From 8aefe1056fb83ace65c3dcdc4273ed174a95d154 Mon Sep 17 00:00:00 2001
From: pcain-usgs <pcain@usgs.gov>
Date: Tue, 28 Jan 2020 15:11:59 -0700
Subject: [PATCH] Fixes continuation indenting, initialization of
custom/default filter, and starttime equation for custom filter
---
geomagio/algorithm/FilterAlgorithm.py | 45 +++++++++++++++------------
1 file changed, 25 insertions(+), 20 deletions(-)
diff --git a/geomagio/algorithm/FilterAlgorithm.py b/geomagio/algorithm/FilterAlgorithm.py
index 74b9478d0..b59527e73 100644
--- a/geomagio/algorithm/FilterAlgorithm.py
+++ b/geomagio/algorithm/FilterAlgorithm.py
@@ -19,6 +19,7 @@ class FilterAlgorithm(Algorithm):
Algorithm.__init__(self, inchannels=None, outchannels=None)
self.window = window
+ self.steparr = steparr
self.coeff_filename = coeff_filename
self.filtertype = filtertype
self.numtaps = numtaps
@@ -26,12 +27,27 @@ class FilterAlgorithm(Algorithm):
self.bin_conv = bin_conv
self.input_sample_period = input_sample_period
self.output_sample_period = output_sample_period
+
+ # Initialize filter to execute filtering step with custom coefficients
+ if self.filtertype == 'custom':
+ self.load_state()
+ self.decimation = int(self.output_sample_period /
+ self.input_sample_period)
+ self.numtaps = len(self.window)
+ # initialize filter to execute cascading filtering steps
+ else:
+ self.steparr = np.array([0.1, 1, 60, 3600])
+ self.window = [sps.firwin(123, 0.45 / 5.0, window='blackman'),
+ sps.get_window(window=('gaussian', 15.8734), Nx=91),
+ sps.windows.boxcar(91)]
+ self.decimation = np.array([1, 10, 60, 60])
+ self.numtaps = np.array([123, 91, 91])
+
# Set volt/bin conversions to defaults if using Python
if self.volt_conv is None:
self.volt_conv = 100
if self.bin_conv is None:
self.bin_conv = 500
- self.steparr = np.array([0.1, 1, 60, 3600])
def load_state(self):
"""Load algorithm state from a file.
@@ -101,39 +117,28 @@ class FilterAlgorithm(Algorithm):
# if input stream is 10 Hz, convert data to nT
if self.input_sample_period == 0.1:
stream = self.convert_miniseed(stream)
+
output_sample_period = self.output_sample_period
input_sample_period = self.input_sample_period
out = Stream()
# perform one filter operation for custom type filter
if self.filtertype == 'custom':
- self.decimation = int(output_sample_period /
- input_sample_period)
- self.load_state()
- self.numtaps = len(self.window)
for trace in stream:
data = trace.data
- step = int(output_sample_period /
- input_sample_period)
+ step = self.decimation
filtered = self.firfilter(data, self.window, step)
stats = Stats(trace.stats)
- self.numtaps = len(self.window)
stats.starttime = trace.stats.starttime + \
- self.numtaps * self.input_sample_period // \
- 2 + self.input_sample_period
+ + self.numtaps * self.input_sample_period // 2 + \
+ + self.input_sample_period
stats.delta = stats.delta * step
stats.npts = filtered.shape[0]
trace_out = self.create_trace(
- stats.channel, stats, filtered)
+ stats.channel, stats, filtered)
out += trace_out
return out
- # initialize filter to execute cascading filtering steps
- self.window = [sps.firwin(123, 0.45 / 5.0, window='blackman'),
- sps.get_window(window=('gaussian', 15.8734), Nx=91),
- sps.windows.boxcar(91)]
- self.decimation = np.array([1, 10, 60, 60])
- self.numtaps = np.array([123, 91, 91])
# set stop index to where the sampling period in steparr
# equals the desired output sample period
stop_idx = np.argwhere(self.steparr == self.output_sample_period)[0][0]
@@ -148,7 +153,7 @@ class FilterAlgorithm(Algorithm):
# timeshift value summing all shift to the starttime required in
# each step to receive desired timeseries
timeshift = sum(np.array(self.steparr[start_idx:stop_idx]) *
- (np.array(self.numtaps[start_idx:stop_idx]) // 2))
+ (np.array(self.numtaps[start_idx:stop_idx]) // 2))
while start_idx != stop_idx:
# set input_sample_period to next filtering step
input_sample_period = self.steparr[start_idx]
@@ -309,8 +314,8 @@ class FilterAlgorithm(Algorithm):
# input and output time intervals are managed by Controller
parser.add_argument('--filter-type',
- help='Specify default filters or custom filter',
- choices=['default', 'custom'])
+ help='Specify default filters or custom filter',
+ choices=['default', 'custom'])
parser.add_argument('--filter-coefficients',
help='File storing custom filter coefficients')
--
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