pyepr.Pulse =========== .. py:class:: pyepr.Pulse(*, tp, t=None, scale=None, flipangle=None, pcyc=[0], name=None, **kwargs) Represents a general experimental pulse. The class for a general pulse. :Parameters: **tp** : float The pulse length in ns. **scale** : float The arbitary experimental pulse amplitude, 0-1. **t** : float, optional The pulse start time in ns. .. !! processed by numpydoc !! .. py:attribute:: name .. py:attribute:: Progression :value: False .. py:property:: bandwidth .. py:method:: _addPhaseCycle(phases, detections=None) Adds a phase cycle to the pulse sequence. Args: phases (list): List of phases to add to the phase cycle. detections (list, optional): List of detection signs. Defaults to None. If None then all cycles are summed. Returns: None .. !! processed by numpydoc !! .. py:method:: _buildFMAM(func, ax=None) Builds the amplitude modulation (AM) and frequency modulation (FM) of a given function. Args: func: A function that takes in an array of values and returns two arrays, representing the AM and FM of the function. Returns: Two arrays representing the AM and FM of the function. .. !! processed by numpydoc !! .. py:method:: build_shape(ax=None) .. py:method:: build_table() Builds a table of variables, axes, and UUIDs for all non-static Parameters in the object. Returns: dict: A dictionary containing the following keys: "Variable", "axis", and "uuid". The values for each key are lists of the corresponding values for each non-static Parameter. .. !! processed by numpydoc !! .. py:method:: is_static() Check if all parameters in the pulse object are static. Returns: bool: True if all parameters are static, False otherwise. .. !! processed by numpydoc !! .. py:method:: isDelayFocused() Does the pulse contain a specified time, `t`? If so then it is not delay focused. .. !! processed by numpydoc !! .. py:method:: isPulseFocused() Does the pulse contain a specified time, `t`? If so then it is delay focused. .. !! processed by numpydoc !! .. py:method:: plot(pad=1000) Plots the time domain representation of this pulse. :Parameters: **pad** : int, optional The number of zeros to pad the data with, by default 1000 .. !! processed by numpydoc !! .. py:method:: _calc_fft(pad=10000) .. py:property:: amp_factor The B1 amplitude factor (nutation frequency) for the pulse in GHz .. !! processed by numpydoc !! .. py:method:: exciteprofile_old(freqs=None, resonator=None) Excitation profile Generates the exciatation profiles for this pulse. This function is ported from EasySpin (https://easyspin.org/easyspin/documentation/sop.html) [1-2], and based upon the method from Gunnar Jeschke, Stefan Pribitzer and Andrin Doll[3]. References: +++++++++++ [1] Stefan Stoll, Arthur Schweiger EasySpin, a comprehensive software package for spectral simulation and analysis in EPR J. Magn. Reson. 178(1), 42-55 (2006) [2] Stefan Stoll, R. David Britt General and efficient simulation of pulse EPR spectra Phys. Chem. Chem. Phys. 11, 6614-6625 (2009) [3] Jeschke, G., Pribitzer, S. & DollA. Coherence Transfer by Passage Pulses in Electron Paramagnetic Resonance Spectroscopy. J. Phys. Chem. B 119, 13570-13582 (2015) :Parameters: **freqs: np.ndarray, optional** The frequency axis. Caution: A larger number of points will linearly increase computation time. **resonator: ad.ResonatorProfile, optional** .. :Returns: Mx: np.ndarray The magentisation in the X direction. My: np.ndarray The magentisation in the Y direction. Mz: np.ndarray The magentisation in the Z direction. .. !! processed by numpydoc !! .. py:method:: exciteprofile(freqs=None, resonator=None, trajectory=False) Excitation profile Generates the exciatation profiles for this pulse, using the two-level system model developed by Jeschke et al. [1]. And then optimised in the PulseShape software package by Maxx Tessmer [2], reproduced under the GNU GPL v3 license. References: +++++++++++ [1] Jeschke, G., Pribitzer, S. & Doll, A. Coherence Transfer by Passage Pulses in Electron Paramagnetic Resonance Spectroscopy. J. Phys. Chem. B 119, 13570-13582 (2015) [2] https://github.com/mtessmer/PulseShape :Parameters: **freqs: np.ndarray, optional** The frequency axis. Caution: A larger number of points will linearly increase computation time. **resonator: ad.ResonatorProfile, optional** The resonator profile to apply resonator compensation. **trajectory: bool, optional** If True, the function will return the magnetisation at each time point. Default is False. :Returns: Mag: np.ndarray The magnetisation in the X, Y, and Z directions. .. !! processed by numpydoc !! .. py:method:: plot_fft() .. py:method:: _pcyc_str() .. py:method:: __str__() .. py:method:: copy(clear=False, **kwargs) Creates a deep-copy of the pulse. I.e. Every parameter object is re-created at another memory space. Parameter can be chaged at this stage by adding them as keyword- arguments (kwargs). :Returns: Pulse A deep copy of the pulse .. !! processed by numpydoc !! .. py:method:: _to_dict() .. py:method:: _to_json() .. py:method:: save(filename) Save the Pulse to a JSON file. :Parameters: **filename** : str Path to the JSON file. :Returns: None .. :Raises: TypeError If the object cannot be serialized to JSON. .. !! processed by numpydoc !! .. py:method:: _from_dict(dct) :classmethod: .. py:method:: _from_json(JSONstring) :classmethod: .. py:method:: load(filename) :classmethod: Load a Pulse object from a JSON file. :Parameters: **filename** : str Path to the JSON file. :Returns: **obj** : Pulse The Pulse loaded from the JSON file. :Raises: FileNotFoundError If the file does not exist. .. !! processed by numpydoc !!