Merge pull request #108 from kathryn-baker/demo-fixes

Demo fixes

examples/files/california_config.yml

@@ -0,0 +1,63 @@
+model:
+  kwargs:
+    model_file: examples/files/california_regression.pt
+  model_class: lume_model.pytorch.PyTorchModel
+  model_info: examples/files/california_model_info.json
+  output_format:
+    type: variable
+  requirements:
+    torch: 1.12
+
+input_variables:
+  MedInc:
+    default: 3.7857346534729004
+    range:
+      - 0.4999000132083893
+      - 15.000100135803223
+    type: scalar
+  HouseAge:
+    default: 29.282135009765625
+    range:
+      - 1.0
+      - 52.0
+    type: scalar
+  AveRooms:
+    default: 5.4074907302856445
+    range:
+      - 0.8461538553237915
+      - 141.90908813476562
+    type: scalar
+  AveBedrms:
+    default: 1.1071722507476807
+    range:
+      - 0.375
+      - 34.06666564941406
+    type: scalar
+  Population:
+    default: 1437.0687255859375
+    range:
+      - 3.0
+      - 28566.0
+    type: scalar
+  AveOccup:
+    default: 3.035413980484009
+    range:
+      - 0.692307710647583
+      - 599.7142944335938
+    type: scalar
+  Latitude:
+    default: 35.28323745727539
+    range:
+      - 32.65999984741211
+      - 41.95000076293945
+    type: scalar
+  Longitude:
+    default: -119.11573028564453
+    range:
+      - -124.3499984741211
+      - -114.30999755859375
+    type: scalar
+
+output_variables:
+  MedHouseVal:
+    type: scalar

examples/files/california_epics_config.yml

@@ -0,0 +1,38 @@
+input_variables:
+  MedInc:
+    pvname: MedInc
+    protocol: pva
+    serve: true
+  HouseAge:
+    pvname: HouseAge
+    protocol: pva
+    serve: true
+  AveRooms:
+    pvname: AveRooms
+    protocol: pva
+    serve: true
+  AveBedrms:
+    pvname: AveBedrms
+    protocol: pva
+    serve: true
+  Population:
+    pvname: Population
+    protocol: pva
+    serve: true
+  AveOccup:
+    pvname: AveOccup
+    protocol: pva
+    serve: true
+  Latitude:
+    pvname: Latitude
+    protocol: pva
+    serve: true
+  Longitude:
+    pvname: Longitude
+    protocol: pva
+    serve: true
+output_variables:
+  MedHouseVal:
+    pvname: MedHouseVal
+    protocol: pva
+    serve: true

examples/files/california_model_info.json

@@ -0,0 +1,48 @@
+{
+    "train_input_mins": [
+        0.4999000132083893,
+        1.0,
+        0.8461538553237915,
+        0.375,
+        3.0,
+        0.692307710647583,
+        32.65999984741211,
+        -124.3499984741211
+    ],
+    "train_input_maxs": [
+        15.000100135803223,
+        52.0,
+        141.90908813476562,
+        34.06666564941406,
+        28566.0,
+        599.7142944335938,
+        41.95000076293945,
+        -114.30999755859375
+    ],
+    "model_in_list": [
+        "MedInc",
+        "HouseAge",
+        "AveRooms",
+        "AveBedrms",
+        "Population",
+        "AveOccup",
+        "Latitude",
+        "Longitude"
+    ],
+    "model_out_list": [
+        "MedHouseVal"
+    ],
+    "loc_in": {
+        "MedInc": 0,
+        "HouseAge": 1,
+        "AveRooms": 2,
+        "AveBedrms": 3,
+        "Population": 4,
+        "AveOccup": 5,
+        "Latitude": 6,
+        "Longitude": 7
+    },
+    "loc_out": {
+        "MedHouseVal": 0
+    }
+}

examples/files/california_normalization.json

@@ -0,0 +1,28 @@
+{
+    "x_mean": [
+        3.7857348454995345,
+        29.282134699245518,
+        5.4074908062777505,
+        1.1071723692329019,
+        1437.0687339932165,
+        3.0354138620008504,
+        35.283234587868925,
+        -119.11572989538202
+    ],
+    "x_scale": [
+        1.8973481323832475,
+        12.395369585636528,
+        2.8019995847982195,
+        0.5464532026823882,
+        1141.2672447074444,
+        5.462164977692798,
+        2.026003694993028,
+        1.8325257865272555
+    ],
+    "y_mean": [
+        1.985587451669133
+    ],
+    "y_scale": [
+        1.1218406322612422
+    ]
+}

examples/pytorch/california_client.py

@@ -0,0 +1,89 @@
+from bokeh.io import curdoc
+from bokeh.layouts import column, row
+from bokeh.models import Div, Button
+
+from lume_epics.client.controller import Controller
+from lume_model.utils import variables_from_yaml
+from lume_epics.utils import config_from_yaml
+
+from lume_epics.client.widgets.tables import ValueTable
+from lume_epics.client.widgets.controls import build_sliders
+from lume_epics.client.controller import Controller
+
+# load the model and the variables from LUME model
+with open("examples/files/california_config.yml", "r") as f:
+    input_variables, output_variables = variables_from_yaml(f)
+
+# load the EPICS pv definitions
+with open("examples/files/california_epics_config.yml", "r") as f:
+    epics_config = config_from_yaml(f)
+
+# create controller from epics config
+controller = Controller(epics_config)
+
+# prepare as list for rendering
+# define the variables that have range to make as sliders
+sliding_variables = [
+    input_var
+    for input_var in input_variables.values()
+    if input_var.value_range[0] != input_var.value_range[1]
+]
+input_variables = list(input_variables.values())
+output_variables = list(output_variables.values())
+
+# define the plots we want to see - sliders for all input values
+# and tables summarising the current state of the inputs and
+# output values
+sliders = build_sliders(sliding_variables, controller)
+input_value_table = ValueTable(input_variables, controller)
+output_value_table = ValueTable(output_variables, controller)
+
+
+title_div = Div(
+    text=f"<b>California Housing Prediction: Last  update {controller.last_update}</b>",
+    style={
+        "font-size": "150%",
+        "color": "#3881e8",
+        "text-align": "center",
+        "width": "100%",
+    },
+)
+
+
+def update_div_text():
+    global controller
+    title_div.text = (
+        f"<b>California Housing Prediction: Last  update {controller.last_update}</b>"
+    )
+
+
+def reset_slider_values():
+    for slider in sliders:
+        slider.reset()
+
+
+slider_reset_button = Button(label="Reset")
+slider_reset_button.on_click(reset_slider_values)
+
+# render
+curdoc().title = "California Housing Prediction"
+curdoc().add_root(
+    column(
+        row(column(title_div, width=600)),
+        row(
+            column(
+                [slider_reset_button] + [slider.bokeh_slider for slider in sliders],
+                width=350,
+            ),
+            column(input_value_table.table, output_value_table.table, width=350),
+        ),
+    ),
+)
+
+# add refresh callbacks to ensure that the values are updated
+# curdoc().add_periodic_callback(image_plot.update, 1000)
+for slider in sliders:
+    curdoc().add_periodic_callback(slider.update, 1000)
+curdoc().add_periodic_callback(update_div_text, 1000)
+curdoc().add_periodic_callback(input_value_table.update, 1000)
+curdoc().add_periodic_callback(output_value_table.update, 1000)

examples/pytorch/california_server.py

@@ -0,0 +1,42 @@
+from lume_epics.epics_server import Server
+from lume_model.utils import model_from_yaml
+from lume_epics.utils import config_from_yaml
+from pathlib import Path
+import json
+from botorch.models.transforms.input import AffineInputTransform
+import torch
+from pprint import pprint
+
+if __name__ == "__main__":
+    # load the model and the variables from LUME model
+    with open("examples/files/california_config.yml", "r") as f:
+        model_class, model_kwargs = model_from_yaml(f, load_model=False)
+
+    # load the EPICS pv definitions
+    with open("examples/files/california_epics_config.yml", "r") as f:
+        epics_config = config_from_yaml(f)
+
+    # load the transformers required for the model
+    with open("examples/files/california_normalization.json", "r") as f:
+        normalizations = json.load(f)
+
+    input_transformer = AffineInputTransform(
+        len(normalizations["x_mean"]),
+        coefficient=torch.tensor(normalizations["x_scale"]),
+        offset=torch.tensor(normalizations["x_mean"]),
+    )
+    output_transformer = AffineInputTransform(
+        len(normalizations["y_mean"]),
+        coefficient=torch.tensor(normalizations["y_scale"]),
+        offset=torch.tensor(normalizations["y_mean"]),
+    )
+
+    # update the model kwargs with the transformers
+    model_kwargs["input_transformers"] = [input_transformer]
+    model_kwargs["output_transformers"] = [output_transformer]
+
+    # start the EPICS server
+    server = Server(model_class, epics_config, model_kwargs=model_kwargs)
+
+    # monitor = False does not loop in main thread
+    server.start(monitor=True)

lume_epics/client/widgets/controls.py

@@ -81,6 +81,9 @@ def update(self):
 
         """
         self.bokeh_slider.value = self.controller.get_value(self.pvname)
+
+    def reset(self):
+        self.bokeh_slider.value = self.variable.default
 
 
 def build_sliders(

lume_epics/epics_pva_server.py

@@ -117,14 +117,16 @@ def update_pv(self, pvname: str, value: Union[np.ndarray, float]) -> None:
         varname = self._pvname_to_varname_map[pvname]
         model_variable = self._input_variables[varname]
 
+        # check for already cached variable
+        model_variable = self._cached_values.get(varname, model_variable)
+
         if model_variable.variable_type == "image":
             model_variable.x_min = value.attrib["x_min"]
             model_variable.x_max = value.attrib["x_max"]
             model_variable.y_min = value.attrib["y_min"]
             model_variable.y_max = value.attrib["y_max"]
-
-        # check for already cached variable
-        model_variable = self._cached_values.get(varname, model_variable)
+        else:
+            model_variable.value = value
 
         self._cached_values[varname] = model_variable
 
@@ -178,7 +180,6 @@ def setup_server(self) -> None:
                 ].default
 
             else:
-
                 if self._context is None:
                     self._context = Context("pva")
 
@@ -198,7 +199,6 @@ def setup_server(self) -> None:
         self._initialize_model()
         model_outputs = None
         while not self.shutdown_event.is_set() and model_outputs is None:
-
             try:
                 model_outputs = self._out_queue.get(timeout=0.1)
             except Empty:
@@ -224,14 +224,11 @@ def setup_server(self) -> None:
             self._structures = {}
             self._structure_specs = {}
             for variable_name, config in self._epics_config.items():
-
                 if config["serve"]:
-
                     fields = config.get("fields")
                     pvname = config.get("pvname")
 
                     if fields is not None:
-
                         spec = []
                         structure = {}
 
@@ -255,7 +252,6 @@ def setup_server(self) -> None:
                                 spec.append((field, "v"))
                                 table_rep = ()
                                 for col in variable.columns:
-
                                     # here we assume double type in tables...
                                     table_rep += (col, "ad")
 
@@ -320,7 +316,6 @@ def setup_server(self) -> None:
                         elif variable.variable_type == "table":
                             table_rep = ()
                             for col in variable.columns:
-
                                 # here we assume double type in tables...
                                 table_rep += (col, "ad")