Reading UVIS data

IO

Tools related to input/output

⚠️ Demo cells below are marked #| eval: false — they require live PDS index fetches, cached data products, or interactive plotting backends that are unavailable during a clean docs render. Open this notebook in JupyterLab to step through it cell-by-cell against your local data.

import datetime as dt
from pathlib import Path

import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
import xarray as xr
from astropy import units as u

import hvplot.pandas  # noqa: F401
import hvplot.xarray  # noqa: F401
import holoviews as hv

from pyuvis import (
    PDSReader,
    UVPDS,
    UVISObs,
    HSP,
    FUV_CDF,
    EUV_CDF,
    sens_df,
)

hide

PDSReader

pid = "FUV2015_225_12_13"

pds = PDSReader(get_data_path(pid))

pds.data.shape

pds.band_range

pds.line_range

hide

UVPDS

uv = UVPDS(pid)

uv.xarray

uv.calibrated

uv.wavelengths

uv.pid

uv.integration_duration

uv.file_id

uv.default_wave_min, uv.default_wave_max

uv.n_bands

uv.n_integrations

uv.pds.band_range, uv.pds.line_range

show_doc(UVPDS.plot)

uv.plot()

uv.plot(precise=True)

(uv.plot().opts(axiswise=False) + uv.plot(precise=True)).cols(1)

uv.plot(calibrated=True)

pds = UVISObs(“FUV2005_172_03_35”)

pds.timestring

pds.euv

pds.euv.wavelengths

pds.fuv.wavelengths

Examples from the UVIS User’s guide

Get the current user guide PDF by using get_user_guide()

get_user_guide()

pid = "FUV2005_172_03_35"

data = UVPDS(pid)

arr = data.xarray

arr.sum(["spatial", "samples"]).hvplot(ylim=(0, 5e5), xlim=(100, 200), title="Total counts")

pid = "FUV2004_163_19_22"

data = UVPDS(pid)
arr = data.xarray

summed = arr.sel(samples=15, drop=True).sum(["spatial"]) / (64 * 30)

s = summed.to_pandas()

import hvplot.pandas

kwargs = {"ylim": (0, 0.02), "xlim": (110, 190), "width": 500}

blackman = s.rolling(window=14, win_type="blackmanharris").mean().hvplot(**kwargs, label='blackmanharris')
blackman

gaussian = s.rolling(window=10, win_type="gaussian").mean(std=3).hvplot(**kwargs, label="gaussian")
gaussian

gaussian * blackman

pid = "FUV2005_195_19_52"

data = UVPDS(pid)
arr = data.xarray

data.shape

s16 = arr.sel(samples=16).sum("spatial")
s32 = arr.sel(samples=32).sum("spatial")

ratio = s32 / s16

(
    s16.hvplot(ylim=(0, 400), title="Sample #16")
    + s32.hvplot(ylim=(0, 400), title="Sample #32")
    + ratio.hvplot(title="Ratio", shared_axes=False)
).cols(1)

arr.sum(["spatial", "samples"]).hvplot()

pid = "EUV2002_198_03_26_54_UVIS_C33ST_SPICARAST002_PRIME"
pid = "FUV2005_195_19_52"

NetCDF readers

The NetCDF readers can be used for the UVIS team internally distributed netCDF files.