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Extend mon_data_space.py to support MinMon binary data #162

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merged 2 commits into from
Nov 13, 2023
Merged

Extend mon_data_space.py to support MinMon binary data #162

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8a4f429
Ref #161
EdwardSafford-NOAA Nov 9, 2023
b3b4055
Ref #161
EdwardSafford-NOAA Nov 9, 2023
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48 changes: 34 additions & 14 deletions src/eva/data/mon_data_space.py
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Original file line number Diff line number Diff line change
Expand Up @@ -9,9 +9,9 @@

# --------------------------------------------------------------------------------------------------


import os
import numpy as np
import array

from xarray import Dataset, concat, merge, align
from scipy.io import FortranFile
Expand Down Expand Up @@ -162,9 +162,10 @@ def execute(self, dataset_config, data_collections, timing):
ds, chans_dict = \
self.subset_coordinate(ds, coord_dict[x][1], requested_coord[x], chans_dict)

# Conditionally add channel, level, and scan related variables
# ------------------------------------------------------------
ds = self.loadConditionalItems(ds, chans_dict, levs_dict, scanpo)
# Conditionally add channel, level, scan, and iteration related variables
# -----------------------------------------------------------------------
iterations = x_range if 'Iteration' in coords.values() else None
ds = self.loadConditionalItems(ds, chans_dict, levs_dict, scanpo, iterations)

# Rename variables with group
rename_dict = {}
Expand Down Expand Up @@ -640,14 +641,17 @@ def read_ieee(self, file_name, coords, dims, ndims_used, dims_arr, nvars, vars,
for x in range(nvars):
if load_data:
if ndims_used == 1:
arr = f.read_reals(dtype=np.dtype('>f4'))
with open(filename, 'rb') as infile:
binary_data = infile.read()

arr = array.array('f')
arr.frombytes(binary_data)
else:
arr = np.transpose(f.read_reals(dtype=np.dtype('>f4')).reshape(dimensions))
else:
arr = zarray

rtn_array = np.append(rtn_array, [arr], axis=0)

if load_data:
f.close()
return rtn_array, cycle_tm
Expand Down Expand Up @@ -864,35 +868,48 @@ def load_dset(self, vars, nvars, coords, darr, dims, ndims_used,
# create dataset from file components
rtn_ds = None

new_coords = {}
for x in range(0, nvars):
if ndims_used == 1:
d = {
vars[x]: {"dims": (coords[dims_arr[0]]), "data": darr[x, :]}
}

# MinMon plots require both the 'allgnorm' data and log('allgnorm').
if vars[x] == 'allgnorm':
d.update({
"log_gnorm": {"dims": (coords[dims_arr[0]]), "data": np.log(darr[x, :])}
})
new_coords = {
coords[dims_arr[0]]: x_range
}
if ndims_used == 2:
d = {
vars[x]: {"dims": (coords[dims_arr[0]], coords[dims_arr[1]]),
"data": darr[x, :, :]}
}
new_coords = {
coords[dims_arr[0]]: x_range,
coords[dims_arr[1]]: y_range
}
if ndims_used == 3:
d = {
vars[x]: {"dims": (coords[dims_arr[0]], coords[dims_arr[1]],
coords[dims_arr[2]]),
"data": darr[x, :, :]}
}
new_coords = {
coords[dims_arr[0]]: x_range,
coords[dims_arr[1]]: y_range,
coords[dims_arr[2]]: z_range
}

if 'Channel' in coords.values():
d.update({"Channel": {"dims": ("Channel"), "data": channo}})

new_ds = Dataset.from_dict(d)
rtn_ds = new_ds if rtn_ds is None else rtn_ds.merge(new_ds)

# Define new coordinates
new_coords = {
coords[dims_arr[0]]: x_range,
coords[dims_arr[1]]: y_range
}

# Add the new coordinates to the dataset
rtn_ds = rtn_ds.assign_coords(new_coords)

Expand Down Expand Up @@ -931,7 +948,7 @@ def load_dset(self, vars, nvars, coords, darr, dims, ndims_used,

# ----------------------------------------------------------------------------------------------

def loadConditionalItems(self, dataset, chans_dict, levs_dict, scanpo):
def loadConditionalItems(self, dataset, chans_dict, levs_dict, scanpo, iterations=None):

"""
Add channel, level, and scan related variables to the dataset.
Expand All @@ -941,7 +958,7 @@ def loadConditionalItems(self, dataset, chans_dict, levs_dict, scanpo):
chans_dict (dict): Dictionary of channel components.
levs_dict (dict): Dictionary of level components.
scanpo (list): List of scan positions.

iterations (list): List of iterations.
Returns:
xarray.Dataset: Dataset with added scan-related variables.
"""
Expand Down Expand Up @@ -973,6 +990,9 @@ def loadConditionalItems(self, dataset, chans_dict, levs_dict, scanpo):
scan_array[:, x] = np.array([scanpo])
dataset['scan'] = (['Scan', 'Channel'], scan_array)

if iterations is not None:
dataset['iteration'] = (['Iteration'], iterations)

return dataset

# ----------------------------------------------------------------------------------------------
Expand Down
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