Feature/Visualise Plots in Experiment Tracking

RELEASE.md

@@ -8,6 +8,7 @@ Please follow the established format:
 
 ## Major features and improvements
 
+- Allow the visualisation of Matplotlib and Plotly plots in experiment tracking. (#984)
 - Remove support for Kedro v16. (#998)
 
 # Release 4.7.2

demo-project/conf/base/catalog_08_reporting.yml

@@ -8,14 +8,16 @@ reporting.cancellation_policy_breakdown:
       x: company_location
       y: price
       color: cancellation_policy
-      log_y: True
+      log_y: true
       labels:
         price: 'fleet_price'
+  versioned: true
 
 reporting.price_histogram:
   type: plotly.JSONDataSet # Constructed via Python API
   filepath: ${base_location}/08_reporting/price_histogram.json
   layer: reporting
+  versioned: true
 
 reporting.cancellation_policy_grid:
   type: demo_project.extras.datasets.image_dataset.ImageDataSet
@@ -24,3 +26,4 @@ reporting.cancellation_policy_grid:
 reporting.matplotlib_image:
   type: matplotlib.MatplotlibWriter
   filepath: ${base_location}/08_reporting/matplot_lib_single_plot.png
+  versioned: true

demo-project/data/08_reporting/cancellation_breakdown.json/2022-07-20T15.39.58.437Z/cancellation_breakdown.json

@@ -0,0 +1 @@
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demo-project/data/08_reporting/cancellation_breakdown.json/2022-07-21T12.54.06.759Z/cancellation_breakdown.json

@@ -0,0 +1 @@
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demo-project/data/09_tracking/linear_params.json/2022-07-20T15.39.58.437Z/linear_params.json

@@ -0,0 +1,6 @@
+{
+  "model_type": "LinearRegression",
+  "fit_intercept": true,
+  "copy_X": true,
+  "positive": false
+}

demo-project/data/09_tracking/linear_params.json/2022-07-21T12.54.06.759Z/linear_params.json

@@ -0,0 +1,6 @@
+{
+  "model_type": "LinearRegression",
+  "fit_intercept": true,
+  "copy_X": true,
+  "positive": false
+}

demo-project/data/09_tracking/linear_params.json/2022-07-22T13.49.08.764Z/linear_params.json

@@ -0,0 +1,6 @@
+{
+  "model_type": "LinearRegression",
+  "fit_intercept": true,
+  "copy_X": true,
+  "positive": false
+}

demo-project/data/09_tracking/linear_score.json/2022-07-20T15.39.58.437Z/linear_score.json

@@ -0,0 +1,3 @@
+{
+  "r2_score": 0.40296896595214116
+}

demo-project/data/09_tracking/linear_score.json/2022-07-21T12.54.06.759Z/linear_score.json

@@ -0,0 +1,3 @@
+{
+  "r2_score": 0.40296896595214116
+}

demo-project/data/09_tracking/linear_score.json/2022-07-22T13.49.08.764Z/linear_score.json

@@ -0,0 +1,3 @@
+{
+  "r2_score": 0.40296896595214116
+}

demo-project/data/09_tracking/rf_params.json/2022-07-20T15.39.58.437Z/rf_params.json

@@ -0,0 +1,15 @@
+{
+  "model_type": "RandomForestRegressor",
+  "n_estimators": 100,
+  "criterion": "squared_error",
+  "min_samples_split": 2,
+  "min_samples_leaf": 1,
+  "min_weight_fraction_leaf": 0,
+  "max_features": "auto",
+  "min_impurity_decrease": 0,
+  "bootstrap": true,
+  "oob_score": false,
+  "verbose": 0,
+  "warm_start": false,
+  "ccp_alpha": 0
+}

demo-project/data/09_tracking/rf_params.json/2022-07-21T12.54.06.759Z/rf_params.json

@@ -0,0 +1,15 @@
+{
+  "model_type": "RandomForestRegressor",
+  "n_estimators": 100,
+  "criterion": "squared_error",
+  "min_samples_split": 2,
+  "min_samples_leaf": 1,
+  "min_weight_fraction_leaf": 0,
+  "max_features": "auto",
+  "min_impurity_decrease": 0,
+  "bootstrap": true,
+  "oob_score": false,
+  "verbose": 0,
+  "warm_start": false,
+  "ccp_alpha": 0
+}

demo-project/data/09_tracking/rf_params.json/2022-07-22T13.49.08.764Z/rf_params.json

@@ -0,0 +1,15 @@
+{
+  "model_type": "RandomForestRegressor",
+  "n_estimators": 100,
+  "criterion": "squared_error",
+  "min_samples_split": 2,
+  "min_samples_leaf": 1,
+  "min_weight_fraction_leaf": 0,
+  "max_features": "auto",
+  "min_impurity_decrease": 0,
+  "bootstrap": true,
+  "oob_score": false,
+  "verbose": 0,
+  "warm_start": false,
+  "ccp_alpha": 0
+}