Merge pull request #106 from fronzbot/refactor-tests

Refactor tests

Author: fronzbot

.DS_Store

@@ -0,0 +1 @@
+"""Init file for tests."""

__init__.py

@@ -0,0 +1,152 @@
+"""Spectral analysis helper module."""
+
+import numpy as np
+
+
+def db_to_pow(value, places=3):
+    """Convert dBW to W."""
+    if isinstance(value, np.ndarray):
+        return np.round(10 ** (0.1 * value), places)
+    return round(10 ** (0.1 * value), places)
+
+
+def dBW(value, places=1):
+    """Convert to dBW."""
+    if isinstance(value, np.ndarray):
+        return np.round(10 * np.log10(value), places)
+    return round(10 * np.log10(value), places)
+
+
+def enob(sndr, places=1):
+    """Return ENOB for given SNDR."""
+    return round((sndr - 1.76) / 6.02, places)
+
+
+def sndr_sfdr(spectrum, freq, fs, nfft, leak, full_scale=0):
+    """Get SNDR and SFDR."""
+
+    # Zero the DC bin
+    for i in range(0, leak + 1):
+        spectrum[i] = 0
+    bin_sig = np.argmax(spectrum)
+    psig = sum(spectrum[i] for i in range(bin_sig - leak, bin_sig + leak + 1))
+    spectrum_n = spectrum.copy()
+    spectrum_n[bin_sig] = 0
+    fbin = fs / nfft
+
+    for i in range(bin_sig - leak, bin_sig + leak + 1):
+        spectrum_n[i] = 0
+
+    bin_spur = np.argmax(spectrum_n)
+    pspur = spectrum[bin_spur]
+
+    noise_power = sum(spectrum_n)
+    noise_floor = 2 * noise_power / nfft
+
+    stats = {}
+
+    stats["sig"] = {
+        "freq": freq[bin_sig],
+        "bin": bin_sig,
+        "power": psig,
+        "dB": dBW(psig),
+        "dBFS": round(dBW(psig) - full_scale, 1),
+    }
+
+    stats["spur"] = {
+        "freq": freq[bin_spur],
+        "bin": bin_spur,
+        "power": pspur,
+        "dB": dBW(pspur),
+        "dBFS": round(dBW(pspur) - full_scale, 1),
+    }
+    stats["noise"] = {
+        "floor": noise_floor,
+        "power": noise_power,
+        "rms": np.sqrt(noise_power),
+        "dBHz": round(dBW(noise_floor, 3) - full_scale, 1),
+        "NSD": round(dBW(noise_floor, 3) - full_scale - 2 * dBW(fbin, 3), 1),
+    }
+    stats["sndr"] = {
+        "dBc": dBW(psig / noise_power),
+        "dBFS": round(full_scale - dBW(noise_power), 1),
+    }
+    stats["sfdr"] = {
+        "dBc": dBW(psig / pspur),
+        "dBFS": round(full_scale - dBW(pspur), 1),
+    }
+    stats["enob"] = {"bits": enob(stats["sndr"]["dBFS"])}
+
+    return stats
+
+
+def find_harmonics(spectrum, freq, nfft, bin_sig, psig, harms=5, leak=20, fscale=1e6):
+    """Get the harmonic contents of the data."""
+    harm_stats = {"harm": {}}
+    harm_index = 2
+    for harm in bin_sig * np.arange(2, harms + 1):
+        harm_stats["harm"][harm_index] = {}
+        zone = np.floor(harm / (nfft / 2)) + 1
+        if zone % 2 == 0:
+            bin_harm = int(nfft / 2 - (harm - (zone - 1) * nfft / 2))
+        else:
+            bin_harm = int(harm - (zone - 1) * nfft / 2)
+
+        # Make sure we pick the max bin where power is maximized; due to spectral leakage
+        # if bin_harm == nfft/2, set to bin of 0
+        if bin_harm == nfft / 2:
+            bin_harm = 0
+        pwr_max = spectrum[bin_harm]
+        bin_harm_max = bin_harm
+        for i in range(bin_harm - leak, bin_harm + leak + 1):
+            try:
+                pwr = spectrum[i]
+                if pwr > pwr_max:
+                    bin_harm_max = i
+                    pwr_max = pwr
+            except IndexError:
+                # bin + leakage out of bounds, so stop looking
+                break
+
+        harm_stats["harm"][harm_index]["bin"] = bin_harm_max
+        harm_stats["harm"][harm_index]["power"] = pwr_max
+        harm_stats["harm"][harm_index]["freq"] = round(freq[bin_harm] / fscale, 1)
+        harm_stats["harm"][harm_index]["dBc"] = dBW(pwr_max / psig)
+        harm_stats["harm"][harm_index]["dB"] = dBW(pwr_max)
+
+        harm_index = harm_index + 1
+
+    return harm_stats
+
+
+def get_plot_string(stats, full_scale, fs, nfft, window, xscale=1e6, fscale="MHz"):
+    """Generate plot string from stats dict."""
+
+    plt_str = "==== FFT ====\n"
+    plt_str += f"NFFT = {nfft}\n"
+    plt_str += f"fbin = {round(fs/nfft / 1e3, 2)} kHz\n"
+    plt_str += f"window = {window}\n"
+    plt_str += "\n"
+    plt_str += "==== Signal ====\n"
+    plt_str += f"FullScale = {full_scale} dB\n"
+    plt_str += f"Psig = {stats['sig']['dBFS']} dBFS ({stats['sig']['dB']} dB)\n"
+    plt_str += f"fsig = {round(stats['sig']['freq']/xscale, 2)} {fscale}\n"
+    plt_str += f"fsamp = {round(fs/xscale, 2)} {fscale}\n"
+    plt_str += "\n"
+    plt_str += "====  SNDR/SFDR  ====\n"
+    plt_str += f"ENOB = {stats['enob']['bits']} bits\n"
+    plt_str += f"SNDR = {stats['sndr']['dBFS']} dBFS ({stats['sndr']['dBc']} dBc)\n"
+    plt_str += f"SFDR = {stats['sfdr']['dBFS']} dBFS ({stats['sfdr']['dBc']} dBc)\n"
+    plt_str += f"Pspur = {stats['spur']['dBFS']} dBFS\n"
+    plt_str += f"fspur = {round(stats['spur']['freq']/xscale, 2)} {fscale}\n"
+    plt_str += f"Noise Floor = {stats['noise']['dBHz']} dBFS\n"
+    plt_str += f"NSD = {stats['noise']['NSD']} dBFS\n"
+    plt_str += "\n"
+    plt_str += "==== Harmonics ====\n"
+
+    for hindex, hdata in stats["harm"].items():
+        plt_str += f"HD{hindex} = {round(hdata['dB'] - full_scale, 1)} dBFS @ {hdata['freq']} {fscale}\n"
+
+    plt_str += "\n"
+
+    return plt_str