Curie temperature¶

Curie temperature.

Find Curie temperature from magnetization vs temperature measurement.

physicslab.experiment.curie_temperature.process(data)[source]¶

Bundle method.

Parameter data must include temperature and magnetization. See Columns for details and column names.

Supplying None for data returns pandas.Series of the same columns with values being units.

Parameters: data (pandas.DataFrame) – Measured data. If None, return units instead
Returns: Derived quantities listed in Columns.process() or units
Return type: pandas.Series

class physicslab.experiment.curie_temperature.Columns[source]¶

Column names.

classmethod mandatory()[source]¶

Get the current values of the mandatory column names.

classmethod process()[source]¶

Get the current values of the process() output column names.

class physicslab.experiment.curie_temperature.Measurement(data)[source]¶

Magnetization vs temperature measurement.

Parameters: data (pandas.DataFrame) – Magnetization and temperature data.
Raises: ValueError – If data is missing a mandatory column

analyze(p0=None)[source]¶

Find Curie temperature.

Parameters: p0 (tuple, optional) – Initial guess of spontaneous magnetization curve parameters. If None, the parameters will be estimated automatically, defaults to None
Returns: Curie temperature
Return type: float

fit(T, M, p0=None, high_temperature_focus=False)[source]¶

Fit spontaneous magnetization curve to the data.

Save the fit into Columns.HIGHTEMPERATUREFIT.

Parameters

T (numpy.ndarray) – Temperature
M (numpy.ndarray) – Magnetization
p0 (tuple, optional) – Initial guess of spontaneous magnetization curve parameters. If None, the parameters will be estimated automatically, defaults to None
high_temperature_focus (bool, optional) – Give high temperature data more weight, defaults to False

Returns

Curie temperature, fit

Return type

tuple(float, numpy.ndarray)

physicslab.experiment.curie_temperature.plot(data_list)[source]¶

Simple plot data and fit for all measurement at once.