Removing plot generators

entropylab/pipeline/api/data_writer.py

@@ -3,10 +3,7 @@
 from datetime import datetime
 from typing import Any
 
-import matplotlib
-from bokeh.models import Renderer
-from bokeh.plotting import Figure
-from matplotlib.figure import Figure as matplotlibFigure
+from matplotlib.figure import Figure
 from plotly import graph_objects as go
 
 
@@ -75,48 +72,6 @@ class Debug:
     extra: str
 
 
-class PlotGenerator(ABC):
-    """
-    An abstract class for plots.
-    Implementations of this class will let Entropy to save and view plots.
-    Every implementation can either implement all plotting functions
-    (within the different environments), or just part of it.
-    """
-
-    def __init__(self) -> None:
-        super().__init__()
-
-    @abstractmethod
-    def plot_bokeh(self, figure: Figure, data, **kwargs) -> Renderer:
-        """
-            plot the given data within the Bokeh Figure
-        :param figure: Bokeh figure to plot in
-        :param data: plot data
-        :param kwargs: extra parameters for plotting
-        """
-        pass
-
-    @abstractmethod
-    def plot_matplotlib(self, figure: matplotlibFigure, data, **kwargs):
-        """
-            plot the given data within the matplotlib Figure
-        :param figure: matplotlib figure
-        :param data: plot data
-        :param kwargs: extra parameters for plotting
-        """
-        pass
-
-    @abstractmethod
-    def plot_plotly(self, figure: go.Figure, data, **kwargs) -> None:
-        """
-            plot the given data within the plot.ly Figure
-        :param figure: plot.ly figure
-        :param data: plot data
-        :param kwargs: extra parameters for plotting
-        """
-        pass
-
-
 @dataclass
 class NodeData:
     """
@@ -182,9 +137,7 @@ def save_figure(self, experiment_id: int, figure: go.Figure) -> None:
         """
         pass
 
-    def save_matplotlib_figure(
-        self, experiment_id: int, figure: matplotlib.figure.Figure
-    ) -> None:
+    def save_matplotlib_figure(self, experiment_id: int, figure: Figure) -> None:
         """
             saves a new matplotlib figure to the db (as a base64-encoded string
             representation of a PNG image) and associates it with an experiment

entropylab/pipeline/tests/test_async_graph.py

@@ -1,7 +1,6 @@
 import asyncio
 
 import numpy as np
-from bokeh.plotting import Figure
 
 from entropylab.pipeline.graph_experiment import (
     Graph,
@@ -136,11 +135,6 @@ def test_async_graph():
 
     results = graph.run().results
     print(results.get_experiment_info())
-    plots = results.get_plots()
-    for plot in plots:
-        figure = Figure()
-        plot.generator.plot_bokeh(figure, plot.plot_data)
-        # save(figure, f"try{plot.label}.html")
 
 
 def test_async_graph_run_to_node():

entropylab/pipeline/tests/test_executor.py

@@ -1,11 +1,10 @@
 from datetime import datetime
 
 import pytest
+from plotly import express as px
 
-from entropylab.pipeline.api.data_writer import PlotSpec
-from entropylab.pipeline.api.execution import EntropyContext
-from entropylab.pipeline.api.plot import CirclePlotGenerator, LinePlotGenerator
 from entropylab.components.lab_topology import LabResources, ExperimentResources
+from entropylab.pipeline.api.execution import EntropyContext
 from entropylab.pipeline.results_backend.sqlalchemy.db import SqlAlchemyDB
 from entropylab.pipeline.script_experiment import Script, script_experiment
 from entropylab.pipeline.tests.mock_instruments import MockScope
@@ -64,14 +63,10 @@ def an_experiment_with_plot(experiment: EntropyContext):
         experiment.add_result("b_result" + str(i), b1 + i + datetime.now().microsecond)
 
     micro = datetime.now().microsecond
-    experiment.add_plot(
-        PlotSpec(
-            label="plot",
-            story="created this plot in experiment",
-            generator=CirclePlotGenerator,
-        ),
-        data=[
-            [
+
+    experiment.add_figure(
+        px.scatter(
+            x=[
                 1 * micro,
                 2 * micro,
                 3 * micro,
@@ -81,20 +76,15 @@ def an_experiment_with_plot(experiment: EntropyContext):
                 7 * micro,
                 8 * micro,
             ],
-            [0, 1, 2, 3, 4, 5, 6, 7],
-        ],
+            y=[0, 1, 2, 3, 4, 5, 6, 7],
+        )
     )
 
-    experiment.add_plot(
-        PlotSpec(
-            label="another plot",
-            story="just showing off now",
-            generator=LinePlotGenerator,
-        ),
-        data=[
-            [1, 2, 3, 4, 5, 6, 7, 8],
-            [4, 5, 6, 7, 0, 1, 2, 3],
-        ],
+    experiment.add_figure(
+        px.line(
+            x=[1, 2, 3, 4, 5, 6, 7, 8],
+            y=[4, 5, 6, 7, 0, 1, 2, 3],
+        )
     )
 
 

entropylab/pipeline/tests/test_graph.py

@@ -1,14 +1,9 @@
 import asyncio
-import os
 from time import sleep
 
 import pytest
-from bokeh.io import save
-from bokeh.plotting import Figure
 
-from entropylab.pipeline.api.data_writer import PlotSpec
 from entropylab.pipeline.api.execution import EntropyContext
-from entropylab.pipeline.api.plot import CirclePlotGenerator
 from entropylab.pipeline.graph_experiment import (
     Graph,
     PyNode,
@@ -52,10 +47,6 @@ def d(x, y):
 async def e(y, z, context: EntropyContext):
     print(f"Node e resting for {y / z}")
     print(f"e Result: {y + z}")
-    context.add_plot(
-        PlotSpec(CirclePlotGenerator, "the best plot"),
-        data=[[0, 1, 2, 3, 4, 5], [y + z, 7, 6, 20, 10, 11]],
-    )
     return {"y_z": [0, 1, 2, 3, 4, 5, y + z, 7, 6, 20, 10, 11]}
 
 
@@ -147,14 +138,6 @@ def test_sync_graph():
 
     results = Graph(None, g, "run_a").run().results
     print(results.get_experiment_info())
-    # TODO: Use figures instead of plots here
-    plots = results.get_plots()
-    for plot in plots:
-        figure = Figure()
-        plot.generator.plot_bokeh(figure, plot.plot_data)
-        if not os.path.exists("tests_cache"):
-            os.mkdir("tests_cache")
-        save(figure, f"tests_cache/bokeh-exported-{plot.label}.html")
 
 
 def test_sync_graph_run_to_node():