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men.py
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men.py
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"""This file contains the export method for men-files.
Export a .men file
R.C. Caljé - march 2018
"""
from os import path
from numpy import NaN, array, vstack, zeros
from pandas import Timestamp
from scipy.io import loadmat, savemat
from ..utils import datetime2matlab
def load(fname: str) -> NotImplementedError:
raise NotImplementedError("This is not implemented yet. See the "
"reads-section for a Menyanthes-read")
def dump(fname: str, data: dict, version: int = 3, verbose: bool = True) -> None:
# version can also be a specific version, like '2.x.g.t (beta)', or an integer (see below)
if version == 3:
version = '3.x.b.c (gamma)'
elif version == 2:
version = '2.x.g.t (beta)'
# load an empty menyanthes file
io_dir, _ = path.split(__file__)
base_fname = path.join(io_dir, 'men', version + '.men')
if not path.exists(base_fname):
msg = "No Menyanthes file found for version {}".format(version)
raise Exception(msg)
men = loadmat(base_fname, matlab_compatible=True)
# add the oseries
dtypeH = men['H'].dtype
fields = dtypeH.fields.keys()
Hdict = {}
for field in fields:
if field == 'ID':
Hdict[field] = men['ID']['H'][0][0][0][0]
men['ID']['H'] += 1
elif field == 'Name':
Hdict[field] = data['oseries']['name']
elif field in ['NITGCode', 'OLGACode', 'NITGnr', 'OLGAnr']:
Hdict[field] = '<no data> (1)'
elif field == 'Type':
Hdict[field] = 'Head'
elif field in ['Project', 'layercode', 'LoggerSerial', 'area',
'datlog_serial']:
Hdict[field] = ''
elif field == 'values':
date = array(
[datetime2matlab(x) for x in data['oseries']['series'].index])
vals = data['oseries']['series'].values
Hdict[field] = [vstack((date, vals)).transpose()]
elif field == 'filtnr':
Hdict[field] = 1
elif field in ['handmeas', 'aerialphoto', 'BWImage', 'photo']:
Hdict[field] = [zeros(shape=(0, 0))]
elif field in ['LastTUFExport', 'surflev', 'measpointlev', 'upfiltlev',
'lowfiltlev', 'sedsumplength', 'LoggerDepth', 'tranche',
'datlog_depth']:
Hdict[field] = NaN
elif field == 'xcoord':
if 'x' in data['oseries']['metadata']:
Hdict[field] = data['oseries']['metadata']['x']
else:
Hdict[field] = NaN
elif field == 'ycoord':
if 'y' in data['oseries']['metadata']:
Hdict[field] = data['oseries']['metadata']['y']
else:
Hdict[field] = NaN
elif field == 'date':
Hdict[field] = datetime2matlab(Timestamp.now())
elif field == 'comment':
# Hdict[field] = [np.array(['',''])]
obj_arr = zeros((2,), dtype=object)
obj_arr[0] = ''
obj_arr[1] = ''
Hdict[field] = [obj_arr]
elif field in ['LoggerBrand', 'LoggerType', 'VegTypo', 'VegType',
'Organization']:
Hdict[field] = 'Unknown'
elif field == 'Status':
Hdict[field] = 'Active'
elif field == 'Comments':
# TODO: has to be a matlab-table
Hdict[field] = ''
elif field == 'Meta':
# TODO: has to be a matlab-table
Hdict[field] = ''
elif field == 'diver_files':
# has to be a matlab-struct
dtype = [('name', 'O'), ('LoggerSerial', 'O'), ('values', 'O'),
('orig_values', 'O'),
('changes', 'O'), ('current_change', 'O'), ('drift', 'O'),
('importedby', 'O'),
('importdate', 'O'), ('validated', 'O'),
('validatedby', 'O'), ('validatedate', 'O'),
('battery_cap', 'O'), ('iscomp', 'O'), ('density', 'O'),
('compID', 'O'), ('ref', 'O'),
('IsEquidistant', 'O'), ('IsLoggerfile', 'O'),
('timeshift', 'O')]
Hdict[field] = [array([], dtype=dtype)]
elif field == 'oldmetadata':
# for version='2.x.g.t (beta)'
dtype = [('xcoord', 'O'), ('ycoord', 'O'), ('upfiltlev', 'O'),
('lowfiltlev', 'O'),
('surflev', 'O'), ('measpointlev', 'O'),
('sedsumplength', 'O'), ('datlog_serial', 'O'),
('datlog_depth', 'O'), ('date', 'O'), ('comment', 'O'),
('LoggerBrand', 'O'),
('LoggerType', 'O'), ('VegTypo', 'O'), ('VegType', 'O')]
Hdict[field] = [array([], dtype=dtype)]
else:
raise (ValueError('Unknown field ' + field))
Hnew = zeros((1,), dtype=dtypeH)
for key, val in Hdict.items():
Hnew[key] = val
men['H'] = vstack((men['H'], Hnew))
# add the stressmodels
dtypeIN = men['IN'].dtype
fields = dtypeIN.fields.keys()
for key in data['stressmodels'].keys():
sm = data['stressmodels'][key]
for istress, stress in enumerate(sm['stress']):
INdict = {}
for field in fields:
if field == 'ID':
INdict[field] = men['ID']['IN'][0][0][0][0]
men['ID']['IN'] += 1
elif field == 'Name':
INdict[field] = stress['name']
elif field == 'Type':
if sm['stressmodel'] == 'StressModel2' and istress == 1:
INdict[field] = 'EVAP'
else:
INdict[field] = 'PREC'
elif field in ['LoggerSerial', 'datlog_serial']:
INdict[field] = ''
elif field == 'values':
date = array(
[datetime2matlab(x) for x in stress['series'].index])
vals = stress['series'].values
INdict[field] = [vstack((date, vals)).transpose()]
elif field == 'filtnr':
INdict[field] = 1
elif field in ['surflev', 'upfiltlev', 'lowfiltlev']:
INdict[field] = NaN
elif field == 'xcoord':
INdict[field] = NaN
elif field == 'ycoord':
INdict[field] = NaN
elif field == 'date':
INdict[field] = datetime2matlab(Timestamp.now())
elif field == 'Meta':
# TODO: has to be a matlab-table
INdict[field] = ''
else:
raise (ValueError('Unknown field ' + field))
INnew = zeros((1,), dtype=dtypeIN)
for key, val in INdict.items():
INnew[key] = val
men['IN'] = vstack((men['IN'], INnew))
if False:
# correct an error from loadmat
if 'AutoImport' in men['PS'].dtype.fields.keys():
for i in range(len(men['PS']['AutoImport'][0][0][0])):
men['PS']['AutoImport'][0][0][0][i]['IsEnabled'] = 0
men['PS']['AutoLocalExportEnabled'] = False
men['PS']['DrainVisEnabled'] = False
if 'RemoteDb' in men['PS'].dtype.fields.keys():
men['PS']['RemoteDb'][0][0]['IsConnected'] = 0
for key in men['ID'].dtype.fields.keys():
men['ID'][key] = 0
# currently does not generate a model yet
# save the file
if not fname.endswith('.men'):
fname = fname + '.men'
savemat(fname, men, appendmat=False)
if verbose:
return print("%s file succesfully exported" % fname)