Level_1

class esis.data.level_1.Level_1(intensity=None, intensity_uncertainty=None, wcs=None, time=None, time_index=None, channel=None, exposure_length=None, detector=None, sequence_metadata=None, analog_metadata=None)

Bases: kgpy.observatories.Obs, kgpy.mixin.Pickleable

__init__(intensity=None, intensity_uncertainty=None, wcs=None, time=None, time_index=None, channel=None, exposure_length=None, detector=None, sequence_metadata=None, analog_metadata=None)

Initialize self. See help(type(self)) for accurate signature.

Parameters
Return type

None

Attributes

analog_metadata

axis

channel

channel_labels

rtype

typing.List[str]

detector

exposure_length

intensity

intensity_uncertainty

num_channels

rtype

int

num_times

rtype

int

sequence_metadata

shape

rtype

typing.Tuple[int, …]

time

time_index

wcs

Methods

__init__([intensity, intensity_uncertainty, …])

Initialize self.

animate(data[, time_slice, axs, thresh_min, …])

rtype

matplotlib.animation.FuncAnimation

animate_channel(images, image_names[, ax, …])

animate_intensity([axs, thresh_min, …])

rtype

matplotlib.animation.FuncAnimation

animate_intensity_channel([ax, time_slice, …])

rtype

matplotlib.animation.FuncAnimation

create_mask(sequence)

default_pickle_path()

rtype

pathlib.Path

from_level_0(lev0[, despike])

rtype

esis.data.level_1.Level_1

from_pickle([path])

rtype

esis.data.level_1.Level_1

intensity_photons(wavelength)

rtype

astropy.units.Quantity

plot_channel(image[, image_name, ax, …])

rtype

matplotlib.axes.Axes

plot_channel_from_data(data[, ax, …])

rtype

matplotlib.axes.Axes

plot_exposure_length([ax])

rtype

matplotlib.axes.Axes

plot_intensity_channel([ax, time_index, …])

rtype

matplotlib.axes.Axes

plot_intensity_mean_vs_time([ax])

rtype

matplotlib.axes.Axes

plot_intensity_time([axs, time_index, …])

rtype

numpy.ndarray

plot_quantity_vs_index(a[, a_name, ax, …])

type a

astropy.units.Quantity

plot_time(images, image_names, axs[, …])

rtype

numpy.ndarray

plot_time_from_data(data[, axs, time_index, …])

rtype

numpy.ndarray

to_fits(path)

to_pickle([path])

zeros(shape)

rtype

kgpy.observatories.Obs

Inheritance Diagram

Inheritance diagram of esis.data.level_1.Level_1

animate(data, time_slice=slice(None, None, None), axs=None, thresh_min=<Quantity 0.01 %>, thresh_max=<Quantity 99.9 %>, norm_gamma=1, frame_interval=<Quantity 100. ms>)
Return type

matplotlib.animation.FuncAnimation

Parameters
animate_channel(images, image_names, ax=None, thresh_min=<Quantity 0.01 %>, thresh_max=<Quantity 99.9 %>, norm_gamma=1, norm_vmin=None, norm_vmax=None, frame_interval=<Quantity 1. s>)
Parameters
animate_intensity(axs=None, thresh_min=<Quantity 0.01 %>, thresh_max=<Quantity 99.9 %>, norm_gamma=1, frame_interval=<Quantity 100. ms>)
Return type

matplotlib.animation.FuncAnimation

Parameters
animate_intensity_channel(ax=None, time_slice=None, channel_index=0, thresh_min=<Quantity 0.01 %>, thresh_max=<Quantity 99.9 %>, norm_gamma=1, frame_interval=<Quantity 100. ms>)
Return type

matplotlib.animation.FuncAnimation

Parameters
create_mask(sequence)
static default_pickle_path()
Return type

pathlib.Path

classmethod from_level_0(lev0, despike=False)
Return type

esis.data.level_1.Level_1

Parameters
classmethod from_pickle(path=None)
Return type

esis.data.level_1.Level_1

Parameters

path (Optional[pathlib.Path]) –

intensity_photons(wavelength)
Return type

astropy.units.Quantity

Parameters

wavelength (astropy.units.Quantity) –

plot_channel(image, image_name='', ax=None, thresh_min=<Quantity 0.01 %>, thresh_max=<Quantity 99.9 %>, colorbar_location='right', transpose=False)
Return type

matplotlib.axes.Axes

Parameters
plot_channel_from_data(data, ax=None, time_index=0, channel_index=0, thresh_min=<Quantity 0.01 %>, thresh_max=<Quantity 99.9 %>)
Return type

matplotlib.axes.Axes

Parameters
plot_exposure_length(ax=None)
Return type

matplotlib.axes.Axes

Parameters

ax (Optional[matplotlib.axes.Axes]) –

plot_intensity_channel(ax=None, time_index=0, channel_index=0, thresh_min=<Quantity 0.01 %>, thresh_max=<Quantity 99.9 %>)
Return type

matplotlib.axes.Axes

Parameters
plot_intensity_mean_vs_time(ax=None)
Return type

matplotlib.axes.Axes

Parameters

ax (Optional[matplotlib.axes.Axes]) –

plot_intensity_time(axs=None, time_index=0, thresh_min=<Quantity 0.01 %>, thresh_max=<Quantity 99.9 %>)
Return type

numpy.ndarray

Parameters
plot_quantity_vs_index(a, a_name='', ax=None, legend_ncol=1, drawstyle='steps')
Parameters
Returns

Return type

matplotlib.axes.Axes

plot_time(images, image_names, axs, thresh_min=<Quantity 0.01 %>, thresh_max=<Quantity 99.9 %>)
Return type

numpy.ndarray

Parameters
plot_time_from_data(data, axs=None, time_index=0, thresh_min=<Quantity 0.01 %>, thresh_max=<Quantity 99.9 %>)
Return type

numpy.ndarray

Parameters
to_fits(path)
Parameters

path (pathlib.Path) –

to_pickle(path=None)
Parameters

path (Optional[pathlib.Path]) –

classmethod zeros(shape)
Return type

kgpy.observatories.Obs

Parameters

shape (Sequence[int]) –

analog_metadata: numpy.ndarray = None
axis: ClassVar[kgpy.observatories.ObsAxis] = <kgpy.observatories.ObsAxis object>
channel: Optional[astropy.units.Quantity] = None
property channel_labels
Return type

typing.List[str]

detector: Optional[esis.optics.detector.Detector] = None
exposure_length: Optional[astropy.units.Quantity] = None
intensity: Optional[astropy.units.Quantity] = None
intensity_uncertainty: Optional[astropy.units.Quantity] = None
property num_channels
Return type

int

property num_times
Return type

int

sequence_metadata: numpy.ndarray = None
property shape
Return type

typing.Tuple[int, …]

time: Optional[astropy.time.Time] = None
time_index: Optional[numpy.ndarray] = None
wcs: Optional[numpy.ndarray] = None