as I the example you gave-
hyper_parameters=[
UniformParameterRange('rep', min_value=0.1, max_value=0.9, step_size=0.05),
UniformParameterRange('coupling', min_value=0.1, max_value=0.6, step_size=0.05),
],

Thanks! What about the objective_metric_title and objective_metric_series? Are they also defined as hyperparameters? Or rather artifacts?

import numpy as np

import matplotlib.pyplot as plt

from clearml import Task, Logger

task = Task.init(project_name="my_task",task_name="try")

interaction = np.random.rand(100,100)
plt.figure()
plt.imshow(np.abs(interaction))
plt.title('interaction (near field)')
plt.colorbar()
plt.show(block=True)

interaction = np.random.rand(100,100)
plt.figure()
plt.imshow(np.abs(interaction))
plt.title('interaction (far field)')
plt.colorbar()
plt.show(block=True)

task.execute_remotely(queue_name='a...

and if I use matrices which are larger than some value, then the following code doesn't work (i.e no plot appears):

import numpy as np

import matplotlib.pyplot as plt

from clearml import Task, Logger

task = Task.init(project_name="my_task",task_name="try")

interaction = np.random.rand(1200,1200)
Logger.current_logger().report_confusion_matrix(
title="interaction (near field)",
series="ignored",
matrix=np.abs(interaction),
xaxis="X",
yaxis="Y",
)

task.execut...