Mode picture module¶
@author: Sam Schott (ss2151@cam.ac.uk)
(c) Sam Schott; This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 2.0 UK: England & Wales License.
-
experiment.mode_picture_dataset.lorentz_peak(x, x0, w, a)[source]¶ Lorentzian with area a, full-width-at-half-maximum w, and center x0.
-
class
experiment.mode_picture_dataset.ModePicture(input_path_or_data, freq=9.385, metadata=None)[source]¶ Class to store mode pictures. It provides methods to calculate Q-values, and save and load mode picture data from and to .txt files.
If several mode pictures with different zoom factors are given,
ModePicturewill rescale and combine the data into a single mode picture.Parameters: Variables: - x_data_mhz – Numpy array with x-axis data of mode picture in MHz.
- x_data_points – Numpy array with x-axis data of mode picture in pts.
- y_data – Mode picture y-axis data (absorption of cavity).
- freq0 – Center frequency of cavity resonance.
- qvalue – Fitted Q-Value.
- qvalue_stderr – Standard error of Q-Value from fitting.
-
combine_data(mode_pic_data)[source]¶ Rescales mode pictures from different zoom factors and combines them to one.
Parameters: mode_pic_data (dict) – Dict with zoom factors as keys and respective mode picture curves as values. Returns: (x_axis_mhz_comb, x_axis_points_comb, mode_pic_comb) where x_axis_mhz_comb and x_axis_points_comb are the combined x-axis values of all mode pictures in mhz and points, respectively, and mode_pic_comb is the combines y-axis data in a.u..
-
fit_qvalue(x_data, y_data, zoom_factor=1)[source]¶ Least square fit of Lorentzian and polynomial background to mode picture.
Parameters: - x_data – Iterable containing x-data of mode picture in points.
- y_data – Iterable containing y-data of mode picture in a.u..
- zoom_factor – Zoom factor (scaling factor of x-axis).
Returns: (q_value, fit_result) where fit_result is a
-
get_qvalue_stderr()[source]¶ Determines 1 sigma confidence bounds for Q-value.
Returns: Standard error of Q-value from fitting. Return type: float
-
plot()[source]¶ Plots mode picture and the least squares fit used to determine the Q-value. Requires matplotlib.