complete docu and correct name parameter

README.md

@@ -129,6 +129,7 @@ If tensorflow or onnx is to be used as inference engine, the yaml file should be
 model:
   name: optional_default_name_of_the_network_for_the_storage_path
   label: optional default label of the network for the plots
+  color: optional color of the network for the plots
   version: optional_version_number # (e.g. "1.0.0")
   inference_engine: name_of_inference_engine  # (either "tf" or "onnx")
   file: path_to_your_pb_or_onnx_model_file
@@ -153,6 +154,7 @@ Hence, the yaml file should be in the following format:
 model:
   name: optional_default_name_of_the_network_for_the_storage_path
   label: optional default label of the network for the plots
+  color: optional color of the network for the plots
   version: version_number  # (e.g. "1.0.0")
   inference_engine: tfaot
   saved_model: path_to_your_saved_model_directory
@@ -264,7 +266,7 @@ This task merges the .csv output files with the required multiple batch sizes fr
 - The .csv files from the several occurences of `MeasureRuntime` (one for each batch size).
 
 ## Parameters:
-- batch-sizes: int. The comma-separated list of batch sizes to be tested; default: `1,2,4`.
+- batch-sizes: int. The comma-separated list of batch sizes to be tested. default: `1,2,4`.
 
 - model-file: str. The absolute path of the yaml file containing the informations of the model to be tested. default: `$MLP_BASE/examples/dnn/model_tf_l10u128.yaml`.
 
@@ -308,21 +310,23 @@ The number of inferences behind one plotted data point is given by `n-events * n
 - The .csv file from the `MergeRuntimes` task.
 
 ## Parameters:
-- y-log: bool. Plot the y-axis values logarithmically; default: `False`.
+- y-log: bool. Plot the y-axis values logarithmically. default: `False`.
 
-- x-log: bool. Plot the x-axis values logarithmically; default: `False`.
+- x-log: bool. Plot the x-axis values logarithmically. default: `False`.
 
 - y-min = float. Minimum y-axis value. default: empty
 
 - y-max: float. Maximum y-axis value. default: empty
 
-- bs-normalized: bool. Normalize the measured values with the batch size before plotting; default: `True`.
+- bs-normalized: bool. Normalize the measured values with the batch size before plotting. default: `True`.
 
-- error-style: str. Style of errors / uncertainties due to averaging; choices: `bars`,`band`; default: `band`.
+- error-style: str. Style of errors / uncertainties due to averaging. choices: `bars`,`band`. default: `band`.
 
 - top-right-label: str. When set, stick this string as label over the top right corner of the plot. default: empty.
 
-- batch-sizes: int. The comma-separated list of batch sizes to be tested; default: `1,2,4`.
+- default_colors: str. Default color cycle to use for plots. choices: `mpl`, `cms_6`, `atlas_10`. default: `cms_6`.
+
+- batch-sizes: int. The comma-separated list of batch sizes to be tested. default: `1,2,4`.
 
 - model-file: str. The absolute path of the yaml file containing the informations of the model to be tested. default: `$MLP_BASE/examples/dnn/model_tf_l10u128.yaml`.
 
@@ -406,21 +410,23 @@ The number of inferences behind one plotted data point is given by `n-events * n
 
 - model-labels: str. The comma-separated list of model labels. When set, use these strings for the model labels in the plots from the plotting tasks. When empty, the `label` fields in the models yaml data are used when existing, else the `name` fields in the models yaml data are used when existing, and model-names otherwise. default: empty.
 
-- y-log: bool. Plot the y-axis values logarithmically; default: `False`.
+- y-log: bool. Plot the y-axis values logarithmically. default: `False`.
 
-- x-log: bool. Plot the x-axis values logarithmically; default: `False`.
+- x-log: bool. Plot the x-axis values logarithmically. default: `False`.
 
 - y-min = float. Minimum y-axis value. default: empty
 
 - y-max: float. Maximum y-axis value. default: empty
 
-- bs-normalized: bool. Normalize the measured values with the batch size before plotting; default: `True`.
+- bs-normalized: bool. Normalize the measured values with the batch size before plotting. default: `True`.
 
-- error-style: str. Style of errors / uncertainties due to averaging; choices: `bars`,`band`; default: `band`.
+- error-style: str. Style of errors / uncertainties due to averaging. choices: `bars`,`band`. default: `band`.
 
 - top-right-label: str. When set, stick this string as label over the top right corner of the plot. default: empty.
 
-- batch-sizes: int. The comma-separated list of batch sizes to be tested; default: `1,2,4`.
+- default_colors: str. Default color cycle to use for plots. choices: `mpl`, `cms_6`, `atlas_10`. default: `cms_6`.
+
+- batch-sizes: int. The comma-separated list of batch sizes to be tested. default: `1,2,4`.
 
 - n-events: int. The number of events to read from each input file for averaging measurements. default: `1`
 

mlprof/plotting/plotter.py

@@ -157,9 +157,9 @@ def plot_batch_size_several_measurements(
 
         # create plot with curves using a single color for each value-error pair
         legend_entries = []
-        if plot_params.get("custom_colors"):
+        if plot_params.get("default_colors"):
             # set the color cycle to the custom color cycle
-            ax._get_lines.set_prop_cycle(cycler("color", colors[plot_params.get("custom_colors")]))
+            ax._get_lines.set_prop_cycle(cycler("color", colors[plot_params.get("default_colors")]))
 
         for i, data in enumerate(plot_data):
             color_used = color_list[i] if color_list[i] else ax._get_lines.get_next_color()

mlprof/tasks/parameters.py

@@ -313,7 +313,7 @@ class CustomPlotParameters(BaseTask):
         significant=False,
         description="stick a label over the top right corner of the plot",
     )
-    custom_colors = luigi.ChoiceParameter(
+    default_colors = luigi.ChoiceParameter(
         choices=["mpl", "cms_6", "atlas_10"],
         default="cms_6",
         significant=False,
@@ -331,5 +331,5 @@ def custom_plot_params(self):
             "bs_normalized": self.bs_normalized,
             "error_style": self.error_style,
             "top_right_label": None if self.top_right_label == law.NO_STR else self.top_right_label,
-            "custom_colors": self.custom_colors,
+            "default_colors": self.default_colors,
         }