vikinganalytics · pro100watt · Apr 4, 2023 · Mar 29, 2023 · Mar 29, 2023 · Mar 30, 2023
diff --git a/.pylintrc b/.pylintrc
@@ -1,6 +1,7 @@
 [pylint]
+extension-pkg-whitelist=pydantic
 disable =
-    R0904,
+    too-many-public-methods,
     too-few-public-methods,
     too-many-arguments,
     logging-fstring-interpolation,

diff --git a/mvg/mvg.py b/mvg/mvg.py
@@ -21,6 +21,7 @@
 
 from mvg.exceptions import MVGConnectionError
 from mvg.utils.response_processing import (
+    FrequencyRange,
     SortOrder,
     get_paginated_analysis_results,
     get_paginated_items,
@@ -61,7 +62,7 @@ def __init__(self, endpoint: str, token: str):
         self.endpoint = endpoint
         self.token = token
 
-        self.mvg_version = self.parse_version("v0.14.6")
+        self.mvg_version = self.parse_version("v0.14.7")
         self.tested_api_version = self.parse_version("v0.5.12")
 
         # Get API version
@@ -281,6 +282,49 @@ def create_source(
         source_info = {"source_id": sid, "meta": meta, "channels": channels}
         self._request("post", "/sources/", do_not_raise, json=source_info)
 
+    def create_spectrum_source(
+        self,
+        sid: str,
+        channels: List[str],
+        meta: dict = None,
+        exist_ok: bool = False,
+    ):
+        """
+        Creates a spectrum source on the server side.
+
+        Parameters
+        ----------
+        sid : str
+            Source ID
+
+        channels : List[str]
+            Channels of spectrum Data. For instance axial, vertical and horizontal.
+            Channel names must be unique.
+            Cannot be updated after creating source.
+
+        meta : dict
+            Meta information of source [optional].
+
+        exist_ok : bool
+            Set to true to prevent exceptions for 409 Conflict errors
+            caused by trying to create an existing source. Defaults to False.
+        """
+
+        logger.info("endpoint %s", self.endpoint)
+        logger.info("creating spectrum source with source id=%s", sid)
+        logger.info("metadata: %s", meta)
+        logger.info("channels: %s", channels)
+
+        if meta is None:
+            meta = {}
+
+        do_not_raise = []
+        if exist_ok:
+            do_not_raise.append(requests.codes["conflict"])  # 409
+
+        source_info = {"source_id": sid, "meta": meta, "channels": channels}
+        self._request("post", "/sources/spectrum", do_not_raise, json=source_info)
+
     def create_tabular_source(
         self,
         sid: str,
@@ -471,6 +515,75 @@ def create_measurement(
             "post", f"/sources/{sid}/measurements", do_not_raise, json=meas_struct
         )
 
+    def create_spectrum_measurement(
+        self,
+        sid: str,
+        freq_range: FrequencyRange,
+        timestamp: int,
+        data: Dict[str, List[float]],
+        meta: dict = None,
+        exist_ok: bool = False,
+    ):
+        """Stores a measurement on the server side.
+
+        Although it is up to the client side to handle the
+        scaling of data it is recommended that the values
+        represent the acceleration in g.
+        The timestamp shall represent the time when the measurement was
+        recorded.
+
+        Parameters
+        ----------
+        sid: str
+            source Id.
+
+        freq_range: FrequencyRange
+            lowest and highest frequency available in the spectrum as a list [MIN, MAX].
+
+        timestamp: int
+            in milliseconds since EPOCH.
+
+        data: Dict[str, List[float]]
+            Data on the format {channel: values}.
+            This format can be generated by pandas.DataFrame.to_dict("list").
+
+        meta: dict
+            Meta information to attach to data [optional].
+
+        exist_ok: bool
+            Set to true to prevent exceptions for 409 Conflict errors
+            caused by trying to create an existing measurement. Defaults to False.
+        """
+
+        logger.info("endpoint %s", self.endpoint)
+        logger.info("creating spectrum measurement for source id=%s", sid)
+        logger.info("  freq_range: %s", freq_range)
+        logger.info("  timestamp: %s", timestamp)
+        logger.info("  meta data: %s", meta)
+
+        if meta is None:
+            meta = {}
+
+        do_not_raise = []
+        if exist_ok:
+            do_not_raise.append(requests.codes["conflict"])  # 409
+
+        meas_struct = [
+            {
+                "timestamp": timestamp,
+                "freq_range": freq_range,
+                "data": data,
+                "meta": meta,
+            }
+        ]
+
+        self._request(
+            "post",
+            f"/sources/{sid}/measurements/spectrum",
+            do_not_raise,
+            json=meas_struct,
+        )
+
     def create_tabular_measurement(
         self,
         sid: str,

diff --git a/mvg/plotting.py b/mvg/plotting.py
@@ -81,7 +81,7 @@ def modes_boxplot(data, feature, request_id, total_modes=None, axes=None):
     modes = modes.astype("category")
     data["Modes"] = data["labels"].copy()
     data["Modes"] = data["Modes"].astype("category")
-    data["Modes"].cat.set_categories(modes.tolist(), inplace=True)
+    data["Modes"] = data["Modes"].cat.set_categories(modes.tolist())
 
     # Plot and format figure
     image = data.boxplot(column=feature, by="Modes", ax=axes)

diff --git a/mvg/utils/response_processing.py b/mvg/utils/response_processing.py
@@ -5,6 +5,10 @@
 from enum import Enum
 from typing import Dict, Callable
 
+from pydantic import conlist
+
+FrequencyRange = conlist(float, min_items=2, max_items=2)
+
 
 class SortOrder(Enum):
     ASC = "asc"

diff --git a/requirements.txt b/requirements.txt
@@ -5,3 +5,4 @@ numpy
 semver
 matplotlib
 tabulate
+pydantic
diff --git a/requirements_dev.txt b/requirements_dev.txt
@@ -13,3 +13,4 @@ pytest-cov
 # for callback test server
 uvicorn==0.16.0
 fastapi
+scipy
diff --git a/tests/conftest.py b/tests/conftest.py
@@ -1,19 +1,20 @@
+import argparse
+import json
 import os
+import sys
 from pathlib import Path
 
+import pandas as pd
 import pytest
 import requests
-import uuid
-import json
-import pandas as pd
+
 from mvg import MVG
 from mvg.exceptions import MVGAPIError
-
-import argparse
-import sys
-
 from tests.helpers import (
+    generate_random_source_id,
     generate_sources_patterns,
+    make_channel_names,
+    simulate_spectrum_data,
     stub_multiaxial_data,
     upload_measurements,
 )
@@ -54,9 +55,9 @@ def pytest_addoption(parser):
 
 # Pytest initial configuration
 def pytest_configure():
-    pytest.SOURCE_ID_WAVEFORM = uuid.uuid1().hex
+    pytest.SOURCE_ID_WAVEFORM = generate_random_source_id()
     pytest.REF_DB_PATH = Path.cwd() / "tests" / "test_data" / "mini_charlie"
-    pytest.SOURCE_ID_TABULAR = uuid.uuid1().hex
+    pytest.SOURCE_ID_TABULAR = generate_random_source_id()
     pytest.VALID_TOKEN = os.environ["TEST_TOKEN"]
 
 
@@ -226,6 +227,51 @@ def fixture(session):
 )
 
 
+def make_spectrum_source_fixture(pattern, n_channels=1):
+    @pytest.fixture
+    def fixture(session: MVG):
+        sid = generate_random_source_id()
+        channels = make_channel_names(n_channels=n_channels)
+
+        source_info = {"sid": sid, "channels": channels, "meta": {}}
+        session.create_spectrum_source(**source_info)
+        timestamps = []
+        measurements = []
+        if pattern:
+            timestamps, measurements = simulate_spectrum_data(
+                pattern=pattern, channels=channels
+            )
+            for meas in measurements:
+                session.create_spectrum_measurement(
+                    sid=sid,
+                    freq_range=meas["freq_range"],
+                    timestamp=meas["timestamp"],
+                    data=meas["data"],
+                    meta=meas["meta"],
+                )
+
+        info = {
+            "measurements": measurements,
+            "timestamps": timestamps,
+            "pattern": pattern,
+            "channels": channels,
+            "meta": source_info["meta"],
+        }
+        try:
+            yield sid, info
+        finally:
+            session.delete_source(sid)
+
+    return fixture
+
+
+spectrum_source_with_zero_measurements = make_spectrum_source_fixture(pattern=[])
+
+spectrum_source_with_measurements = make_spectrum_source_fixture(
+    pattern=7 * [0] + 15 * [1]
+)
+
+
 @pytest.fixture()
 def tabular_source(session):
     source_id = pytest.SOURCE_ID_TABULAR

diff --git a/tests/helpers.py b/tests/helpers.py
@@ -1,9 +1,21 @@
+from typing import List
+import uuid
 from itertools import cycle
+
 import numpy as np
+from scipy import fft
 
 from mvg.mvg import MVG
 
 
+def generate_random_source_id():
+    return uuid.uuid1().hex
+
+
+def make_channel_names(n_channels):
+    return [f"acc_{i}" for i in range(n_channels)]
+
+
 def upload_measurements(session: MVG, sid: str, data: list):
     """Upload measurements for a source"""
     timestamps = list(data.keys())
@@ -14,6 +26,29 @@ def upload_measurements(session: MVG, sid: str, data: list):
         )
 
 
+def FFT(data, sample_freq) -> list():
+    """Calculates FFT of the given time-series data.
+
+    Parameters
+    ----------
+    data : array
+           data to be transformed.
+    sample_freq : float
+         sampling frequency.
+
+    Returns
+    -------
+    tuple : the frequency range and FFT
+    """
+    N = len(data)  # Number of samples
+    T = 1 / sample_freq  # Sample spacing
+    xf = np.linspace(0.0, 1.0 / (2.0 * T), int(N / 2))  # Creates frequency vector
+    yf = fft.rfft(data)  # Performs FFT
+    # FFTpeak is currently calculated, to calculate FFTrms reaplce 2.0 by np.sqrt(2)
+    abs_yf = (2.0 / N) * np.absolute(yf[: N // 2])  # Calculates norm
+    return xf, abs_yf
+
+
 def stub_multiaxial_data(samp_freq=3000, duration=3.0, pattern={}):
     """Create measurements based on cosine signals (with added noise) for a multiaxial source.
 
@@ -37,7 +72,7 @@ def stub_multiaxial_data(samp_freq=3000, duration=3.0, pattern={}):
 
     Examples
     --------
-    >>> pattern = {'acc_x': [0] * 1 + [1] * 1, 'acc_x': [0] * 2, 'acc_z': [1] * 2}
+    >>> pattern = {'acc_x': [0] * 1 + [1] * 1, 'acc_y': [0] * 2, 'acc_z': [1] * 2}
     >>> timestamps, data, duration = stub_multiaxial_data()
     >>> print(data)
     {0: {"data": {"acc_x": [...], "acc_y": [...], "acc_z": [...]}, "meta": {}}, 3600000: {"data": {"acc_x": [...], "acc_y": [...], "acc_z": [...]}, "meta": {}}}
@@ -86,6 +121,35 @@ def stub_multiaxial_data(samp_freq=3000, duration=3.0, pattern={}):
     return timestamps, data, duration
 
 
+def simulate_spectrum_data(pattern, channels, sample_freq=3000):
+    channels_pattern = {channel: pattern for channel in channels}
+
+    timestamps, data, _ = stub_multiaxial_data(
+        samp_freq=sample_freq, pattern=channels_pattern
+    )
+
+    measurements: List[dict] = []
+    for timestamp in timestamps:
+        waveform_data = data[timestamp]["data"]
+        spectrum_data = {}
+        for channel, channel_data in waveform_data.items():
+            # convert the waveform data in each channel to its
+            # respective spectrum
+            _, fft_y = FFT(channel_data, sample_freq)
+            spectrum_data[channel] = list(fft_y)
+
+        measurements.append(
+            {
+                "timestamp": timestamp,
+                "freq_range": [0, sample_freq],
+                "meta": {},
+                "data": spectrum_data,
+            }
+        )
+
+    return ti
57B2
mestamps, measurements
+
+
 def generate_sources_patterns():
     """Generate a list of multiaxial sources with axis-based patterns"""
     sources_patterns = [
-Original file line number
+Diff line change
@@ Expand Up / @@ -13,3 +13,4 @@ pytest-cov @@
     # for callback test server
     uvicorn==0.16.0
     fastapi
+    scipy