Tools related to input/output
pid = "FUV2015_225_12_13"
pds = PDSReader(get_data_path(pid))
pds.data.shape
pds.band_range
pds.line_range
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
uv.plot()
uv.plot(precise=True)
(uv.plot().opts(axiswise=False) + uv.plot(precise=True)).cols(1)
uv.plot(calibrated=True)
pds.timestring
pds.euv
pds.euv.wavelengths
pds.fuv.wavelengths
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"