def plot_heatmap(acc_list, algorithm, param1_space, param2_space):
"""plot heatmap of accuracy with regard to different hyperparameters
Parameters
-------------
acc_list: a matrix with the values of f1-scores to plot in a heatmap with param1_space and param2_space on the axis
algorithm: either "lle" or "tsne"
param1_space: the most important hyperparam and linear data. lle -> number of neighbors, tsne -> perplexity
param2_space: the less important hyperparam and logistic data. lle -> regularization, tsne -> min_grad_norm
"""
fig, ax = plt.subplots(figsize=(10, 8))
ax = sns.heatmap(acc_list,
cmap="YlGnBu_r",
ax=ax,
cbar_kws={'label': 'F1-score'})
if algorithm == "lle":
ax.set_xlabel("Regularization term (R)")
ax.set_ylabel("Number of Neighbors (K)")
elif algorithm == "tsne":
ax.set_xlabel("Tolerance (tol)")
ax.set_ylabel("Perplexity (Perp)")
ax.set_xticklabels(HL.round_array(param2_space), rotation=90)
ax.set_yticklabels(param1_space, rotation=0)
plt.tight_layout()
plt.savefig("images/MNIST_heatmap_" + algorithm)
plt.show()
def __str__(self):
msg = "RUN "+str(self.run_id)+"\n"
msg += "seed: "+str(self.seed)
msg += "\n\n\n##### BEST TEAM METRICS PER VALIDATION"
msg += "\n\nBest Team Fitness per Validation: "+str(round_array(self.train_score_per_validation))
msg += "\n\nBest Team Validation Score per Validation (champion): "+str(round_array(self.test_score_per_validation))
msg += "\n\nBest Team Recall per Action per Validation: "+str(self.recall_per_validation)
msg += "\n\n\n##### GLOBAL METRICS PER VALIDATION"
msg += "\n\nGlobal Mean Fitness Score per Validation: "+str(self.global_mean_fitness_score_per_validation)
msg += "\n\nGlobal Max. Fitness Score per Validation: "+str(self.global_max_fitness_score_per_validation)
msg += "\n\nGlobal Mean Validation Score per Validation: "+str(self.global_mean_validation_score_per_validation)
msg += "\n\nGlobal Max. Validation Score per Validation: "+str(self.global_max_validation_score_per_validation)
if len(Config.RESTRICTIONS['used_diversities']) > 0:
msg += "\n\nGlobal Diversities per Validation"
for key in self.global_diversity_per_validation:
msg += "\n"+str(key)+": "+str(self.global_diversity_per_validation[key])
msg += "\n\n\n##### DISTRIBUTION METRICS PER VALIDATION"
msg += "\n\nDistribution of Actions per Validation: "+str(self.actions_distribution_per_validation)
msg += "\n\nDistribution of Inputs per Validation (per instruction): "+str(self.inputs_distribution_per_instruction_per_validation)
msg += "\n\nDistribution of Inputs per Validation (per team): "+str(self.inputs_distribution_per_team_per_validation)
msg += "\n\n\n##### METRICS FOR SIZES PER VALIDATION"
msg += "\n\nMean Team Sizes: "+str(self.mean_team_size_per_validation)
msg += "\n\nMean Program Sizes (with introns): "+str(self.mean_program_size_with_introns_per_validation)
msg += "\n\nMean Program Sizes (without introns): "+str(self.mean_program_size_without_introns_per_validation)
msg += "\n\n\n##### GLOBAL METRICS PER TRAINING"
msg += "\n\nGlobal Mean Fitness Score per Training: "+str(self.global_mean_fitness_per_generation)
msg += "\n\nGlobal Max. Fitness Score per Training: "+str(self.global_max_fitness_per_generation)
msg += "\n\nGlobal Fitness Score per Training (per diversity):"
if len(Config.RESTRICTIONS['used_diversities']) > 1:
for key in self.global_fitness_per_diversity_per_generation:
msg += "\n"+str(key)+": "+str(self.global_fitness_per_diversity_per_generation[key])
if len(Config.RESTRICTIONS['used_diversities']) > 0:
msg += "\n\nGlobal Diversities per Training"
for key in self.global_diversity_per_generation:
msg += "\n"+str(key)+": "+str(self.global_diversity_per_generation[key])
if len(Config.RESTRICTIONS['used_diversities']) > 1:
msg += "\n\nDiversity Type per Training: "+str(self.novelty_type_per_generation)
return msg
def __str__(self):
msg = "RUN " + str(self.run_id) + "\n"
msg += "seed: " + str(self.seed)
msg += "\n\n\n\n#################### General Metrics:"
msg += "\n\n\n##### GLOBAL METRICS PER VALIDATION"
msg += "\n\nChampion Fitness per Validation: " + str(
round_array(self.train_score_per_validation_))
msg += "\nChampion Score per Validation: " + str(
round_array(self.champion_score_per_validation_))
if len(Config.USER['advanced_training_parameters']['diversity']
['metrics']) > 0:
msg += "\n\nGlobal Diversities per Validation"
for key in self.global_diversity_per_validation_:
msg += "\n - " + str(key) + ": " + str(
self.global_diversity_per_validation_[key])
msg += "\n\n\n##### GLOBAL METRICS PER TRAINING"
msg += "\n\nGlobal Mean Fitness Score per Training: " + str(
self.global_mean_fitness_per_generation_)
msg += "\nGlobal Max. Fitness Score per Training: " + str(
self.global_max_fitness_per_generation_)
if len(Config.USER['advanced_training_parameters']['diversity']
['metrics']) > 1:
msg += "\n\n\nGlobal Fitness Score per Training (per diversity):"
for key in self.global_fitness_per_diversity_per_generation_:
msg += "\n - " + str(key) + ": " + str(
self.global_fitness_per_diversity_per_generation_[key])
if len(Config.USER['advanced_training_parameters']['diversity']
['metrics']) > 0:
msg += "\n\nGlobal Diversities per Training"
for key in self.global_diversity_per_generation_:
msg += "\n - " + str(key) + ": " + str(
self.global_diversity_per_generation_[key])
if len(Config.USER['advanced_training_parameters']['diversity']
['metrics']) > 1:
msg += "\n\nDiversity Type per Training: " + str(
self.novelty_type_per_generation_)
msg += "\n\n\n##### DISTRIBUTION METRICS PER VALIDATION"
msg += "\n\nDistribution of Actions"
msg += "\n - last validation: " + str(
self.actions_distribution_per_validation_[-1])
msg += "\n - per validation: " + str(
self.actions_distribution_per_validation_)
msg += "\n\nDistribution of Inputs (per program)"
msg += "\n - last validation: " + str(
self.inputs_distribution_per_instruction_per_validation_[-1])
msg += "\n - per validation: " + str(
self.inputs_distribution_per_instruction_per_validation_)
msg += "\n\nDistribution of Inputs (per team)"
msg += "\n - last validation: " + str(
self.inputs_distribution_per_team_per_validation_[-1])
msg += "\n - per validation: " + str(
self.inputs_distribution_per_team_per_validation_)
msg += "\n\n\n##### SIZE METRICS PER VALIDATION"
msg += "\n\nMean Team Sizes"
msg += "\n - last validation: " + str(
self.mean_team_size_per_validation_[-1])
msg += "\n - per validation: " + str(
self.mean_team_size_per_validation_)
msg += "\n\nMean Program Sizes (with introns)"
msg += "\n - last validation: " + str(
self.mean_program_size_with_introns_per_validation_[-1])
msg += "\n - per validation: " + str(
self.mean_program_size_with_introns_per_validation_)
msg += "\n\nMean Program Sizes (without introns)"
msg += "\n - last validation: " + str(
self.mean_program_size_without_introns_per_validation_[-1])
msg += "\n - per validation: " + str(
self.mean_program_size_without_introns_per_validation_)
msg += self.environment.metrics_.generate_output_for_attributes_for_run_info(
self)
return msg
