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Replacing RadClass.RadClass with RadClass.Processor #39

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Merged
gonuke merged 1 commit into from
Nov 20, 2022
Merged

Replacing RadClass.RadClass with RadClass.Processor #39

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6 changes: 3 additions & 3 deletions README.md
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Expand Up @@ -38,12 +38,12 @@ RadClass is designed to be modular, allowing a user to use analysis modules as n
![RadClass Workflow](/images/RadClass_workflow.png)

An HDF5 data file is specified as input, which is processed by `DataSet`. The user can specify a type of `AnalysisParameters`. For example, `H0` for hypothesis testing, `BackgroundEstimator` for background estimation, etc.
`RadClass` then uses `DataSet` and the user specified `AnalysisParameters` to run, storing the results for use by the user.
To see examples of how a user can initialize and run `RadClass`, review /tests/.
`Processor` then uses `DataSet` and the user specified `AnalysisParameters` to run, storing the results for use by the user.
To see examples of how a user can initialize and run `Processor`, review /tests/.

## Data Format

`RadClass` expects a data structure as follows:
`RadClass.Processor` expects a data structure as follows:

![File Structure](/images/file_structure.png)

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2 changes: 1 addition & 1 deletion RadClass/RadClass.py → RadClass/Processor.py
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Expand Up @@ -7,7 +7,7 @@
import RadClass.DataSet as ds


class RadClass:
class Processor:
'''
Bulk handler class. Contains most functions needed for processing data
stream files and pass along to an analysis object.
Expand Down
Binary file modified images/RadClass_workflow.png
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10 changes: 5 additions & 5 deletions tests/test_BackgroundEstimator.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,7 +3,7 @@
import os
from datetime import datetime, timedelta

from RadClass.RadClass import RadClass
from RadClass.Processor import Processor
from RadClass.BackgroundEstimator import BackgroundEstimator
import tests.test_data as test_data

Expand Down Expand Up @@ -40,8 +40,8 @@ def test_estimation():
confidence = 0.8
bckg = BackgroundEstimator(confidence=confidence)
# run handler script
classifier = RadClass(stride, integration, test_data.datapath,
test_data.filename, store_data=True, analysis=bckg)
classifier = Processor(stride, integration, test_data.datapath,
test_data.filename, store_data=True, analysis=bckg)
classifier.run_all()

bckg.estimate()
Expand Down Expand Up @@ -69,8 +69,8 @@ def test_write():
confidence = 0.8
bckg = BackgroundEstimator(confidence=confidence)
# run handler script
classifier = RadClass(stride, integration, test_data.datapath,
test_data.filename, store_data=True, analysis=bckg)
classifier = Processor(stride, integration, test_data.datapath,
test_data.filename, store_data=True, analysis=bckg)
classifier.run_all()

ofilename = 'bckg_test'
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14 changes: 7 additions & 7 deletions tests/test_DiffSpectra.py
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Expand Up @@ -3,7 +3,7 @@
import os
from datetime import datetime, timedelta

from RadClass.RadClass import RadClass
from RadClass.Processor import Processor
from RadClass.DiffSpectra import DiffSpectra
import tests.test_data as test_data

Expand Down Expand Up @@ -34,9 +34,9 @@ def test_difference():
# small stride since there are less data samples in test_data
diff_stride = 2
post_analysis = DiffSpectra(stride=diff_stride)
classifier = RadClass(stride, integration, test_data.datapath,
test_data.filename, post_analysis=post_analysis,
store_data=True)
classifier = Processor(stride, integration, test_data.datapath,
test_data.filename, post_analysis=post_analysis,
store_data=True)
classifier.run_all()

diff_spectra = post_analysis.diff_spectra
Expand Down Expand Up @@ -81,9 +81,9 @@ def test_write():
# small stride since there are less data samples in test_data
diff_stride = 2
post_analysis = DiffSpectra(stride=diff_stride)
classifier = RadClass(stride, integration, test_data.datapath,
test_data.filename, post_analysis=post_analysis,
store_data=True)
classifier = Processor(stride, integration, test_data.datapath,
test_data.filename, post_analysis=post_analysis,
store_data=True)
classifier.run_all()
post_analysis.write(filename)

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18 changes: 9 additions & 9 deletions tests/test_H0.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,7 +3,7 @@
import os
from datetime import datetime, timedelta

from RadClass.RadClass import RadClass
from RadClass.Processor import Processor
from RadClass.H0 import H0
import tests.test_data as test_data

Expand Down Expand Up @@ -49,8 +49,8 @@ def test_gross():

# run handler script with analysis parameter
analysis = H0()
classifier = RadClass(stride, integration, test_data.datapath,
test_data.filename, analysis=analysis)
classifier = Processor(stride, integration, test_data.datapath,
test_data.filename, analysis=analysis)
classifier.run_all()

obs_timestamp = analysis.triggers[0][0]
Expand All @@ -69,8 +69,8 @@ def test_channel():

# run handler script with analysis parameter
analysis = H0(gross=False, energy_bins=test_data.energy_bins)
classifier = RadClass(stride, integration, test_data.datapath,
test_data.filename, analysis=analysis)
classifier = Processor(stride, integration, test_data.datapath,
test_data.filename, analysis=analysis)
classifier.run_all()

obs_timestamp = analysis.triggers[0][0]
Expand All @@ -94,8 +94,8 @@ def test_write_gross():

# run handler script with analysis parameter
analysis = H0()
classifier = RadClass(stride, integration, test_data.datapath,
test_data.filename, analysis=analysis)
classifier = Processor(stride, integration, test_data.datapath,
test_data.filename, analysis=analysis)
classifier.run_all()
analysis.write(filename)

Expand All @@ -115,8 +115,8 @@ def test_write_channel():

# run handler script with analysis parameter
analysis = H0(gross=False, energy_bins=test_data.energy_bins)
classifier = RadClass(stride, integration, test_data.datapath,
test_data.filename, analysis=analysis)
classifier = Processor(stride, integration, test_data.datapath,
test_data.filename, analysis=analysis)
classifier.run_all()
analysis.write(filename)

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75 changes: 37 additions & 38 deletions tests/test_RadClass.py
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Original file line number Diff line number Diff line change
@@ -1,11 +1,10 @@
from multiprocessing.sharedctypes import Value
import numpy as np
import h5py
import pytest
import os
from datetime import datetime, timedelta

from RadClass.RadClass import RadClass
from RadClass.Processor import Processor
import tests.test_data as test_data

# initialize sample data
Expand Down Expand Up @@ -40,9 +39,9 @@ def test_analysis():
integration = int(test_data.timesteps/10)

# run handler script
classifier = RadClass(stride, integration, test_data.datapath,
test_data.filename, analysis=NullAnalysis(),
store_data=False)
classifier = Processor(stride, integration, test_data.datapath,
test_data.filename, analysis=NullAnalysis(),
store_data=False)
classifier.run_all()

np.testing.assert_equal(True, classifier.analysis.changed)
Expand All @@ -55,11 +54,11 @@ def test_init():
cache_size = 10000
stop_time = 2e9

classifier = RadClass(stride=stride, integration=integration,
datapath=test_data.datapath,
filename=test_data.filename, store_data=store_data,
cache_size=cache_size, stop_time=stop_time,
labels=test_data.labels)
classifier = Processor(stride=stride, integration=integration,
datapath=test_data.datapath,
filename=test_data.filename, store_data=store_data,
cache_size=cache_size, stop_time=stop_time,
labels=test_data.labels)

np.testing.assert_equal(stride, classifier.stride)
np.testing.assert_equal(integration, classifier.integration)
Expand All @@ -75,8 +74,8 @@ def test_integration():
integration = int(test_data.timesteps/10)

# run handler script
classifier = RadClass(stride, integration, test_data.datapath,
test_data.filename, store_data=True)
classifier = Processor(stride, integration, test_data.datapath,
test_data.filename, store_data=True)
classifier.run_all()

# the resulting 1-hour observation should be:
Expand All @@ -94,9 +93,9 @@ def test_cache():
cache_size = 100

# run handler script
classifier = RadClass(stride, integration, test_data.datapath,
test_data.filename, store_data=True,
cache_size=cache_size)
classifier = Processor(stride, integration, test_data.datapath,
test_data.filename, store_data=True,
cache_size=cache_size)
classifier.run_all()

# the resulting 1-hour observation should be:
Expand All @@ -113,8 +112,8 @@ def test_stride():
integration = 5

# run handler script
classifier = RadClass(stride, integration, test_data.datapath,
test_data.filename)
classifier = Processor(stride, integration, test_data.datapath,
test_data.filename)
classifier.run_all()

# the resulting 1-hour observation should be:
Expand All @@ -137,8 +136,8 @@ def test_write():
filename = 'test_results'

# run handler script
classifier = RadClass(stride, integration, test_data.datapath,
test_data.filename)
classifier = Processor(stride, integration, test_data.datapath,
test_data.filename)
classifier.run_all()
classifier.write(filename)

Expand Down Expand Up @@ -184,9 +183,9 @@ def test_start():
start_time = timestamps[integration]

# run handler script
classifier = RadClass(stride, integration, test_data.datapath,
test_data.filename, store_data=True,
cache_size=cache_size, start_time=start_time)
classifier = Processor(stride, integration, test_data.datapath,
test_data.filename, store_data=True,
cache_size=cache_size, start_time=start_time)
classifier.run_all()

integration_val = (((2*integration)*(2*integration-1)/2) -
Expand All @@ -212,9 +211,9 @@ def test_stop():
stop_time = timestamps[integration*(periods-1)+1]

# run handler script
classifier = RadClass(stride, integration, test_data.datapath,
test_data.filename, store_data=True,
cache_size=cache_size, stop_time=stop_time)
classifier = Processor(stride, integration, test_data.datapath,
test_data.filename, store_data=True,
cache_size=cache_size, stop_time=stop_time)
classifier.run_all()

integration_val = (((integration*(periods-1)) *
Expand All @@ -238,9 +237,9 @@ def test_max_stop():
stop_time = timestamps[-1]+1000.0

# run handler script
classifier = RadClass(stride, integration, test_data.datapath,
test_data.filename, store_data=True,
stop_time=stop_time)
classifier = Processor(stride, integration, test_data.datapath,
test_data.filename, store_data=True,
stop_time=stop_time)
classifier.run_all()

# the resulting 1-hour observation should be:
Expand All @@ -259,23 +258,23 @@ def test_bad_start_stop():
# Checks if start_time > stop_time
start_time = timestamps[1]
stop_time = timestamps[0]
classifier = RadClass(stride, integration, test_data.datapath,
test_data.filename, start_time=start_time,
stop_time=stop_time)
classifier = Processor(stride, integration, test_data.datapath,
test_data.filename, start_time=start_time,
stop_time=stop_time)
with pytest.raises(ValueError):
classifier.queue_file()

# checks if start_time > last timestamp
start_time = timestamps[-1] + 1000.0
classifier = RadClass(stride, integration, test_data.datapath,
test_data.filename, start_time=start_time)
classifier = Processor(stride, integration, test_data.datapath,
test_data.filename, start_time=start_time)
with pytest.raises(ValueError):
classifier.queue_file()

# checks if stop_time < first timestamp
stop_time = timestamps[0] - 1000.0
classifier = RadClass(stride, integration, test_data.datapath,
test_data.filename, stop_time=stop_time)
classifier = Processor(stride, integration, test_data.datapath,
test_data.filename, stop_time=stop_time)
with pytest.raises(ValueError):
classifier.queue_file()

Expand All @@ -287,8 +286,8 @@ def test_equal_start_stop():
# Checks if start_time = stop_time
start_time = timestamps[0]
stop_time = timestamps[0]
classifier = RadClass(stride, integration, test_data.datapath,
test_data.filename, start_time=start_time,
stop_time=stop_time)
classifier = Processor(stride, integration, test_data.datapath,
test_data.filename, start_time=start_time,
stop_time=stop_time)
with pytest.raises(RuntimeWarning):
classifier.queue_file()