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New implemention for the meca function
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@seisman
seisman committed Mar 4, 2022
1 parent 76cb362 commit 621330d
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Showing 2 changed files with 73 additions and 249 deletions.
304 changes: 62 additions & 242 deletions pygmt/src/meca.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,14 +6,7 @@
import pandas as pd
from pygmt.clib import Session
from pygmt.exceptions import GMTError, GMTInvalidInput
from pygmt.helpers import (
build_arg_string,
data_kind,
dummy_context,
fmt_docstring,
kwargs_to_strings,
use_alias,
)
from pygmt.helpers import build_arg_string, fmt_docstring, kwargs_to_strings, use_alias


def data_format_code(convention, component="full"):
Expand Down Expand Up @@ -160,17 +153,14 @@ def meca(
proportional to the magnitude. Scale defines the size for magnitude = 5
(i.e. scalar seismic moment M0 = 4.0E23 dynes-cm)
longitude: int, float, list, or 1d numpy array
Longitude(s) of event location. Ignored if `spec` is not a dictionary.
List must be the length of the number of events. Ignored if `spec` is a
DataFrame and contains a 'longitude' column.
Longitude(s) of event location. Will override the longitudes in ``spec``
if ``spec`` is a dict or DataFrame.
latitude: int, float, list, or 1d numpy array
Latitude(s) of event location. Ignored if `spec` is not a dictionary.
List must be the length of the number of events. Ignored if `spec` is a
DataFrame and contains a 'latitude' column.
Latitude(s) of event location. Will override the latitudes in ``spec``
if ``spec`` is a dict or DataFrame.
depth: int, float, list, or 1d numpy array
Depth(s) of event location in kilometers. Ignored if `spec` is not a
dictionary. List must be the length of the number of events. Ignored if
`spec` is a DataFrame and contains a 'depth' column.
Depth(s) of event location in kilometers. Will override the depths in
``spec`` if ``spec`` is a dict or DataFrame.
convention: str
``"aki"`` (Aki & Richards), ``"gcmt"`` (global CMT), ``"mt"`` (seismic
moment tensor), ``"partial"`` (partial focal mechanism), or
Expand All @@ -181,13 +171,13 @@ def meca(
full seismic moment tensor), ``"dc"`` (the closest double couple with
zero trace and zero determinant), ``"deviatoric"`` (zero trace)
plot_longitude: int, float, list, or 1d numpy array
Longitude(s) at which to place beachball, only used if `spec` is a
dictionary. List must be the length of the number of events. Ignored if
`spec` is a DataFrame and contains a 'plot_longitude' column.
Longitude(s) at which to place beachball. List must be the length of the
number of events. Will override the plot_longitude in ``spec`` if
``spec`` is a dict or DataFrame
plot_latitude: int, float, list, or 1d numpy array
Latitude(s) at which to place beachball, only used if `spec` is a
dictionary. List must be the length of the number of events. Ignored if
`spec` is a DataFrame and contains a 'plot_latitude' column.
Latitude(s) at which to place beachball. List must be the length of the
number of events. Will override the plot_latideu in ``spec`` if ``spec``
is a dict or DataFrame.
offset: bool or str
Offsets beachballs to the longitude, latitude specified in the last two
columns of the input file or array, or by `plot_longitude` and
Expand All @@ -208,48 +198,11 @@ def meca(
{t}
"""

# pylint warnings that need to be fixed
# pylint: disable=too-many-locals
# pylint: disable=too-many-nested-blocks
# pylint: disable=too-many-branches
# pylint: disable=too-many-statements

def set_pointer(data_pointers, spec):
"""
Set optional parameter pointers based on DataFrame or dict, if those
parameters are present in the DataFrame or dict.
"""
for param in list(data_pointers):
if param in spec:
# set pointer based on param name
data_pointers[param] = spec[param]

def update_pointers(data_pointers):
"""
Updates variables based on the location of data, as the following data
can be passed as parameters or it can be contained in `spec`.
"""
# update all pointers
longitude = data_pointers["longitude"]
latitude = data_pointers["latitude"]
depth = data_pointers["depth"]
plot_longitude = data_pointers["plot_longitude"]
plot_latitude = data_pointers["plot_latitude"]
return (longitude, latitude, depth, plot_longitude, plot_latitude)

kwargs = self._preprocess(**kwargs) # pylint: disable=protected-access
# Check the spec and parse the data according to the specified
# convention
if isinstance(spec, (dict, pd.DataFrame)):
# dicts and DataFrames are handed similarly but not identically
if (longitude is None or latitude is None or depth is None) and not isinstance(
spec, (dict, pd.DataFrame)
):
raise GMTError("Location not fully specified.")

param_conventions = {
"AKI": ["strike", "dip", "rake", "magnitude"],
"GCMT": [
"aki": ["strike", "dip", "rake", "magnitude"],
"gcmt": [
"strike1",
"dip1",
"rake1",
Expand All @@ -259,9 +212,9 @@ def update_pointers(data_pointers):
"mantissa",
"exponent",
],
"MT": ["mrr", "mtt", "mff", "mrt", "mrf", "mtf", "exponent"],
"PARTIAL": ["strike1", "dip1", "strike2", "fault_type", "magnitude"],
"PRINCIPAL_AXIS": [
"mt": ["mrr", "mtt", "mff", "mrt", "mrf", "mtf", "exponent"],
"partial": ["strike1", "dip1", "strike2", "fault_type", "magnitude"],
"pricipal_axis": [
"t_exponent",
"t_azimuth",
"t_plunge",
Expand All @@ -274,195 +227,62 @@ def update_pointers(data_pointers):
"exponent",
],
}

# to keep track of where optional parameters exist
data_pointers = {
"longitude": longitude,
"latitude": latitude,
"depth": depth,
"plot_longitude": plot_longitude,
"plot_latitude": plot_latitude,
}

# make a DataFrame copy to check convention if it contains other params
# check if a copy is necessary
copy = False
drop_list = []
for pointer in data_pointers:
if pointer in spec:
copy = True
drop_list.append(pointer)
if copy:
spec_conv = spec.copy()
# delete optional parameters from copy for convention check
for item in drop_list:
del spec_conv[item]
else:
spec_conv = spec

# set convention and focal parameters based on spec convention
for conv in list(param_conventions):
if set(spec_conv) == set(param_conventions[conv]):
convention = conv.lower()
foc_params = param_conventions[conv]
# determine the convention based on dict keys
for conv, paras in param_conventions.items():
if set(paras).issubset(set(spec.keys())):
convention = conv
break
else: # if there is no convention assigned
else:
raise GMTError(
"Parameters in spec dictionary do not match known conventions."
)

# create a dict type pointer for easier to read code
if isinstance(spec, dict):
dict_type_pointer = list(spec.values())[0]
elif isinstance(spec, pd.DataFrame):
# use df.values as pointer for DataFrame behavior
dict_type_pointer = spec.values

# assemble the 1D array for the case of floats and ints as values
if isinstance(dict_type_pointer, (int, float)):
# update pointers
set_pointer(data_pointers, spec)
# look for optional parameters in the right place
(
longitude,
latitude,
depth,
plot_longitude,
plot_latitude,
) = update_pointers(data_pointers)

# Construct the array (order matters)
spec = [longitude, latitude, depth] + [spec[key] for key in foc_params]

# Add in plotting options, if given, otherwise add 0s
for arg in plot_longitude, plot_latitude:
if arg is None:
spec.append(0)
else:
if "A" not in kwargs:
kwargs["A"] = True
spec.append(arg)

# or assemble the 2D array for the case of lists as values
elif isinstance(dict_type_pointer, list):
# update pointers
set_pointer(data_pointers, spec)
# look for optional parameters in the right place
(
longitude,
latitude,
depth,
plot_longitude,
plot_latitude,
) = update_pointers(data_pointers)

# before constructing the 2D array lets check that each key
# of the dict has the same quantity of values to avoid bugs
list_length = len(list(spec.values())[0])
for value in list(spec.values()):
if len(value) != list_length:
raise GMTError(
"Unequal number of focal mechanism "
"parameters supplied in 'spec'."
)
# lets also check the inputs for longitude, latitude,
# and depth if it is a list or array
if (
isinstance(longitude, (list, np.ndarray))
or isinstance(latitude, (list, np.ndarray))
or isinstance(depth, (list, np.ndarray))
):
if (len(longitude) != len(latitude)) or (
len(longitude) != len(depth)
):
raise GMTError(
"Unequal number of focal mechanism " "locations supplied."
)

# values are ok, so build the 2D array
spec_array = []
for index in range(list_length):
# Construct the array one row at a time (note that order
# matters here, hence the list comprehension!)
row = [longitude[index], latitude[index], depth[index]] + [
spec[key][index] for key in foc_params
]

# Add in plotting options, if given, otherwise add 0s as
# required by GMT
for arg in plot_longitude, plot_latitude:
if arg is None:
row.append(0)
else:
if "A" not in kwargs:
kwargs["A"] = True
row.append(arg[index])
spec_array.append(row)
spec = spec_array

# or assemble the array for the case of pd.DataFrames
elif isinstance(dict_type_pointer, np.ndarray):
# update pointers
set_pointer(data_pointers, spec)
# look for optional parameters in the right place
(
longitude,
latitude,
depth,
plot_longitude,
plot_latitude,
) = update_pointers(data_pointers)

# lets also check the inputs for longitude, latitude, and depth
# just in case the user entered different length lists
if (
isinstance(longitude, (list, np.ndarray))
or isinstance(latitude, (list, np.ndarray))
or isinstance(depth, (list, np.ndarray))
):
if (len(longitude) != len(latitude)) or (len(longitude) != len(depth)):
raise GMTError(
"Unequal number of focal mechanism locations supplied."
)

# values are ok, so build the 2D array in the correct order
spec_array = []
for index in range(len(spec)):
# Construct the array one row at a time (note that order
# matters here, hence the list comprehension!)
row = [longitude[index], latitude[index], depth[index]] + [
spec[key][index] for key in foc_params
]

# Add in plotting options, if given, otherwise add 0s as
# required by GMT
for arg in plot_longitude, plot_latitude:
if arg is None:
row.append(0)
else:
if "A" not in kwargs:
kwargs["A"] = True
row.append(arg[index])
spec_array.append(row)
spec = spec_array

else:
raise GMTError("Parameter 'spec' contains values of an unsupported type.")
# prepare for input arrays
# longitude, latitude, depth, focal_parameters, [plot_longitude, plot_latitude] [labels]
arrays = []
# a temporary dict for event locations
loc_spec = {
"longitude": longitude if longitude is not None else spec["longitude"],
"latitude": latitude if latitude is not None else spec["latitude"],
"depth": depth if depth is not None else spec["depth"],
}
# a temporary dict for plotting beachballs
plotloc_spec = {
"plot_longtiude": plot_longitude
if plot_longitude is not None
else spec.get("plot_longitude", None),
"plot_latitude": plot_latitude
if plot_latitude is not None
else spec.get("plot_latitude", None),
}
# reset the plotloc_spec dict to empty if no plotting locations are given
if not all(plotloc_spec.values()):
plotloc_spec = {}

# location arrays
arrays.extend(np.atleast_1d(loc_spec[param]) for param in loc_spec)
# focal parameter arrays
arrays.extend(
np.atleast_1d(spec[param]) for param in param_conventions[convention]
)
# plotting location arrays if given
arrays.extend(np.atleast_1d(plotloc_spec[param]) for param in plotloc_spec)
# TODO: label arrays
# transpose the 2D array
spec = np.atleast_2d(arrays).T

# Convert 1d array types into 2d arrays
if isinstance(spec, np.ndarray) and spec.ndim == 1:
spec = np.atleast_2d(spec)

# determine data_foramt from convection and component
data_format = data_format_code(convention=convention, component=component)

# Assemble -S flag
kwargs["S"] = data_format + scale

kind = data_kind(spec)
with Session() as lib:
if kind == "matrix":
file_context = lib.virtualfile_from_matrix(np.atleast_2d(spec))
elif kind == "file":
file_context = dummy_context(spec)
else:
raise GMTInvalidInput(f"Unrecognized data type: {type(spec)}")
# Choose how data will be passed into the module
file_context = lib.virtualfile_from_data(check_kind="vector", data=spec)
with file_context as fname:
arg_str = " ".join([fname, build_arg_string(kwargs)])
lib.call_module("meca", arg_str)
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