Rohde & Schwarz RTP Export Examples
Scott Prahl
Mar 2026
[1]:
%config InlineBackend.figure_format = 'retina'
import io
import numpy as np
import matplotlib.pyplot as plt
import requests
from RigolWFM import Wfm
repo = "https://raw.githubusercontent.com/scottprahl/RigolWFM/main/tests/files/"
def sample_url(relative_path: str) -> str:
return repo + relative_path
def _time_scale(times):
span = float(abs(times[-1] - times[0])) if len(times) > 1 else 1.0
if span >= 1e-3:
return 1e3, "ms"
if span >= 1e-6:
return 1e6, "us"
if span >= 1e-9:
return 1e9, "ns"
return 1e12, "ps"
def _volt_scale(values):
peak = max(float(np.max(np.abs(v))) for v in values) if values else 1.0
if peak >= 1.0:
return 1.0, "V"
if peak >= 1e-3:
return 1e3, "mV"
if peak >= 1e-6:
return 1e6, "uV"
return 1e9, "nV"
def plot_analog_channels(w, title=None, max_points=5000):
active = [ch for ch in w.channels if ch.times is not None and ch.volts is not None]
if not active:
print("No analog channels are enabled in this capture.")
return
colors = ["green", "red", "blue", "orange"]
t_scale, t_unit = _time_scale(active[0].times)
v_scale, v_unit = _volt_scale([ch.volts for ch in active])
fig, axes = plt.subplots(len(active), 1, sharex=True, figsize=(10, 2.5 * len(active)))
if len(active) == 1:
axes = [axes]
for ax, ch, color in zip(axes, active, colors):
stride = max(len(ch.times) // max_points, 1)
ax.plot(ch.times[::stride] * t_scale, ch.volts[::stride] * v_scale, color=color)
ax.set_ylabel(v_unit)
ax.set_title(f"CH{ch.channel_number} {ch.points} points")
ax.grid(True)
axes[-1].set_xlabel(f"Time ({t_unit})")
if title:
fig.suptitle(title)
plt.tight_layout()
plt.show()
def plot_logic_window(w, names=None, start=0, stop=4000, title=None):
if not w.logic_channels:
print("No logic channels are enabled in this capture.")
return
if names is None:
names = list(w.logic_channels)
if w.logic_times is None:
times = np.arange(len(next(iter(w.logic_channels.values()))), dtype=np.float64)
else:
times = w.logic_times
stop = min(stop, len(times))
t_scale, t_unit = _time_scale(times[start:stop])
fig, axes = plt.subplots(len(names), 1, sharex=True, figsize=(10, 1.6 * len(names)))
if len(names) == 1:
axes = [axes]
colors = ["green", "red", "blue", "orange", "purple", "brown"]
for ax, name, color in zip(axes, names, colors):
trace = w.logic_channels[name]
ax.step(times[start:stop] * t_scale, trace[start:stop], where="post", color=color)
ax.set_ylim(-0.2, 1.2)
ax.set_yticks([0, 1])
ax.set_ylabel(name)
ax.grid(True)
axes[-1].set_xlabel(f"Time ({t_unit})")
if title:
fig.suptitle(title)
plt.tight_layout()
plt.show()
def load_vendor_csv(relative_path: str):
response = requests.get(sample_url(relative_path), timeout=30)
response.raise_for_status()
data = np.loadtxt(io.StringIO(response.text), delimiter=",", dtype=np.float64)
if data.ndim == 1:
data = data[:, np.newaxis]
return data
rs_rtp_01.bin - Single-channel analog export
[2]:
filename = "rs/rs_rtp_01.bin"
w = Wfm.from_url(sample_url(filename), "RohdeSchwarz")
print(w.describe())
General:
File Model = Rohde & Schwarz
User Model = RohdeSchwarz
Parser Model = rohde_schwarz_bin
Firmware = unknown
Filename = rs_rtp_01.bin
Channels = [1]
Trigger:
Derived Level (CH1) = 1.03 V
Channel 1:
Coupling = unknown
Scale = 400.00 mV/div
Offset = 0.00 V
Probe = 1X
Inverted = False
Time Base = 500.000 µs/div
Offset = 0.000 s
Delta = 1.250 µs/point
Points = 4000
Count = [ 1, 2, 3 ... 3999, 4000]
Raw = [ 247, 240, 236 ... 18, 11]
Times = [-2.500 ms,-2.499 ms,-2.498 ms ... 2.498 ms, 2.499 ms]
Volts = [-31.62 mV, 0.00 V, 15.81 mV ... 996.05 mV, 1.03 V]
downloading 'https://raw.githubusercontent.com/scottprahl/RigolWFM/main/tests/files/rs/rs_rtp_01.bin'
downloading 'https://raw.githubusercontent.com/scottprahl/RigolWFM/main/tests/files/rs/rs_rtp_01.Wfm.bin'
Plot the decoded waveform
[3]:
plot_analog_channels(w, title=filename)
rs_rtp_02.bin - Two-channel analog export
[4]:
filename = "rs/rs_rtp_02.bin"
w = Wfm.from_url(sample_url(filename), "RohdeSchwarz")
print(w.describe())
downloading 'https://raw.githubusercontent.com/scottprahl/RigolWFM/main/tests/files/rs/rs_rtp_02.bin'
downloading 'https://raw.githubusercontent.com/scottprahl/RigolWFM/main/tests/files/rs/rs_rtp_02.Wfm.bin'
General:
File Model = Rohde & Schwarz
User Model = RohdeSchwarz
Parser Model = rohde_schwarz_bin
Firmware = unknown
Filename = rs_rtp_02.bin
Channels = [1, 2]
Trigger:
Derived Level (CH1) = 1.03 V
Derived Level (CH2) = 221.34 mV
Channel 1:
Coupling = unknown
Scale = 400.00 mV/div
Offset = 0.00 V
Probe = 1X
Inverted = False
Time Base = 500.000 µs/div
Offset = 0.000 s
Delta = 1.250 µs/point
Points = 4000
Count = [ 1, 2, 3 ... 3999, 4000]
Raw = [ 247, 240, 236 ... 18, 11]
Times = [-2.500 ms,-2.499 ms,-2.498 ms ... 2.498 ms, 2.499 ms]
Volts = [-31.62 mV, 0.00 V, 15.81 mV ... 996.05 mV, 1.03 V]
Channel 2:
Coupling = unknown
Scale = 400.00 mV/div
Offset = 0.00 V
Probe = 1X
Inverted = False
Time Base = 500.000 µs/div
Offset = 0.000 s
Delta = 1.250 µs/point
Points = 4000
Count = [ 1, 2, 3 ... 3999, 4000]
Raw = [ 223, 231, 231 ... 100, 115]
Times = [-2.500 ms,-2.499 ms,-2.498 ms ... 2.498 ms, 2.499 ms]
Volts = [-221.34 mV,-237.15 mV,-237.15 mV ... 31.62 mV, 0.00 V]
Plot both channels
[5]:
plot_analog_channels(w, title=filename)
rs_rtp_04.bin - Compare RigolWFM output to the vendor CSV
[6]:
filename = "rs/rs_rtp_04.bin"
w = Wfm.from_url(sample_url(filename), "RohdeSchwarz")
csv = load_vendor_csv("rs/rs_rtp_04.Wfm.csv")
times = w.channels[0].times
volts = w.channels[0].volts
vendor_times = csv[:, 0]
vendor_volts = csv[:, 1]
print(f"Max abs voltage difference: {np.max(np.abs(volts - vendor_volts)):.6e} V")
print(f"Max abs time difference: {np.max(np.abs(times - vendor_times)):.6e} s")
downloading 'https://raw.githubusercontent.com/scottprahl/RigolWFM/main/tests/files/rs/rs_rtp_04.bin'
downloading 'https://raw.githubusercontent.com/scottprahl/RigolWFM/main/tests/files/rs/rs_rtp_04.Wfm.bin'
Max abs voltage difference: 4.964130e-08 V
Max abs time difference: 1.895898e-20 s
Overlay the first 500 samples
[7]:
plt.figure(figsize=(10, 4))
plt.plot(times[:500] * 1e9, volts[:500] * 1e6, label="RigolWFM", linewidth=2)
plt.plot(vendor_times[:500] * 1e9, vendor_volts[:500] * 1e6, "--", label="Vendor CSV", linewidth=1)
plt.xlabel("Time (ns)")
plt.ylabel("Voltage (uV)")
plt.title(filename)
plt.grid(True)
plt.legend()
plt.show()
