from comet_ml.api import API, APIExperiment
from config import comet_ml_key
comet_api = API(api_key=comet_ml_key)
for key in ["405", "301", "1000"]:
exps = comet_api.get_experiments(
"ericzhao28",
project_name="active-label-shift-adaptation",
pattern=".*" + key + ".*")
for exp in exps:
if exp.get_metadata()["archived"]:
continue
if key in exp.get_name():
print(exp.get_name())
x = comet_api.get("ericzhao28/active-label-shift-adaptation/" +
exp.get_metadata()["experimentKey"])
for asset in x.get_asset_list():
assetid = asset["assetId"]
print(asset["fileName"])
if "csv" not in asset["fileName"]:
continue
with open("../data/" + exp.get_name() + ".csv", "w") as f:
f.write(exp.get_asset(asset_id=assetid,
return_type="text"))
class fetcher:
'''
An Interface for fetching experiment results through comet API.
Example
-------
>>> y = fetcher(project=["crossa-wheat-env-0", "crossa-wheat-env-1"])
>>> results = y.get_results(parameters = ["run_arg_9", "model", "coding"])
'''
def __init__(self, workspace="dna-i", project=None):
'''
Initializes API key and optionally which workspace and projects to use
Parameters
----------
workspace : STR, optional
Comet workspace. The default is "dna-i".
project : list(STR), optional
List of Projects to use. The default is None.
Returns
-------
None.
'''
self.workspace = workspace
self.project = project
self.api = API(api_key="V0OXnWOi4KVNS4OkwLjdnxSgK")
def get_all_projects(self, workspace="dna-i"):
'''
Gets and prints all available projects.
Parameters
----------
workspace : STR, optional
The default is "dna-i".
Returns
-------
LIST(STR)
available projects
'''
self.available_projects = self.api.get(workspace)
print(self.available_projects)
return self.available_projects
def get_all_experiments(self, project=None):
'''
Fetches all experiments for a given project
Parameters
----------
project : STR, optional
The default is None.
Returns
-------
COMET EXPERIMENT OBJ
'''
if project is not None:
self.experiments = self.api.get(f"{self.workspace}/{project}")
print("fetching experiments")
else:
experiment = []
for proj in self.available_projects:
elem = {'project': proj,
'experiments':self.api.get(f"{self.workspace}/{proj}")}
experiment.append(elem)
self.experiments = experiment
return self.experiments
def get_exp_keys(self):
'''
Converts list of comet experiment objects to experiment keys.
Returns
-------
list of str
'''
self.keys = []
print("fetching experiment keys")
for exp in self.experiments:
self.keys.append(exp.get_metadata()['experimentKey'])
return self.keys
def result_to_df(self):
'''
Converts list of dictionaries result created with get_results to
human friendly to a pandas dataframe.
Returns
-------
DataFrame
'''
r = []
for p in self.results:
result = p["metrics"]
project = p["project"]
for k,v in result.items():
d = {}
d["database"] = project
d['experimentKey']=v["experimentKey"]
d = {**d, **v['params']}
for metric in v["metrics"]:
d['metricName']= metric["metricName"]
for value, step in zip(metric["values"], metric["epochs"]):
aux= { **d, 'value': value,'step': step,}
r.append(aux)
self.results = pd.DataFrame(r)
def get_results(self, metrics=["r_test (r)", "mse_test", "r_train (r)",
"mse_train", "r_test (r)_mean", "mse_test_mean"],
parameters=["model", "coding"], project=None):
'''
Fetches experiment metrics and parameters
Parameters
----------
metrics : LIST(STR), optional
Which metrics to retrieve. The default is ["r_test (r)", "mse_test", "r_train (r)", "mse_train", "r_test (r)_mean", "mse_test_mean"].
parameters : LIST(STR), optional
Which param to retrieve. The default is ["model", "coding"].
project : LIST(STR), optional
Which projects to retriever data from. The default is None.
Returns
-------
Pandas dataframe with results
'''
print(f"Fetching {metrics} and {parameters}")
if project is None:
project = self.project
self.results = []
for proj in project:
print(f"Project {proj}")
self.get_all_experiments(project=proj)
self.get_exp_keys()
value = self.api.get_metrics_for_chart(self.keys, full=True, metrics = metrics, parameters=parameters)
self.results.append({"project": proj, "metrics":value })
self.result_to_df()
return self.results
from comet_ml.api import API, APIExperiment
from config import comet_ml_key
comet_api = API(api_key=comet_ml_key)
for key in ["405", "301", "1000"]:
exps = comet_api.get_experiments(
"qasimwani",
project_name="active-label-shift-adaptation",
pattern=".*" + key + ".*")
for exp in exps:
if exp.get_metadata()["archived"]:
continue
if key in exp.get_name():
print(exp.get_name())
x = comet_api.get("qasimwani/active-label-shift-adaptation/" + exp.get_metadata()["experimentKey"])
for asset in x.get_asset_list():
assetid = asset["assetId"]
print(asset["fileName"])
if "csv" not in asset["fileName"]:
continue
with open("../data/" + exp.get_name() + ".csv", "w") as f:
f.write(exp.get_asset(asset_id=assetid, return_type="text"))