<jupyter_start><jupyter_text>QuickstartExamples to get you up and running in no time.<jupyter_code># imports
from modeltestSDK import Client

# configurations
%matplotlib notebook

# initiate client with defaults
client = Client()
# list available campaigns
campaigns = client.campaign.get()
# have a look at the data (using Pandas here)
campaigns.to_pandas()
# which tests were carried out for White Pearl? (it is the first campaign in the list above)
campaign = campaigns[0]
tests = campaign.tests()
tests.to_pandas().head() # just list the first ones
# you can also do it as `campaigns[0].tests().to_pandas()`
# and the sensor setup?
sensors = campaign.sensors()
sensors.to_pandas().head(n=20) # just list the first 20.
# let's have a closer look at the surge decay tests (the third in the above list)
# and the surge motion ("XPOS_WL")
test = tests[3]
test.timeseries(sensor_id="d9a51897-3511-462a-bb92-d2cc2b368e1d").plot()<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.10334029227557412, 'fraction_numerical': 0.029227557411273485, 'mean_word_length': 5.523809523809524, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '612292', 'license': 'MIT', 'n_tokens_mistral': 332, 'n_tokens_neox': 305, 'n_words': 109, 'path': 'examples/quickstart.ipynb', 'repo_name': 'SevanSSP/inquire-modeltest-sdk', 'size': '958'}