lambda: (gr.update(value=False),) * len(do_chest),
         inputs=None,
@@ -695,21 +701,23 @@ with gr.Blocks(theme=gr.themes.Default()) as demo:
     )
 
     # "reset" button: reset cf output panels
-    for _k, _v in zip(
-        [reset, reset_brain, reset_chest], [cf_out, cf_out_brain, cf_out_chest]
-    ):
-        _k.click(fn=lambda: plt.close("all"), inputs=None, outputs=None)
-        _k.click(fn=lambda: (gr.update(value=None),) * 3, inputs=None, outputs=_v)
-
-    # enable mnist interventions when checkbox is selected & update graph
-    for _k, _v in zip(do, [t, i, y]):
-        _k.change(fn=lambda x: gr.update(interactive=x), inputs=_k, outputs=_v)
-        _k.change(mnist_graph, inputs=do, outputs=causal_graph)
-
-    # enable brain interventions when checkbox is selected & update graph
-    for _k, _v in zip(do_brain, [m, s, a, b, v]):
-        _k.change(fn=lambda x: gr.update(interactive=x), inputs=_k, outputs=_v)
-        _k.change(brain_graph, inputs=do_brain, outputs=causal_graph_brain)
+    # for _k, _v in zip(
+    #     [reset, reset_brain, reset_chest], [cf_out, cf_out_brain, cf_out_chest]
+    # ):
+    #     _k.click(fn=lambda: plt.close("all"), inputs=None, outputs=None)
+    #     _k.click(fn=lambda: (gr.update(value=None),) * 3, inputs=None, outputs=_v)
+    reset_chest.lick(fn=lambda: plt.close("all"), inputs=None, outputs=None)
+    reset_chest.lick(fn=lambda: (gr.update(value=None),) * 3, inputs=None, outputs=cf_out_chest)
+
+    # # enable mnist interventions when checkbox is selected & update graph
+    # for _k, _v in zip(do, [t, i, y]):
+    #     _k.change(fn=lambda x: gr.update(interactive=x), inputs=_k, outputs=_v)
+    #     _k.change(mnist_graph, inputs=do, outputs=causal_graph)
+    #
+    # # enable brain interventions when checkbox is selected & update graph
+    # for _k, _v in zip(do_brain, [m, s, a, b, v]):
+    #     _k.change(fn=lambda x: gr.update(interactive=x), inputs=_k, outputs=_v)
+    #     _k.change(brain_graph, inputs=do_brain, outputs=causal_graph_brain)
 
     # enable chest interventions when checkbox is selected & update graph
     for _k, _v in zip(do_chest, [r_chest, s_chest, f_chest, a_chest]):
@@ -717,12 +725,12 @@ with gr.Blocks(theme=gr.themes.Default()) as demo:
         _k.change(chest_graph, inputs=do_chest, outputs=causal_graph_chest)
 
     # "submit" button: infer countefactuals
-    submit.click(fn=infer_mnist_cf, inputs=obs + do, outputs=cf_out + [t, i, y])
-    submit_brain.click(
-        fn=infer_brain_cf,
-        inputs=obs_brain + do_brain,
-        outputs=cf_out_brain + [m, s, a, b, v],
-    )
+    # submit.click(fn=infer_mnist_cf, inputs=obs + do, outputs=cf_out + [t, i, y])
+    # submit_brain.click(
+    #     fn=infer_brain_cf,
+    #     inputs=obs_brain + do_brain,
+    #     outputs=cf_out_brain + [m, s, a, b, v],
+    # )
     submit_chest.click(
         fn=infer_chest_cf,
         inputs=obs_chest + do_chest,