import xarray as xr
import pandas as pd
xr.set_options(keep_attrs=True, display_style="html")
<xarray.core.options.set_options at 0x7ff000ed4c18>
station = "Davis"
inpath = "/projekt2/hochatm/akuchar/from_GStobel/analysis_h5only/"
ds_info = xr.open_dataset(f"{inpath}{station}_solar_cycle.h5", group="info")
ds_info = ds_info.rename({"phony_dim_7": "alt"})
ds = xr.open_dataset(f"{inpath}{station}_solar_cycle.h5", group="LTC")
s_year = int(ds["year"].values[0][0])
s_month = int(ds["month"].values[0][0])
time_shape = ds["year"].values.shape[0]
ds = ds.assign_coords(
{
"alt": ds_info["alt"].squeeze(),
"time": pd.date_range(f"{s_year}-{s_month}", freq="M", periods=time_shape),
}
)
ds = ds.rename({"phony_dim_0": "time", "phony_dim_1": "alt"})
ds
<xarray.Dataset>
Dimensions: (alt: 26, phony_dim_2: 4, phony_dim_3: 12, phony_dim_4: 1, time: 192)
Coordinates:
* alt (alt) float64 70.0 72.0 74.0 76.0 ... 116.0 118.0 120.0
* time (time) datetime64[ns] 2005-01-31 ... 2020-12-31
Dimensions without coordinates: phony_dim_2, phony_dim_3, phony_dim_4
Data variables:
A12u_mod (time, alt) float64 nan nan nan nan ... nan nan nan nan
A12u_mod_err (time, alt) float64 nan nan nan nan ... nan nan nan nan
A12u_sol_cycle (phony_dim_2, phony_dim_3, alt) float64 nan nan ... nan
A12u_sol_cycle_err (phony_dim_2, phony_dim_3, alt) float64 nan nan ... nan
A12um_mod (time, alt) float64 nan nan nan nan ... nan nan nan nan
A12um_mod_err (time, alt) float64 nan nan nan nan ... nan nan nan nan
A12v_mod (time, alt) float64 nan nan nan nan ... nan nan nan nan
A12v_mod_err (time, alt) float64 nan nan nan nan ... nan nan nan nan
A12v_sol_cycle (phony_dim_2, phony_dim_3, alt) float64 nan nan ... nan
A12v_sol_cycle_err (phony_dim_2, phony_dim_3, alt) float64 nan nan ... nan
A12vm_mod (time, alt) float64 nan nan nan nan ... nan nan nan nan
A12vm_mod_err (time, alt) float64 nan nan nan nan ... nan nan nan nan
A24u_mod (time, alt) float64 nan nan nan nan ... nan nan nan nan
A24u_mod_err (time, alt) float64 nan nan nan nan ... nan nan nan nan
A24u_sol_cycle (phony_dim_2, phony_dim_3, alt) float64 nan nan ... nan
A24u_sol_cycle_err (phony_dim_2, phony_dim_3, alt) float64 nan nan ... nan
A24um_mod (time, alt) float64 nan nan nan nan ... nan nan nan nan
A24um_mod_err (time, alt) float64 nan nan nan nan ... nan nan nan nan
A24v_mod (time, alt) float64 nan nan nan nan ... nan nan nan nan
A24v_mod_err (time, alt) float64 nan nan nan nan ... nan nan nan nan
A24v_sol_cycle (phony_dim_2, phony_dim_3, alt) float64 nan nan ... nan
A24v_sol_cycle_err (phony_dim_2, phony_dim_3, alt) float64 nan nan ... nan
A24vm_mod (time, alt) float64 nan nan nan nan ... nan nan nan nan
A24vm_mod_err (time, alt) float64 nan nan nan nan ... nan nan nan nan
GW_mod (time, alt) float64 nan nan nan nan ... nan nan nan nan
GW_mod_err (time, alt) float64 nan nan nan nan ... nan nan nan nan
PW_mod (time, alt) float64 nan nan nan nan ... nan nan nan nan
PW_mod_err (time, alt) float64 nan nan nan nan ... nan nan nan nan
day (time, phony_dim_4) float64 15.0 15.0 15.0 ... 15.0 15.0
month (time, phony_dim_4) float64 1.0 2.0 3.0 ... 11.0 12.0
p12u_sol_cycle (phony_dim_3, alt) float64 nan nan nan ... nan nan nan
p12u_sol_cycle_err (phony_dim_3, alt) float64 nan nan nan ... nan nan nan
p12v_sol_cycle (phony_dim_3, alt) float64 nan nan nan ... nan nan nan
p12v_sol_cycle_err (phony_dim_3, alt) float64 nan nan nan ... nan nan nan
p24u_sol_cycle (phony_dim_3, alt) float64 nan nan nan ... nan nan nan
p24u_sol_cycle_err (phony_dim_3, alt) float64 nan nan nan ... nan nan nan
p24v_sol_cycle (phony_dim_3, alt) float64 nan nan nan ... nan nan nan
p24v_sol_cycle_err (phony_dim_3, alt) float64 nan nan nan ... nan nan nan
pu0_sol_cycle (phony_dim_3, alt) float64 nan nan nan ... nan nan nan
pu0_sol_cycle_err (phony_dim_3, alt) float64 nan nan nan ... nan nan nan
pv0_sol_cycle (phony_dim_3, alt) float64 nan nan nan ... nan nan nan
pv0_sol_cycle_err (phony_dim_3, alt) float64 nan nan nan ... nan nan nan
season (phony_dim_3, phony_dim_4) float64 7.378e+05 ... 7.38...
u0_mod (time, alt) float64 nan nan nan nan ... nan nan nan nan
u0_mod_err (time, alt) float64 nan nan nan nan ... nan nan nan nan
u0_sol_cycle (phony_dim_2, phony_dim_3, alt) float64 nan nan ... nan
u0_sol_cycle_err (phony_dim_2, phony_dim_3, alt) float64 nan nan ... nan
u0m_mod (time, alt) float64 nan nan nan nan ... nan nan nan nan
u0m_mod_err (time, alt) float64 nan nan nan nan ... nan nan nan nan
u0m_sol_cycle (phony_dim_2, alt) float64 nan nan nan ... nan nan nan
u0m_sol_cycle_err (phony_dim_2, alt) float64 nan nan nan ... nan nan nan
v0_mod (time, alt) float64 nan nan nan nan ... nan nan nan nan
v0_mod_err (time, alt) float64 nan nan nan nan ... nan nan nan nan
v0_sol_cycle (phony_dim_2, phony_dim_3, alt) float64 nan nan ... nan
v0_sol_cycle_err (phony_dim_2, phony_dim_3, alt) float64 nan nan ... nan
v0m_mod (time, alt) float64 nan nan nan nan ... nan nan nan nan
v0m_mod_err (time, alt) float64 nan nan nan nan ... nan nan nan nan
v0m_sol_cycle (phony_dim_2, alt) float64 nan nan nan ... nan nan nan
v0m_sol_cycle_err (phony_dim_2, alt) float64 nan nan nan ... nan nan nan
year (time, phony_dim_4) float64 2.005e+03 ... 2.02e+03array([ 70., 72., 74., 76., 78., 80., 82., 84., 86., 88., 90., 92.,
94., 96., 98., 100., 102., 104., 106., 108., 110., 112., 114., 116.,
118., 120.])array(['2005-01-31T00:00:00.000000000', '2005-02-28T00:00:00.000000000',
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[ nan, nan, nan, nan, 4.740951e-02,
3.412316e-02, 2.798630e-02, 2.328948e-02, 2.019846e-02, 1.880141e-02,
1.931178e-02, 2.180857e-02, 2.649126e-02, 3.344346e-02, 4.345958e-02,
6.650180e-02, nan, nan, nan, nan,
nan, nan, nan, nan, nan,
nan],
[ nan, nan, nan, nan, 4.072088e-02,
2.910968e-02, 2.375555e-02, 1.969902e-02, 1.711739e-02, 1.603527e-02,
1.666356e-02, 1.912801e-02, 2.355690e-02, 2.994941e-02, 3.890664e-02,
5.813947e-02, nan, nan, nan, nan,
nan, nan, nan, nan, nan,
nan]])array([[2005.],
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[2020.],
[2020.],
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[2020.]])ds = xr.open_dataset(f"{inpath}{station}_solar_cycle.h5", group="wind")
ds = ds.rename({"phony_dim_10": "time", "phony_dim_11": "alt"})
s_year = int(ds_info["year"].values[0][0])
s_month = int(ds_info["month"].values[0][0])
s_day = int(ds_info["day"].values[0][0])
ds = ds.assign_coords(
{
"alt": ds_info["alt"].squeeze(),
"time": pd.date_range(
f"{s_year}-{s_month}-{s_day}", freq="D", periods=ds.time.shape[0]
),
}
)
ds
<xarray.Dataset>
Dimensions: (alt: 26, time: 5844)
Coordinates:
* alt (alt) float64 70.0 72.0 74.0 76.0 78.0 ... 114.0 116.0 118.0 120.0
* time (time) datetime64[ns] 2005-01-01 2005-01-02 ... 2020-12-31
Data variables:
u0 (time, alt) float64 ...
u0_err (time, alt) float64 ...
v0 (time, alt) float64 ...
v0_err (time, alt) float64 ...
w0 (time, alt) float64 ...
w0_err (time, alt) float64 ...array([ 70., 72., 74., 76., 78., 80., 82., 84., 86., 88., 90., 92.,
94., 96., 98., 100., 102., 104., 106., 108., 110., 112., 114., 116.,
118., 120.])array(['2005-01-01T00:00:00.000000000', '2005-01-02T00:00:00.000000000',
'2005-01-03T00:00:00.000000000', ..., '2020-12-29T00:00:00.000000000',
'2020-12-30T00:00:00.000000000', '2020-12-31T00:00:00.000000000'],
dtype='datetime64[ns]')[151944 values with dtype=float64]
[151944 values with dtype=float64]
[151944 values with dtype=float64]
[151944 values with dtype=float64]
[151944 values with dtype=float64]
[151944 values with dtype=float64]