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Haiqu.log(parent_ctx: CircuitModel | QuantumCircuit | Any = None, child_ctx: Any = None, name: str = None, description: str = None) → str | CircuitModel

Record data to the Haiqu cloud based on the context (e.g., circuit, or any other relevant information). This method functions similarly to a generic logger, in the same vein as the log method of the Weights & Biases Python SDK for machine learning.
  • Parameters:
    • parent_ctx — The input object to be logged.
    • child_ctx — An optional child object, linked to the context of the parent.
    • name — An optional name for the logged object.
    • description — An optional description if logging a circuit.
  • Returns: Status message, circuit metadata.
  • Return type: str | CircuitModel

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Examples

If used without parameters, haiqu.log() displays the nice widget with help. Try it out: 
>>> haiqu.log()
This function always acts in the context of the current experiment. If the circuit metadata object (CircuitModel) is passed as the first argument, it will log data to that circuit.

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Log metrics

>>> haiqu.log(12.34, name="Some value")
>>> haiqu.log("Hello quantum world!", name="Some textual value")
>>> haiqu.log([1, 2, 3], name="Experiment parameters")
>>> # W&B style:
>>> haiqu.log({"examples": ["one", "two", "three"]})
>>> haiqu.log({"some_value": 12.34, "some_text": "Quantum!", "parameters": [1, 2, 3]})

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Log a circuit

>>> from qiskit.circuit.random import random_circuit
>>> qc = random_circuit(num_qubits=4, depth=1, max_operands=4, measure=True)
>>> meta = haiqu.log(qc)
>>> # or with name/description:
>>> meta = haiqu.log(qc, name="Hello", description="World!")
>>> # log artifact/metric to the circuit:
>>> haiqu.log(meta, 42)

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Log the Matplotlib plt object

>>> import matplotlib.pyplot as plt
>>> plt.plot([1, 2, 3], [4, 5, 6], label="Label")
>>> haiqu.log(plt, name="Awesome plot")
>>> # or W&B style:
>>> # haiqu.log({"chart": plt})

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Log the Pandas DataFrame

>>> import pandas as pd
>>> data = {
>>>     "columns": [0, 1, 2],
>>>     "data": [50, 40, 45]
>>> }
>>> df = pd.DataFrame(data)
>>> haiqu.log(df, name="My DataFrame")

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Log the Drawer plot

>>> from haiqu.sdk.wiz.drawer import Drawer
>>> drawer = Drawer()
>>> drawer.plot([1, 2, 3], [4, 5, 6])
>>> haiqu.log(drawer, name="Cool drawer plot")

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Log the Matplotlib figure

>>> import matplotlib.pyplot as plt

>>> fig, ax = plt.subplots()
>>> ax.plot([1, 2, 3], [4, 5, 6], label="Test Plot")
>>> ...
>>> haiqu.log(fig, name="Awesome figure")
You can see logged data on Dashboard: https://dashboard.haiqu.ai