def remove_static_shift(
df_fn,
nf=22,
save_dir=Path(
r"c:\Users\jpeacock\OneDrive - DOI\Geysers\CEC\EDI_files_birrp_processed\Geographic\Edited\SS"
),
):
df = pd.read_csv(df_fn)
for row in df.itertuples():
m1 = MT(row.original)
m2 = MT(row.phase_01)
m1.Z, m1.Tipper = m1.interpolate(m2.frequencies, bounds_error=False)
sx = np.median(m1.Z.res_xy[:nf] / m2.Z.res_xy[:nf])
sy = np.median(m1.Z.res_yx[:nf] / m2.Z.res_yx[:nf])
print(f"station: {m1.station} - {m2.station}: sx={sx}, sy={sy}")
m2.Z = m2.remove_static_shift(1.0 / sx, 1.0 / sy)
m2.write_mt_file(save_dir=save_dir)
"start": "time_period.start",
"end": "time_period.end",
}
# "runlist": "run_list"}
for fn in fn_list:
m = MT(fn)
find = m.station_metadata.comments.find("SITE LATITUDE")
lines = m.station_metadata.comments[find:find + chars].split("\n")
attr_dict = {}
for line in lines:
if line.count("=") == 0:
continue
if line.count("=") > 1:
key, value = line.split(" ")
attr, units, value = value.split("=")
attr_dict[key.lower()] = value
attr_dict[f"{key.lower()}.{attr}"] = units
else:
key, value = line.split("=")
key = key.replace("SITE", "").lower().strip().replace(" ", "_")
value = value.replace(r"UTC/GMT", "").replace('"', "")
attr_dict[key] = value
for brod_key, mt_key in key_dict.items():
value = attr_dict[brod_key]
m.station_metadata.set_attr_from_name(mt_key, value)
m.write_mt_file(fn.name, save_dir=fn.parent)
from mtpy.core.mt import MT
from mtpy.utils.calculator import get_period_list
# directory format for windows users
edi_path = r'C:\mtpywin\mtpy\examples\data\edi_files_2'
savepath = r'C:\tmp'
edi_file = os.path.join(edi_path,'Synth00.edi')
mtObj = MT(edi_file)
#new_freq_list = mtObj.Z.freq # takes every second frequency
new_freq_list = 1./get_period_list(1e-4,1e3,5) # 5 periods per decade from 0.0001 to 100000 s
# create new Z and Tipper objects containing interpolated data
new_Z_obj, new_Tipper_obj = mtObj.interpolate(new_freq_list)
# write a new edi file using the new data
mtObj.write_mt_file(save_dir=savepath,
fn_basename='Synth00_new',
file_type='edi', # edi or xml format
new_Z_obj=new_Z_obj, # provide a z object to update the data
new_Tipper_obj=new_Tipper_obj, # provide a tipper object to update the data
longitude_format='LONG', # write longitudes as 'LON' or 'LONG'
latlon_format='dd' # write as decimal degrees (any other input
# will write as degrees minutes seconds
)
m.hx_metadata.translated_azimuth = (
m.hx_metadata.measurement_azimuth -
m.station_metadata.location.declination.value)
m.hx_metadata.translated_tilt = None
m.hx_metadata.type = "magnetic"
m.hx_metadata.units = "nanotesla"
m.hy_metadata.measurement_azimuth = sdf.hy_azimuth
m.hy_metadata.measurement_tilt = 0.0
m.hy_metadata.sensor.manufacturer = "Zonge International"
m.hy_metadata.sensor.model = "ANT4"
m.hy_metadata.sensor.type = "magnetic induction coil"
m.hy_metadata.translated_azimuth = (
m.hy_metadata.measurement_azimuth -
m.station_metadata.location.declination.value)
m.hy_metadata.translated_tilt = None
m.hy_metadata.type = "magnetic"
m.hy_metadata.units = "nanotesla"
m.hz_metadata.measurement_azimuth = 0
m.hz_metadata.measurement_tilt = 90
m.hz_metadata.sensor.manufacturer = "Zonge International"
m.hz_metadata.sensor.model = "ANT4"
m.hz_metadata.sensor.type = "magnetic induction coil"
m.hz_metadata.translated_azimuth = 0
m.hz_metadata.translated_tilt = 90
m.hz_metadata.type = "magnetic"
m.hz_metadata.units = "nanotesla"
m.write_mt_file()
# -*- coding: utf-8 -*-
"""
This script will rotate principle axis back to geographic coordinates.
Created on Wed Jan 26 11:07:21 2022
@author: jpeacock
"""
# =============================================================================
# Imports
# =============================================================================
from pathlib import Path
from mtpy.core.mt import MT
# =============================================================================
edi_path = Path(r"c:\Users\jpeacock\OneDrive - DOI\mt\principle_axis")
for edi_filename in edi_path.glob("*.edi"):
m = MT(edi_filename)
m.Z.rotate(m.Z.rotation_angle)
m.Tipper.rotate(m.Tipper.rotation_angle)
p = m.plot_mt_response(plot_num=2)
p.save_plot(edi_path.joinpath(f"{m.station}_geographic.png").as_posix(),
fig_dpi=300)
m.write_mt_file(fn_basename=f"{m.station}_geographic.edi")
"""
Created on Mon Nov 30 15:43:54 2020
:author: Jared Peacock
:license: MIT
"""
from pathlib import Path
import pandas as pd
from mtpy.core.mt import MT
epath = Path(r"c:\Users\jpeacock\Documents\milipitas")
spath = Path(r"c:\Users\jpeacock\Documents\milipitas\new_edis")
loc_fn = Path(r"c:\Users\jpeacock\Documents\milipitas\latlon_NAD83.txt")
df = pd.read_csv(loc_fn)
for fn in epath.glob("*.edi"):
m = MT(fn)
m.station = f"{m.station}_{fn.stem}"
l = df[df.Station == fn.stem]
m.latitude = l.Latitude.values[0]
m.longitude = l.Longitude.values[0]
m.elevation = l.Elevation.values[0]
m.write_mt_file(save_dir=spath)
p = m.plot_mt_response(plot_num=2)
p.save_plot(spath.joinpath(f"{m.station}.png").as_posix(), fig_dpi=300)
def analysis_edi(datadir):
""" analysis """
# Define the path to your edi file
edi_file = datadir + r"edifiles2\15125A.edi"
savepath = datadir
edi_path = datadir + 'edifiles2'
# Create an MT object
mt_obj = MT(edi_file)
# look at the skew values as a histogram
plt.hist(mt_obj.pt.beta, bins=50)
plt.xlabel('Skew angle (degree)')
plt.ylabel('Number of values')
plt.show()
# Have a look at the dimensionality
dim = dimensionality(z_object=mt_obj.Z,
skew_threshold=5,
eccentricity_threshold=0.1)
print(dim)
# calculate strike
strike = strike_angle(z_object=mt_obj.Z,
skew_threshold=5,
eccentricity_threshold=0.1)
# display the median strike angle for this station
# two values because of 90 degree ambiguity in strike
strikemedian = np.nanmedian(strike, axis=0)
print(strikemedian)
# Use dimensionality to mask a file
mask = dim < 3
# Apply masking. The new arrays z_array, z_err_array, and freq will
# exclude values where mask is False (i.e. the 3D parts)
new_Z_obj = Z(z_array=mt_obj.Z.z[mask],
z_err_array=mt_obj.Z.z_err[mask],
freq=mt_obj.Z.freq[mask])
new_Tipper_obj = Tipper(tipper_array=mt_obj.Tipper.tipper[mask],
tipper_err_array=mt_obj.Tipper.tipper_err[mask],
freq=mt_obj.Tipper.freq[mask])
# Write a new edi file
mt_obj.write_mt_file(save_dir=savepath,
fn_basename='Synth00_mask3d',
file_type='edi',
new_Z_obj=new_Z_obj,
new_Tipper_obj=new_Tipper_obj,
longitude_format='LONG',
latlon_format='dd')
# Plot strike
# Get full path to all files with the extension '.edi' in edi_path
edi_list = [
os.path.join(edi_path, ff) for ff in os.listdir(edi_path)
if ff.endswith('.edi')
]
# make a plot (try also plot_type = 1 to plot by decade)
strikeplot = PlotStrike(fn_list=edi_list, plot_type=2, plot_tipper='y')
# save to file
# strikeplot.save_plot(savepath,
# file_format='.png',
# fig_dpi=400)
strike = strikemedian[0] # 0 index chosen based on geological information
mt_obj.Z.rotate(strike)
mt_obj.Tipper.rotate(strike)
# check the rotation angle
print(mt_obj.Z.rotation_angle)
# Write a new edi file (as before)
mt_obj.write_mt_file(save_dir=savepath,
fn_basename='Synth00_rotate%1i' % strike,
file_type='edi',
longitude_format='LONG',
latlon_format='dd')