From c9176a064e6a5cf83bc1dd2c1fd416266e501e6b Mon Sep 17 00:00:00 2001
From: Christian Darsow Fromm <cdarsowf@physnet.uni-hamburg.de>
Date: Mon, 5 Aug 2019 18:55:56 +0200
Subject: [PATCH] Resolve "Modematching analyzing script"
---
.gitignore | 1 +
.gitlab-ci.yml | 2 +-
.pylintrc | 2 +-
doc/analysis.rst | 8 +
setup.cfg | 2 +-
src/openqlab/analysis/modematching.py | 109 ++
src/tests/modematching/opo_scan.csv | 2002 +++++++++++++++++++++++++
src/tests/test_modematching.py | 40 +
watch_tests.local.sh | 2 +-
9 files changed, 2164 insertions(+), 4 deletions(-)
create mode 100644 src/openqlab/analysis/modematching.py
create mode 100644 src/tests/modematching/opo_scan.csv
create mode 100644 src/tests/test_modematching.py
diff --git a/.gitignore b/.gitignore
index 6b6df68..2f5618b 100644
--- a/.gitignore
+++ b/.gitignore
@@ -23,3 +23,4 @@ src/tests/test_io/gzip_data_files/
*.gz
\.dmypy\.json
+TestCSV*
diff --git a/.gitlab-ci.yml b/.gitlab-ci.yml
index 6ce0e97..ff85a53 100644
--- a/.gitlab-ci.yml
+++ b/.gitlab-ci.yml
@@ -53,7 +53,7 @@ test:
- src/tests/htmlcov
expire_in: 30 days
-codequality:
+.codequality:
image: lasnq/openqlab
stage: test
allow_failure: true
diff --git a/.pylintrc b/.pylintrc
index 5cf64a8..23f1840 100644
--- a/.pylintrc
+++ b/.pylintrc
@@ -313,7 +313,7 @@ indent-after-paren=4
indent-string=' '
# Maximum number of characters on a single line.
-max-line-length=160
+max-line-length=100
# Maximum number of lines in a module.
max-module-lines=1000
diff --git a/doc/analysis.rst b/doc/analysis.rst
index 69e3443..5fc76d6 100644
--- a/doc/analysis.rst
+++ b/doc/analysis.rst
@@ -16,6 +16,14 @@ Fit beam data obtained from a beam analyzer to the gaussian beam model using non
.. automodule:: openqlab.analysis.gaussian_beam
:members:
+Mode Matching
+-------------
+
+Mode matching calculations
+
+.. automodule:: openqlab.analysis.modematching
+ :members:
+
Phase
-----
diff --git a/setup.cfg b/setup.cfg
index 49428e1..687c517 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -89,6 +89,6 @@ version = 3.0.3
package = openqlab
[pycodestyle]
-max-line-length = 160
+max-line-length = 100
statistics = True
exclude = OldImporters
diff --git a/src/openqlab/analysis/modematching.py b/src/openqlab/analysis/modematching.py
new file mode 100644
index 0000000..8121162
--- /dev/null
+++ b/src/openqlab/analysis/modematching.py
@@ -0,0 +1,109 @@
+"""Automatically calculate modematchings with data taken from an oscilloscope."""
+
+from typing import Optional
+import logging as log
+from pandas import Series
+from scipy.signal import find_peaks
+import numpy as np
+import matplotlib.pyplot as plt
+
+
+def calculate(data: Series, # pylint: disable=invalid-name
+ plot: bool = False,
+ U_max: Optional[float] = None,
+ offset: Optional[float] = None, rel_prominence: float = .02) -> float:
+ """Calculate the mode matching.
+
+ It assumes a cavity scan bounded by two peaks of the main mode.
+ The method looks for the smaller peaks where the detection threshold
+ can be adjusted with :obj:`rel_prominence`.
+
+ Offset
+ The default method to find out the offset is by calculating the mean value.
+ If you have measured it more precisely, use the parameter :obj:`offset`.
+
+ Improve precision
+ To get a better resolution for small peaks there is an option to take data
+ with a clipped main mode. Use the parameter :obj:`U_max` to manually set
+ the measured maximum value.
+
+ Parameters
+ ----------
+
+ data : Series
+ Measured data (just one column).
+ plot : bool
+ Make a plot to see, if the correct peaks where detected.
+ U_max : Optional[float]
+ U_max is the parameter to set the peak voltage of the clipped main peak.
+ rel_prominence : float
+ rel_prominence is the parameter to adjust the threshold for the detection
+ of small peaks.
+
+ Returns
+ -------
+
+ float
+ Calculated mode matching value.
+ """
+ if len(data.shape) != 1:
+ raise ValueError('The DataFrame should only contain one single column.')
+ data = data.dropna()
+
+ # Adjust offset
+ if offset is None:
+ offset = np.median(data)
+ data -= offset
+
+ # Make peaks positive if necessary
+ _adjust_peak_sign(data)
+
+ # Find highest value
+ max_value = np.max(data)
+ if U_max is None:
+ U_max = max_value
+ else:
+ U_max = abs(U_max - offset)
+
+ # Find peaks
+ peaks, peak_dict = find_peaks(data, prominence=U_max*rel_prominence)
+
+ # Find occurences of the main mode. Two are assumed
+ main_mode = np.where(peak_dict['prominences'] >= max_value*.9)[0]
+ if len(main_mode) != 2:
+ raise ValueError('The main mode must occur exactly two times for the algorithm to work, '
+ f'but it found {len(main_mode)} main modes.')
+
+ # Main peak voltage
+ log.info(f'U_max: {U_max}')
+ # Sum of all different modes (excluding 2nd main mode)
+ U_sum = sum(data.iloc[peaks[main_mode[0]+1:main_mode[1]]], U_max) # pylint: disable=invalid-name
+ # This version with U_max makes it possible to manually
+ # include a clipped value for the main peak
+ log.info(f'U_sum: {U_sum}')
+
+ # Mode matching
+ modematching = U_max / U_sum
+
+ # Plotting
+ if plot:
+ index_first, index_last = peaks[main_mode]
+ axes = data.plot()
+ plt.axvline(x=data.index[index_first], color='gray')
+ plt.axvline(x=data.index[index_last], color='gray')
+ plt.axvspan(data.index[0], data.index[index_first], color='gray', alpha=0.5)
+ plt.axvspan(data.index[index_last], data.index[-1], color='gray', alpha=0.5)
+ data.iloc[peaks].plot(style='.')
+ data.iloc[peaks[main_mode]].plot(style='o')
+
+ axes.set_xlim(data.index[0], data.index[-1])
+
+ return modematching
+
+
+def _adjust_peak_sign(data: Series):
+ minimum = np.min(data)
+ maximum = np.max(data)
+
+ if abs(minimum) > abs(maximum):
+ data *= -1
diff --git a/src/tests/modematching/opo_scan.csv b/src/tests/modematching/opo_scan.csv
new file mode 100644
index 0000000..3277c43
--- /dev/null
+++ b/src/tests/modematching/opo_scan.csv
@@ -0,0 +1,2002 @@
+x-axis,1,2,3,4
+second,Volt,Volt,Volt,Volt
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diff --git a/src/tests/test_modematching.py b/src/tests/test_modematching.py
new file mode 100644
index 0000000..0de6275
--- /dev/null
+++ b/src/tests/test_modematching.py
@@ -0,0 +1,40 @@
+import unittest
+import matplotlib.pyplot as plt
+from openqlab import analysis, io
+from openqlab.analysis.modematching import calculate
+
+
+class TestModematching(unittest.TestCase):
+ def setUp(self):
+ self.data = io.read('modematching/opo_scan.csv')
+
+ def test_default_inverted(self):
+ result = calculate(self.data['opo_scan_2'], plot=True)
+ # plt.show()
+ self.assertAlmostEqual(result, .955, places=2)
+
+ def test_default_not_inverted(self):
+ self.data *= -1
+ result = calculate(self.data['opo_scan_2'], plot=True)
+ self.assertAlmostEqual(result, .955, places=2)
+
+ def test_to_many_columns(self):
+ with self.assertRaisesRegex(ValueError, 'only contain one single'):
+ calculate(self.data)
+
+ def test_with_clipped_data(self):
+ self.data.clip(lower=-1, upper=1, inplace=True)
+ result = calculate(self.data['opo_scan_2'], U_max=6.668)
+ self.assertAlmostEqual(result, .955, places=2)
+
+ def test_fail_with_only_one_peak(self):
+ with self.assertRaises(ValueError) as err:
+ calculate(self.data['opo_scan_2'].loc[:.01])
+ self.assertEqual(err.exception.args[0],
+ 'The main mode must occur exactly two times for the algorithm to work, but it found 1 main modes.')
+
+ def test_with_much_offset(self):
+ self.data *= -1
+ self.data -= 2
+ result = calculate(self.data['opo_scan_2'], U_max=6.668-2, offset=-1.98, plot=True)
+ self.assertAlmostEqual(result, .955, places=2)
diff --git a/watch_tests.local.sh b/watch_tests.local.sh
index 4c1f40e..8222f44 100755
--- a/watch_tests.local.sh
+++ b/watch_tests.local.sh
@@ -2,5 +2,5 @@
while true
do
inotifywait -e modify src/**/*.py
- make mypy && make test && make pylint
+ make mypy && make test
done
--
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