made UI changes

app.py

@@ -1,11 +1,19 @@
 import streamlit as st, pandas as pd, os, io
 from modeci_mdf.mdf import Model, Graph, Node, Parameter, OutputPort
 from modeci_mdf.utils import load_mdf_json, load_mdf, load_mdf_yaml
-from modeci_mdf.execution_engine import EvaluableGraph
+from modeci_mdf.execution_engine import EvaluableGraph, EvaluableOutput
 import json
-st.set_page_config(layout="wide")
-st.title("🔋 MDF Simulator")
 import requests
+st.set_page_config(layout="wide", page_icon="logo.png", page_title="Model Description Format", menu_items={
+        'Report a bug': "https://github.com/ModECI/MDF/",
+        'About': "ModECI (Model Exchange and Convergence Initiative) is a multi-investigator collaboration that aims to develop a standardized format for exchanging computational models across diverse software platforms and domains of scientific research and technology development, with a particular focus on neuroscience, Machine Learning and Artificial Intelligence. Refer to https://modeci.org/ for more."
+    })
+header1, header2 = st.columns([1,12], vertical_alignment="top")
+with header1:
+    st.image("logo.png", width=100)
+with header2:
+    st.title("Welcome to Model Description Format")
+st.write("Lets get started! Choose one of the following methods.")
 # models: Purpose: To store the state of the model and update the model
 def run_simulation(param_inputs, mdf_model):
     mod_graph = mdf_model.graphs[0]
@@ -14,8 +22,10 @@ def run_simulation(param_inputs, mdf_model):
         parameters = node.parameters
         outputs = node.output_ports
         eg = EvaluableGraph(mod_graph, verbose=False)
+        # eo = EvaluableOutput(mod_graph, verbose=)
         duration = param_inputs["Simulation Duration (s)"]
         dt = param_inputs["Time Step (s)"]
+        print("hi me param_inputs inside run simulation", param_inputs)
         t = 0
         times = []
         output_values = {op.value: [] for op in outputs}
@@ -27,25 +37,27 @@ def run_simulation(param_inputs, mdf_model):
                 eg.evaluate(time_increment=dt)
 
             for param in output_values:
-                eval_param = eg.enodes[node.id].evaluable_parameters[param]
+                if any(operator in param  for operator in "+-/*"):
+                    eval_param = eg.enodes[node.id].evaluable_outputs[param]
+                    
+                else:
+                    eval_param = eg.enodes[node.id].evaluable_parameters[param] 
                 output_values[param].append(eval_param.curr_value)
             t += dt
         chart_data = pd.DataFrame(output_values)
         chart_data['Time'] = times
         chart_data.set_index('Time', inplace=True)
-        return chart_data
-
+        show_simulation_results(chart_data)
+    return None
 # views: Purpose: To display the state of the model 
 def show_simulation_results(chart_data):
     st.line_chart(chart_data, use_container_width=True, height=400)
-    st.write("Output Values")
-    st.write(chart_data)
 
 def show_mdf_graph(mdf_model):
     st.subheader("MDF Graph")
     mdf_model.to_graph_image(engine="dot", output_format="png", view_on_render=False, level=3, filename_root=mdf_model.id, only_warn_on_fail=(os.name == "nt"))
     image_path = mdf_model.id + ".png"
-    st.image(image_path, caption="Model Graph Visualization")
+    st.sidebar.image(image_path, caption="Model Graph Visualization")
 
 def show_json_output(mdf_model):
     st.subheader("JSON Output")
@@ -54,16 +66,16 @@ def show_json_output(mdf_model):
 def view_tabs(mdf_model, param_inputs): # view
     tab1, tab2, tab3 = st.tabs(["Simulation Results", "MDF Graph", "Json Output"])
     with tab1:
-        mod_graph = mdf_model.graphs[0]
-        nodes = mod_graph.nodes
-        for node in nodes:
-            st.write("Node Name: ", node.id)
-            node_parameters = {}
-            for param in node.parameters:
-                node_parameters[param.id] = node_parameters[param.id] = param.value if param.value else param.time_derivative
-            st.write("Node Parameters: ", node_parameters)   
-            chart_data = run_simulation(param_inputs, mdf_model) # model
-            show_simulation_results(chart_data) # view
+        # mod_graph = mdf_model.graphs[0]
+        # nodes = mod_graph.nodes
+        # for node in nodes:
+        #     st.write("Node Name: ", node.id)
+        #     node_parameters = {}
+        #     for param in node.parameters:
+        #         node_parameters[param.id] = node_parameters[param.id] = param.value if param.value else param.time_derivative
+        #     st.write("Node Parameters: ", node_parameters)   
+        run_simulation(param_inputs, mdf_model) # model
+        #     show_simulation_results(chart_data) # view
     with tab2:
         show_mdf_graph(mdf_model) # view
     with tab3:
@@ -72,21 +84,22 @@ def view_tabs(mdf_model, param_inputs): # view
 def parameter_form_to_update_model_and_view(mdf_model, parameters, param_inputs, mod_graph, nodes):
     form = st.form(key="parameter_form")
     valid_inputs = True
-
-    for i, param in enumerate(parameters):
-        if isinstance(param.value, str) or param.value is None:
-            continue  
-        key = f"{param.id}_{i}"
-        if mdf_model.metadata:
-            value = form.text_input(f"{param.metadata.get('description', param.id)} ({param.id})", value=str(param.value), key=key)
-        else:
-            value = form.text_input(f"{param.id}", value=str(param.value), key=key)
-        
-        try:
-            param_inputs[param.id] = float(value)
-        except ValueError:
-            st.error(f"Invalid input for {param.id}. Please enter a valid number.")
-            valid_inputs = False
+    for node_wise_parameter_key, node_wise_parameter in enumerate(parameters):
+        # st.write("hi i am b", node_wise_parameter)
+        for i, param in enumerate(node_wise_parameter):
+            if isinstance(param.value, str) or param.value is None:
+                continue  
+            key = f"{param.id}_{i}"
+            if mdf_model.metadata:
+                value = form.text_input(f"{param.metadata.get('description', param.id)} ({param.id})", value=str(param.value), key=key)
+            else:
+                value = form.text_input(f"{param.id}", value=str(param.value), key=key)
+            
+            try:
+                param_inputs[param.id] = float(value)
+            except ValueError:
+                st.error(f"Invalid input for {param.id}. Please enter a valid number.")
+                valid_inputs = False
 
     sim_duration = form.text_input("Simulation Duration (s)", value=str(param_inputs["Simulation Duration (s)"]), key="sim_duration")
     time_step = form.text_input("Time Step (s)", value=str(param_inputs["Time Step (s)"]), key="time_step")
@@ -105,41 +118,107 @@ def parameter_form_to_update_model_and_view(mdf_model, parameters, param_inputs,
     run_button = form.form_submit_button("Run Simulation")
     if run_button:
         if valid_inputs:
-            for param in parameters:
-                if param.id in param_inputs:
-                    param.value = param_inputs[param.id]
+            for b in parameters:
+                for param in b:
+                    if param.id in param_inputs:
+                        param.value = param_inputs[param.id]
             view_tabs(mdf_model, param_inputs)
         # else:
         #     st.error("Please correct the invalid inputs before running the simulation.")
 
+# def upload_file_and_load_to_model():
+#     st.write("Choose how to load the model:")
+#     load_option = st.radio("", ("Upload File", "GitHub URL", "Example Models"), )
+#     st.write("Choose how to load the model:")
+#     if load_option == "Upload File":
+#         uploaded_file = st.file_uploader("Choose a JSON/YAML/BSON file", type=["json", "yaml", "bson"])
+#         if uploaded_file is not None:
+#             file_content = uploaded_file.getvalue()
+#             file_extension = uploaded_file.name.split('.')[-1].lower()
+#             return load_model_from_content(file_content, file_extension)
+
+#     elif load_option == "GitHub URL":
+#         st.write("sample_github_url = https://raw.githubusercontent.com/ModECI/MDF/development/examples/MDF/NewtonCoolingModel.json")
+#         github_url = st.text_input("Enter GitHub raw file URL:", placeholder="Enter GitHub raw file URL")
+#         if github_url:
+#             try:
+#                 response = requests.get(github_url)
+#                 response.raise_for_status()
+#                 file_content = response.content
+#                 file_extension = github_url.split('.')[-1].lower()
+#                 return load_model_from_content(file_content, file_extension)
+#             except requests.RequestException as e:
+#                 st.error(f"Error loading file from GitHub: {e}")
+#                 return None
+
+#     elif load_option == "Example Models":
+#         example_models = {
+#             "Newton Cooling Model": "https://raw.githubusercontent.com/ModECI/MDF/development/examples/MDF/NewtonCoolingModel.json",
+#             "ABCD": "https://raw.githubusercontent.com/ModECI/MDF/main/examples/MDF/ABCD.json",
+#             "FN": "https://raw.githubusercontent.com/ModECI/MDF/main/examples/MDF/FN.mdf.json",
+#             "States": "https://raw.githubusercontent.com/ModECI/MDF/main/examples/MDF/States.json",
+#             "Other Model 4": "https://example.com/other_model_4.json"
+#         }
+
+#         selected_model = st.selectbox("Choose an example model", list(example_models.keys()))
+#         if selected_model:
+#             example_url = example_models[selected_model]
+#             try:
+#                 response = requests.get(example_url)
+#                 response.raise_for_status()
+#                 file_content = response.content
+#                 file_extension = example_url.split('.')[-1].lower()
+#                 return load_model_from_content(file_content, file_extension)
+#             except requests.RequestException as e:
+#                 st.error(f"Error loading example model: {e}")
+#                 return None
+
+#     st.write("Try out example files:")
+#     return None
 
 def upload_file_and_load_to_model():
-    st.write("Choose how to load the model:")
-    load_option = st.radio("", ("Upload File", "GitHub URL"))
-
-    if load_option == "Upload File":
-        uploaded_file = st.file_uploader("Choose a JSON/YAML/BSON file", type=["json", "yaml", "bson"])
-        if uploaded_file is not None:
-            file_content = uploaded_file.getvalue()
-            file_extension = uploaded_file.name.split('.')[-1].lower()
+    # col1, col2 = st.columns(2)
+    # with col1:
+    uploaded_file = st.file_uploader("Choose a JSON/YAML/BSON file", type=["json", "yaml", "bson"])
+    if uploaded_file is not None:
+        file_content = uploaded_file.getvalue()
+        file_extension = uploaded_file.name.split('.')[-1].lower()
+        return load_model_from_content(file_content, file_extension)
+    github_url = st.text_input("Enter GitHub raw file URL:", placeholder="Enter GitHub raw file URL")
+    if github_url:
+        try:
+            response = requests.get(github_url)
+            response.raise_for_status()
+            file_content = response.content
+            file_extension = github_url.split('.')[-1].lower()
             return load_model_from_content(file_content, file_extension)
-    else:
-        st.write("sample_github_url = https://raw.githubusercontent.com/ModECI/MDF/development/examples/MDF/NewtonCoolingModel.json")
-        github_url = st.text_input("Enter GitHub raw file URL:", placeholder="Enter GitHub raw file URL")
-        if github_url:
-            try:
-                response = requests.get(github_url)
-                response.raise_for_status()
-                file_content = response.content
-            # print(file_content)
-                file_extension = github_url.split('.')[-1].lower()
-                return load_model_from_content(file_content, file_extension)
-            except requests.RequestException as e:
-                st.error(f"Error loading file from GitHub: {e}")
-                return None
-
+        except requests.RequestException as e:
+            st.error(f"Error loading file from GitHub: {e}")
+            return None
+    # with col2:
+    example_models = {
+        "Newton Cooling Model": "https://raw.githubusercontent.com/ModECI/MDF/development/examples/MDF/NewtonCoolingModel.json",
+        "ABCD": "https://raw.githubusercontent.com/ModECI/MDF/main/examples/MDF/ABCD.json",
+        "FN": "https://raw.githubusercontent.com/ModECI/MDF/main/examples/MDF/FN.mdf.json",
+        "States": "https://raw.githubusercontent.com/ModECI/MDF/main/examples/MDF/States.json",
+        "Other Model 4": "https://example.com/other_model_4.json"
+    }
+    selected_model = st.selectbox("Choose an example model", list(example_models.keys()), index=None)
+    if selected_model:
+        example_url = example_models[selected_model]
+        try:
+            response = requests.get(example_url)
+            response.raise_for_status()
+            file_content = response.content
+            file_extension = example_url.split('.')[-1].lower()
+            return load_model_from_content(file_content, file_extension)
+        except requests.RequestException as e:
+            st.error(f"Error loading example model: {e}")
+            return None
+    # st.button("Newton Cooling Model", on_click=load_mdf_json(""))
     return None
 
+
 def load_model_from_content(file_content, file_extension):
     try:
         if file_extension == 'json':
@@ -160,14 +239,14 @@ def load_model_from_content(file_content, file_extension):
 
 
 def main():
-    st.write("Text box changed to input. Github URL is allowed. Added some warnings eg. on adding text in input fields. Now working on multiple parameters allow.")
     mdf_model = upload_file_and_load_to_model() # controller
     if mdf_model:
         mod_graph = mdf_model.graphs[0]
         nodes = mod_graph.nodes
+        parameters = []
         for node in nodes:
-            parameters = node.parameters
-            param_inputs = {}
+            parameters.append(node.parameters)
+        param_inputs = {}
         if mdf_model.metadata:
             preferred_duration = float(mdf_model.metadata.get("preferred_duration", 10))
             preferred_dt = float(mdf_model.metadata.get("preferred_dt", 0.1))

examples/FN.mdf.json

@@ -0,0 +1,140 @@
+{
+    "FN": {
+        "format": "ModECI MDF v0.4",
+        "graphs": {
+            "FN": {
+                "notes": "FitzHugh Nagumo cell model - originally specified in NeuroML/LEMS",
+                "nodes": {
+                    "FNpop": {
+                        "metadata": {
+                            "color": "0.2 0.2 0.2",
+                            "radius": 3,
+                            "region": "region1"
+                        },
+                        "parameters": {
+                            "initial_w": {
+                                "value": [
+                                    0.0
+                                ]
+                            },
+                            "initial_v": {
+                                "value": [
+                                    -1.0
+                                ]
+                            },
+                            "a_v": {
+                                "value": [
+                                    -0.3333333333333333
+                                ]
+                            },
+                            "b_v": {
+                                "value": [
+                                    0.0
+                                ]
+                            },
+                            "c_v": {
+                                "value": [
+                                    1.0
+                                ]
+                            },
+                            "d_v": {
+                                "value": [
+                                    1.0
+                                ]
+                            },
+                            "e_v": {
+                                "value": [
+                                    -1.0
+                                ]
+                            },
+                            "f_v": {
+                                "value": [
+                                    1.0
+                                ]
+                            },
+                            "time_constant_v": {
+                                "value": [
+                                    1.0
+                                ]
+                            },
+                            "a_w": {
+                                "value": [
+                                    1.0
+                                ]
+                            },
+                            "b_w": {
+                                "value": [
+                                    -0.8
+                                ]
+                            },
+                            "c_w": {
+                                "value": [
+                                    0.7
+                                ]
+                            },
+                            "time_constant_w": {
+                                "value": [
+                                    12.5
+                                ]
+                            },
+                            "threshold_exc": {
+                                "value": [
+                                    -1.0
+                                ]
+                            },
+                            "mode": {
+                                "value": [
+                                    1.0
+                                ]
+                            },
+                            "uncorrelated_activity": {
+                                "value": [
+                                    0.0
+                                ]
+                            },
+                            "Iext": {
+                                "value": [
+                                    0.0
+                                ]
+                            },
+                            "MSEC": {
+                                "value": [
+                                    0.001
+                                ]
+                            },
+                            "spike": {
+                                "value": [
+                                    0
+                                ]
+                            },
+                            "V": {
+                                "default_initial_value": "initial_v",
+                                "time_derivative": "(a_v*V*V*V + (1+threshold_exc)*b_v*V*V + (-1*threshold_exc)*c_v*V + d_v + e_v*W + f_v*Iext + INPUT) / (time_constant_v*MSEC)"
+                            },
+                            "W": {
+                                "default_initial_value": "initial_w",
+                                "time_derivative": "(mode*a_w*V + b_w*W + c_w + (1-mode)*uncorrelated_activity) / (time_constant_w*MSEC)"
+                            }
+                        },
+                        "input_ports": {
+                            "INPUT": {}
+                        },
+                        "output_ports": {
+                            "spike": {
+                                "value": "spike"
+                            },
+                            "V": {
+                                "value": "V"
+                            },
+                            "W": {
+                                "value": "W"
+                            }
+                        },
+                        "notes": "Cell: [Cell(notes=None, id='fn', parameters={'initial_w': 'initial_w', 'initial_v': 'initial_v', 'a_v': 'a_v', 'b_v': 'b_v', 'c_v': 'c_v', 'd_v': 'd_v', 'e_v': 'e_v', 'f_v': 'f_v', 'time_constant_v': 'time_constant_v', 'a_w': 'a_w', 'b_w': 'b_w', 'c_w': 'c_w', 'time_constant_w': 'time_constant_w', 'threshold': 'threshold', 'mode': 'mode', 'uncorrelated_activity': 'uncorrelated_activity', 'Iext': 'Iext'}, neuroml2_source_file=None, lems_source_file='FN_Definitions.xml', neuroml2_cell=None, pynn_cell=None, arbor_cell=None, bindsnet_node=None)] is defined in FN_Definitions.xml and in Lems is: Component, id: fn, type: fnCell,\n   parameters: {'initial_w': '0.0', 'initial_v': '-1', 'a_v': '-0.3333333333333333', 'b_v': '0.0', 'c_v': '1.0', 'd_v': '1', 'e_v': '-1.0', 'f_v': '1.0', 'time_constant_v': '1.0', 'a_w': '1.0', 'b_w': '-0.8', 'c_w': '0.7', 'time_constant_w': '12.5', 'threshold_exc': '-1.0', 'mode': '1.0', 'uncorrelated_activity': '0.0', 'Iext': '0'}\n   parent: None\n"
+                    }
+                },
+                "edges": {}
+            }
+        }
+    }
+}

examples/NewtonCoolingModel.json

@@ -0,0 +1,38 @@
+{
+    "NewtonCoolingModel": {
+        "format": "ModECI MDF v0.4",
+        "generating_application": "Python modeci-mdf v0.4.11",
+        "graphs": {
+            "cooling_process": {
+                "nodes": {
+                    "cool_node": {
+                        "parameters": {
+                            "cooling_coeff": {
+                                "value": 0.1
+                            },
+                            "T_a": {
+                                "value": 20
+                            },
+                            "T_curr": {
+                                "default_initial_value": 90,
+                                "time_derivative": "dT_dt"
+                            },
+                            "dT_dt": {
+                                "value": "-cooling_coeff*(T_curr - T_a)",
+                                "default_initial_value": 0
+                            }
+                        },
+                        "output_ports": {
+                            "out_port": {
+                                "value": "T_curr"
+                            },
+                            "out_port2": {
+                                "value": "dT_dt"
+                            }
+                        }
+                    }
+                }
+            }
+        }
+    }
+}

examples/States.json

@@ -0,0 +1,50 @@
+{
+    "States": {
+        "format": "ModECI MDF v0.4",
+        "generating_application": "Python modeci-mdf v0.4.11",
+        "graphs": {
+            "state_example": {
+                "nodes": {
+                    "counter_node": {
+                        "parameters": {
+                            "increment": {
+                                "value": 1
+                            },
+                            "count": {
+                                "value": "count + increment"
+                            }
+                        },
+                        "output_ports": {
+                            "out_port": {
+                                "value": "count"
+                            }
+                        }
+                    },
+                    "sine_node": {
+                        "parameters": {
+                            "amp": {
+                                "value": 3
+                            },
+                            "period": {
+                                "value": 0.4
+                            },
+                            "level": {
+                                "default_initial_value": 0,
+                                "time_derivative": "6.283185 * rate / period"
+                            },
+                            "rate": {
+                                "default_initial_value": 1,
+                                "time_derivative": "-1 * 6.283185 * level / period"
+                            }
+                        },
+                        "output_ports": {
+                            "out_port": {
+                                "value": "amp * level"
+                            }
+                        }
+                    }
+                }
+            }
+        }
+    }
+}

examples/SwitchedRLC_Circuit.json

@@ -0,0 +1,75 @@
+{
+    "SwitchedRLC_Circuit": {
+        "format": "ModECI MDF v0.4",
+        "generating_application": "Python modeci-mdf v0.4.11",
+        "metadata": {
+            "preferred_duration": 2,
+            "preferred_dt": 0.001
+        },
+        "graphs": {
+            "SwitchedRLC_Circuit": {
+                "nodes": {
+                    "V": {
+                        "parameters": {
+                            "Vs": {
+                                "conditions": [
+                                    {
+                                        "id": "off",
+                                        "test": "time<0.5",
+                                        "value": "0"
+                                    },
+                                    {
+                                        "id": "on",
+                                        "test": "time>=0.5",
+                                        "value": 0.1
+                                    }
+                                ]
+                            },
+                            "R": {
+                                "metadata": {
+                                    "description": "Resistance in Ohms"
+                                },
+                                "value": 100
+                            },
+                            "L": {
+                                "metadata": {
+                                    "description": "Inductance in Henrys"
+                                },
+                                "value": 1
+                            },
+                            "C": {
+                                "value": 0.001
+                            },
+                            "time": {
+                                "default_initial_value": 0,
+                                "time_derivative": "1"
+                            },
+                            "V": {
+                                "default_initial_value": 0,
+                                "time_derivative": "i_C /C"
+                            },
+                            "i_R": {
+                                "value": "V / R"
+                            },
+                            "i_L": {
+                                "default_initial_value": 0,
+                                "time_derivative": "(Vs - V)/L"
+                            },
+                            "i_C": {
+                                "value": "i_L-i_R"
+                            }
+                        },
+                        "output_ports": {
+                            "V_out": {
+                                "value": "V"
+                            },
+                            "i_L_out": {
+                                "value": "i_L"
+                            }
+                        }
+                    }
+                }
+            }
+        }
+    }
+}