damaris.data.ADC_Result

class damaris.data.ADC_Result(x: ndarray | list | None = None, y: list[ndarray] | None = None, index: list[tuple[int, int]] | None = None, sampl_freq: float | None = None, desc: dict[str, str] | None = None, job_id: int | None = None, job_date: datetime | None = None)[source]
__init__(x: ndarray | list | None = None, y: list[ndarray] | None = None, index: list[tuple[int, int]] | None = None, sampl_freq: float | None = None, desc: dict[str, str] | None = None, job_id: int | None = None, job_date: datetime | None = None)[source]

Methods

__init__([x, y, index, sampl_freq, desc, ...])

add_sample_space(samples)

Adds space for n samples, where n can also be negative (deletes space).

autophase()

Automatically phases the data to maximize real part.

bartlett_window()

Symmetric centered window (bartlett)

baseline([last_part])

Correct the baseline of your data by subtracting the mean of the last_part fraction of your data.

blackman_window()

Symmetric centered window (blackmann)

check_clipping([bit_depth])

Check if any data in y is clipped.

clip([start, stop])

Method for clipping data, returns only the data between start and stop start and stop can be either time or frequency.

contains_data()

Returns true if ADC_Result contains data.

create_data_space(channels, samples)

Initialises the internal data-structures

dexp_window([line_broadening, ...])

exp_window([line_broadening])

Exponential window function

fft([samples])

Calculate the Fourier transform of the data inplace.

gauss_window([line_broadening])

Gaussian window function

get_description(key)

Returns the description value for a given key

get_description_dictionary()

Returns a reference to the description (Dictionary)

get_index_bounds(index)

Returns a tuple with (start, end) of the wanted result

get_job_date()

Gets the date of this result

get_job_id()

Returns the job-id of this result

get_legend()

Returns the legend of the plot (Dictionary)

get_nChannels()

Gets the number of channels

get_number_of_channels()

Return the number of data channels.

get_phase([pos])

Return the phase in degrees from the first two channels.

get_result_by_index(index)

get_sampling_rate()

Returns the samplingfrequency

get_style()

Returns a reference to plot-styles (dictionary)

get_text(index)

Returns labels to be plotted (List)

get_title()

Returns the title of the plot

get_xdata()

Returns a reference to the x-Plotdata (array)

get_xlabel()

Returns the label for the x-axis

get_xmax()

Returns maximum of x

get_xmin()

Returns minimun of x

get_xminpos()

Returns smallest positive value of x

get_ydata([channel])

Return public values for one channel.

get_ylabel()

Gets the label for the y-axis

get_ymax()

Return the global maximum across all channels.

get_ymax_channels()

Return the maximum value of each channel.

get_ymean([start, stop])

Return the mean of every channel over a time interval.

get_ymin()

Return the global minimum across all channels.

get_ymin_channels()

Return the minimum value of each channel.

get_yminpos()

Returns smallest positive value of y

get_yrms()

Return the root-mean-square value of each channel.

get_ystd()

Return the population standard deviation of each channel.

hamming_window()

Symmetric centered window (hamming)

hanning_window()

Symmetric centered window (hanning)

kaiser_window([beta, use_scipy])

Symmetric centered window (kaiser)

lowpass(cutoff[, numtaps])

Apply a zero-phase lowpass FIR filter to all channels.

magnitude()

Return absolute signal, i.e.:

phase(degrees)

rotate signal by degrees for phase cycling, etc.

ppm(f_ref)

Return result scaled to PPM compared to f_ref

set_description(key, value)

Adds a attribute to the description

set_description_dictionary(dictionary)

Sets the entire description

set_job_date(date)

Sets the date of this result

set_job_id(_id)

Sets the job-id of this result

set_legend(channel, value)

Sets the legend of the plot

set_nChannels(channels)

Sets the number of channels

set_sampling_rate(hz)

Sets the samplingfrequency in hz

set_style(channel, value)

Sets a channel to a certain plot-style

set_text(index, text)

Sets labels to be plotted

set_title(title)

Sets the title of the plot

set_xdata(pos, value)

Sets a point in x

set_xlabel(label)

Sets the label for the x-axis

set_xmax(xmax)

Sets maximum of x

set_xmin(xmin)

Sets minimum of x

set_ydata(channel, pos, value)

Sets a point in y

set_ylabel(label)

Sets the label for the y-axis

set_ymax(ymax)

Sets maximum of y

set_ymin(ymin)

Sets minimum of y

traf_window([line_broadening])

uses_statistics()

write_to_csv([destination, delimiter])

writes the data to a file or to sys.stdout destination can be a file or a filename suitable for further processing

write_to_hdf(hdffile, where, name, title[, ...])

write_to_simpson([destination, delimiter])

writes the data to a text file or sys.stdout in Simpson format, for further processing with the NMRnotebook software; destination can be a file or a filename

Attributes

default_bit_depth

Represents the result of an ADC, encapsulating data and metadata for processing, visualization, and export.