solve numpy error, add colors options

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

@@ -1,11 +1,30 @@
 # coding: utf-8
 
 colors = {
-    "mpl_standard": [
+    "mpl": [
         "#1f77b4", "#ff7f0e", "#2ca02c", "#d62728", "#9467bd", "#8c564b", "#e377c2", "#7f7f7f", "#bcbd22", "#17becf",
     ],
-    "custom_edgecolor": ["#CC4F1B", "#1B2ACC", "#3F7F4C"],
-    "custom_facecolor": ["#FF9848", "#089FFF", "#7EFF99"],
+    # Atlas and cms standards correspond to results in :
+    # Color wheel from https://arxiv.org/pdf/2107.02270 Table 1, 10 color palette
+    # hexacodes in https://github.com/mpetroff/accessible-color-cycles/blob/0a17e754d9f83161baffd803dcea8bee7d95a549/readme.md#final-results # noqa
+    # as implemented in mplhep
+    "cms_6": [
+        "#5790fc", "#f89c20", "#e42536", "#964a8b", "#9c9ca1", "#7a21dd",
+    ],
+    "atlas_10": [
+        "#3f90da",
+        "#ffa90e",
+        "#bd1f01",
+        "#94a4a2",
+        "#832db6",
+        "#a96b59",
+        "#e76300",
+        "#b9ac70",
+        "#717581",
+        "#92dadd",
+    ],
+    # "custom_edgecolor": ["#CC4F1B", "#1B2ACC", "#3F7F4C"],
+    # "custom_facecolor": ["#FF9848", "#089FFF", "#7EFF99"],
 }
 
 
@@ -86,7 +105,7 @@ def fill_plot(x, y, y_down, y_up, error_style, color):
     if error_style == "band":
         p1 = plt.plot(x, y, "-", color=color)
         plt.fill_between(x, y - y_down, y + y_up, alpha=0.5, facecolor=color)
-        p2 = plt.fill(np.NaN, np.NaN, alpha=0.5, color=color)
+        p2 = plt.fill(np.nan, np.nan, alpha=0.5, color=color)
         legend = (p1[0], p2[0])
     else:  # bars
         p = plt.errorbar(x, y, yerr=(y_down, y_up), capsize=12, marker=".", linestyle="")
@@ -100,6 +119,7 @@ def plot_batch_size_several_measurements(
     input_paths,
     output_path,
     measurements,
+    color_list,
     plot_params,
 ):
     """
@@ -114,6 +134,7 @@ def plot_batch_size_several_measurements(
     """
     import matplotlib.pyplot as plt
     import mplhep  # type: ignore[import-untyped]
+    from cycler import cycler
 
     if isinstance(measurements[0], str):
         measurements_labels_strs = list(measurements)
@@ -136,14 +157,19 @@ def plot_batch_size_several_measurements(
 
         # create plot with curves using a single color for each value-error pair
         legend_entries = []
-        for data in plot_data:
+        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("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()
             entry = fill_plot(
                 x=batch_sizes,
                 y=data["y"],
                 y_down=data["y_down"],
                 y_up=data["y_up"],
                 error_style=plot_params["error_style"],
-                color=ax._get_lines.get_next_color(),
+                color=color_used,
             )
             legend_entries.append(entry)
 

mlprof/tasks/parameters.py

@@ -211,6 +211,7 @@ class MultiModelParameters(BaseTask):
         description="when set, use these labels in plots; 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",
+        brace_expand=True,
     )
 
     def __init__(self, *args, **kwargs):
@@ -312,6 +313,13 @@ class CustomPlotParameters(BaseTask):
         significant=False,
         description="stick a label over the top right corner of the plot",
     )
+    default_colors = luigi.ChoiceParameter(
+        choices=["mpl", "cms_6", "atlas_10"],
+        default="cms_6",
+        significant=False,
+        description="default color cycle to use; choices: 'mpl', 'cms_6', 'atlas_10'"
+        "; default: 'cms_6'",
+    )
 
     @property
     def custom_plot_params(self):
@@ -323,4 +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,
+            "default_colors": self.default_colors,
         }

mlprof/tasks/runtime.py

@@ -150,6 +150,7 @@ def run(self):
             [self.input().path],
             output.path,
             [self.model.full_model_label],
+            [self.model.color],
             self.custom_plot_params,
         )
         print("plot saved")
@@ -280,5 +281,6 @@ def run(self):
             input_paths=input_paths,
             output_path=output.path,
             measurements=self.params_product_params_to_write,
+            color_list=[model.color for model in self.models],
             plot_params=self.custom_plot_params,
         )

mlprof/util.py

@@ -26,6 +26,7 @@ def __init__(self, model_file: str, name: str, label: str, **kwargs) -> None:
         self.model_file = expand_path(model_file, abs=True)
         self.name = name
         self.label = label
+        self._color = None
 
         # cached data
         self._all_data = None
@@ -67,3 +68,9 @@ def full_model_label(self):
 
         # fallback to the full model name
         return self.full_name
+
+    @property
+    def color(self):
+        if self._color is None:
+            self._color = self.data.get("color")
+        return self._color

sandboxes/plotting.txt

@@ -1,6 +1,6 @@
-# version 1
+# version 2
 
-numpy
-pandas
-matplotlib
-mplhep
+numpy~=2.0.1
+pandas~=2.2.2
+matplotlib~=3.9.0
+mplhep~=0.3.50