DBras
/
46045-syslab
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

question: D3 Part 2

This commit is contained in:
DBras 2024-06-10 14:34:57 +02:00
parent fa6eda5c16
commit bb6ebbc9db
2 changed files with 4264 additions and 10 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

4256
data/measurements/measurements_1718013830.json Normal file
View File

File diff suppressed because it is too large Load Diff

18
demo_plotter.py
View File

@ -34,10 +34,12 @@ if use_setpoint_log:
else: else:
data = meas_data data = meas_data
################################################################################
################## Part 2 ######################################################
################################################################################
################################################################################ ## The controller is reasonably fast at reacting to changes; the sum of in and
################## Question 4 ################################################## ## out is at zero roughly 5-10 seconds after a change.
################################################################################
# Construct a dataframe and pivot it to obtain a dataframe with a column per unit, and a row per timestamp. # Construct a dataframe and pivot it to obtain a dataframe with a column per unit, and a row per timestamp.
df = pd.DataFrame.from_records(data) df = pd.DataFrame.from_records(data)
@ -46,15 +48,11 @@ df_pivot = df.pivot_table(values='value', columns='unit', index='time')
df_resampled = df_pivot.resample('s').mean() df_resampled = df_pivot.resample('s').mean()
df_resampled.interpolate(method='linear', inplace=True) df_resampled.interpolate(method='linear', inplace=True)
df_resampled = pd.DataFrame(df_resampled) df_resampled = pd.DataFrame(df_resampled)
df_resampled['common_p'] = df_resampled[[c for c in df_resampled if '_p' in c
and c != 'pcc_p']].sum(axis=1) * -1
# Plot the data. Note, that the data will mostly not be plotted with lines. # Plot the data. Note, that the data will mostly not be plotted with lines.
plt.ion() # Turn interactive mode on plt.ion() # Turn interactive mode on
plt.figure() plt.figure()
plt.plot(df_resampled['pcc_p']) ax1, ax2 = plt.subplot(211), plt.subplot(212)
plt.plot(df_resampled['common_p']) df_resampled[[c for c in df_resampled.columns if '_p' in c]].plot(marker='.', ax=ax1, linewidth=3)
df_resampled['pcc_p'].plot(marker='.', ax=ax2, linewidth=3)
plt.show(block=True) plt.show(block=True)
## The controller seems to balance in and out from the grid. Differences are
## probably from interpolation and resampling.