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feat: histogram creation and training report

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Derisis13
2024-10-06 22:58:24 +02:00
parent 29e6a86d3d
commit aea4816827
3 changed files with 103 additions and 1 deletions
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19
create_histogram.py Normal file
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@@ -0,0 +1,19 @@
import json
import matplotlib.pyplot as plt
import numpy as np
if __name__ == "__main__":
with open("training_report.json") as jsonfile:
from_json = json.load(jsonfile)
values = np.array(list(from_json.values()))
values = values.__abs__()
fig,ax = plt.subplots()
ax.hist(values, bins=200 )
# ax.set_xscale('log')
ax.set_yscale('log')
ax.set_ylabel('Number of detections')
ax.set_xlabel('Error (s)')
ax.set_title(f'Histogram of error relative to marked start over the training dataset', fontweight='bold')
plt.show()

7
detect_moonquakes.py
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@@ -5,6 +5,7 @@ import create_matched_filter
import matplotlib.pyplot as plt import matplotlib.pyplot as plt
from pathlib import Path from pathlib import Path
from tqdm import tqdm from tqdm import tqdm
import json
IMGDIR = "./images" IMGDIR = "./images"
@@ -19,6 +20,7 @@ def main():
matched_filter = create_matched_filter.create_matched_filter() matched_filter = create_matched_filter.create_matched_filter()
outfolder = Path(IMGDIR + "/lunar/training/") outfolder = Path(IMGDIR + "/lunar/training/")
outfolder.mkdir(parents=True, exist_ok=True) outfolder.mkdir(parents=True, exist_ok=True)
data = {}
for row in tqdm(CAT_LUNAR.iloc): for row in tqdm(CAT_LUNAR.iloc):
arrival_time = datetime.strptime(row['time_abs(%Y-%m-%dT%H:%M:%S.%f)'],'%Y-%m-%dT%H:%M:%S.%f') arrival_time = datetime.strptime(row['time_abs(%Y-%m-%dT%H:%M:%S.%f)'],'%Y-%m-%dT%H:%M:%S.%f')
test_filename = row.filename test_filename = row.filename
@@ -29,7 +31,8 @@ def main():
test_filename = test_filename.replace('HR00', 'HR02') test_filename = test_filename.replace('HR00', 'HR02')
st, arrival = from_mseed(test_filename, LUNAR_DATA_DIR, arrival_time) st, arrival = from_mseed(test_filename, LUNAR_DATA_DIR, arrival_time)
estimated_arrival, likelyhood = do_detection(st, matched_filter) estimated_arrival, likelyhood = do_detection(st, matched_filter)
print(arrival - estimated_arrival) diff = (arrival - estimated_arrival)
data.update({test_filename: diff})
# Plot trace # Plot trace
outfile = outfolder.joinpath(test_filename + "_correlation.png") outfile = outfolder.joinpath(test_filename + "_correlation.png")
fig,ax = plt.subplots(1,1,figsize=(20,6)) fig,ax = plt.subplots(1,1,figsize=(20,6))
@@ -43,6 +46,8 @@ def main():
# plt.show() # plt.show()
plt.savefig(outfile) plt.savefig(outfile)
plt.close(fig) plt.close(fig)
with open("training_report.json", "w") as jsonfile:
json.dump(data, jsonfile, indent=2)
if __name__ == "__main__": if __name__ == "__main__":

78
training_report.json Normal file
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@@ -0,0 +1,78 @@
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