def plot_section(self):
# self.matplotlib_widget.fig.clf()
colormap = self.control_widget.colormap_ComboBox.currentText()
if self.control_widget.wiggle_CheckBox.checkState() == Qt.Checked:
kind = 'vawt'
else:
kind = 'img'
ax = self.matplotlib_widget.axes
ax.cla()
for idx in range(self.control_widget.data_listWidget.count()):
# for data_item in self.control_widget.data_listWidget.items:
item = self.control_widget.data_listWidget.item(idx)
if self.control_widget.il_radioButton.isChecked() is True:
if item.checkState() == Qt.Checked:
data_path = Path(CONF.data_root) / CONF.current_survey / \
"Seismics" / ".{}".format(item.text())
if data_path.exists() is True:
if not hasattr(self, "data_{}".format(item.text())):
# check if data has already been loaded
# create new seis object if not
self.new_seis_object(item.text())
self.status.emit("Reading data ...")
seis_object = getattr(self,
"data_{}".format(item.text()))
self.status.emit("Plotting ...")
seis_object.plot(ppp.InlineIndex(
self.control_widget.inline_SpinBox.value()),
ax,
kind=kind,
cm=colormap)
self.matplotlib_widget.fig.canvas.draw()
self.status.emit("")
else:
self.statusBar().showMessage(
"can not find data file {}".format(item.text))
elif self.control_widget.cl_radioButton.isChecked() is True:
if item.checkState() == Qt.Checked:
data_path = Path(CONF.data_root) / CONF.current_survey / \
"Seismics" / ".{}".format(item.text())
if data_path.exists() is True:
if not hasattr(self, "data_{}".format(item.text())):
# check if data has already been loaded
# create new seis object if not
self.new_seis_object(item.text())
self.status.emit("Reading data ...")
seis_object = getattr(self,
"data_{}".format(item.text()))
self.status.emit("Plotting ...")
seis_object.plot(ppp.CrlineIndex(
self.control_widget.crline_SpinBox.value()),
ax,
kind=kind,
cm=colormap)
self.matplotlib_widget.fig.canvas.draw()
self.status.emit("")
else:
self.statusBar().showMessage(
"can not find data file {}".format(item.text))
def average_to_interval(input_object, output_object):
input_seisegy = ppp.SeiSEGY(str(input_object.path))
output_seisegy = ppp.SeiSEGY(str(output_object.path))
twt = np.array(list(input_seisegy.depths()))
for il in input_seisegy.inlines():
input_data_inline = input_seisegy.inline(il)
output_data_inline = np.copy(input_data_inline)
for idx in range(input_seisegy.nNorth):
output_data_inline[idx] = ppp.avg2int(twt, input_data_inline[idx])
output_seisegy.update(ppp.InlineIndex(il), output_data_inline)
def velocity_to_density_conversion(input_object, output_object, c, d):
input_seisegy = ppp.SeiSEGY(str(input_object.path))
output_seisegy = ppp.SeiSEGY(str(output_object.path))
# twt = np.array(list(input_seisegy.depths()))
for il in input_seisegy.inlines():
input_data_inline = input_seisegy.inline(il)
output_data_inline = np.copy(input_data_inline)
for idx in range(input_seisegy.nNorth):
output_data_inline[idx] = ppp.gardner(input_data_inline[idx], c, d)
output_seisegy.update(ppp.InlineIndex(il), output_data_inline)
def obp_calculation(input_object, output_object):
input_seisegy = ppp.SeiSEGY(str(input_object.path))
stepDepth = input_seisegy.survey_setting.stepDepth
output_seisegy = ppp.SeiSEGY(str(output_object.path))
# depth = np.array(list(input_seisegy.depths()))
for il in input_seisegy.inlines():
input_data_inline = input_seisegy.inline(il)
output_data_inline = np.copy(input_data_inline)
for idx in range(input_seisegy.nNorth):
output_data_inline[idx] = ppp.obp_trace(input_data_inline[idx],
stepDepth)
output_seisegy.update(ppp.InlineIndex(il), output_data_inline)
def test__seisegy():
seis_cube = ppp.SeiSEGY("test/data/f3_sparse.sgy")
# test generators
assert list(seis_cube.inlines()) == list(range(200, 641, 20))
assert list(seis_cube.crlines())[-1] == 1200
assert list(seis_cube.inline_crlines())[-1] == (640, 1200)
assert list(seis_cube.depths())[-1] == 1100
# test retrieve data
first_test_cdp_data = seis_cube.data(ppp.CdpIndex((200, 700)))
assert (seis_cube.data(ppp.InlineIndex(200))[0] == \
first_test_cdp_data).all()
assert (seis_cube.data(ppp.CrlineIndex(700))[0] == \
first_test_cdp_data).all()
assert seis_cube.data(ppp.DepthIndex(1100))[0][0] == \
first_test_cdp_data[-1]
assert seis_cube.valid_cdp((199, 400)) == (200, 400)
assert str(seis_cube) == repr(seis_cube)
def eaton_calculation(obp_object, vel_object, output_object, a, b, n):
obp_seisegy = ppp.SeiSEGY(str(obp_object.path))
vel_seisegy = ppp.SeiSEGY(str(vel_object.path))
output_seisegy = ppp.SeiSEGY(str(output_object.path))
# preparation
depth = np.array(list(obp_seisegy.depths()))
vn = ppp.normal(depth, a, b)
hydrostatic = ppp.hydrostatic_trace(depth)
# actual calcualtion
for il in obp_seisegy.inlines():
obp_data_inline = obp_seisegy.inline(il)
vel_data_inline = vel_seisegy.inline(il)
output_data_inline = np.copy(obp_data_inline)
for idx in range(obp_seisegy.nNorth):
output_data_inline[idx] = ppp.eaton(
vel_data_inline[idx], vn, hydrostatic,
obp_data_inline[idx], n=n)
output_seisegy.update(ppp.InlineIndex(il), output_data_inline)
def bowers_calculation(obp_object, vel_object, output_object, a, b):
obp_seisegy = ppp.SeiSEGY(str(obp_object.path))
vel_seisegy = ppp.SeiSEGY(str(vel_object.path))
output_seisegy = ppp.SeiSEGY(str(output_object.path))
# actual calcualtion
for il in obp_seisegy.inlines():
obp_data_inline = obp_seisegy.inline(il)
vel_data_inline = vel_seisegy.inline(il)
output_data_inline = np.copy(obp_data_inline)
for idx in range(obp_seisegy.nNorth):
output_data_inline[idx] = ppp.bowers(vel_data_inline[idx],
obp_data_inline[idx],
1,
start_idx=-1,
a=a,
b=b,
vmax=5000,
end_idx=None)
output_seisegy.update(ppp.InlineIndex(il), output_data_inline)
def test__InlineIndex():
assert ppp.InlineIndex(1).value == 1
