def import_eit40(self, filename, configfile, correction_file=None):
"""EIT40 data import"""
df = reda_eit40.import_medusa_data(
filename,
configfile,
)
if correction_file is not None:
reda_eit40.apply_correction_factors(df, correction_file)
redanr.assign_norrec_to_df(df)
df = redanr.assign_norrec_diffs(df, ['R', 'rpha'])
self._add_to_container(df)
print('Summary:')
self._describe_data(df)
def _add_to_container(self, df):
"""Add a given DataFrame to the container
Parameters
----------
df : pandas.DataFrame
DataFrame, must adhere to the container contraints (i.e., must have
all required columns)
"""
if self.data is None:
self.data = df
else:
self.data = pd.concat((self.data, df),
ignore_index=True,
sort=True)
# clean any previous norrec-assignments
if 'norrec' and 'id' in self.data.columns:
self.data.drop(['norrec', 'id'], axis=1, inplace=True)
self.data = assign_norrec_to_df(self.data)
# note that columns not in the DataFrames are ignored, thus no problem
# to include rho_a and rpha
self.data = assign_norrec_diffs(self.data, ['r', 'rho_a', 'rpha'])
# Put a, b, m, n in the front and ensure integers
for col in tuple("nmba"):
cols = list(self.data)
cols.insert(0, cols.pop(cols.index(col)))
self.data = self.data.iloc[:, self.data.columns.get_indexer(cols)]
self.data[col] = self.data[col].astype(int)
if 'timestep' in self.data:
# make sure the timestep column is in the fifth position
col_order = ['a', 'b', 'm', 'n', 'timestep']
self.data = self.data.reindex(columns=(col_order + list(
[key for key in self.data.columns if key not in col_order])))
# Daten einlesen und berechnen
# ----------------------------
# reda container erstellen
ert = reda.ERT()
# normal und reciproke Daten einlesen
ert.import_syscal_bin('data_nor.bin')
ert.import_syscal_bin('data_rec.bin', reciprocals=48)
# K-Faktor berechnen
K = reda.utils.geometric_factors.compute_K_analytical(ert.data, spacing=2.5)
# Rho_a berechnen
reda.utils.geometric_factors.apply_K(ert.data, K)
# negative Widerstände bei negativen K umdrehen
reda.utils.fix_sign_with_K.fix_sign_with_K(ert.data)
# calculate diffeence between nor and rec measurement
ert.data = NR.assign_norrec_diffs(ert.data, ('r', 'rho_a'))
###############################################################################
# Histogramme plotten
# -------------------
fig = ert.histogram(('r', 'rdiff', 'rho_a', 'rho_adiff', 'Iab'))
plt.savefig('histogramms.png')
###############################################################################
# Pseudosektionen plotten
# -----------------------
fig = ert.pseudosection('r')
plt.savefig('pseudo_r.png')
fig = ert.pseudosection('rdiff')