added logging for filename in case of an unexpected error
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@@ -570,11 +570,15 @@ def belts_calibration(lognames, klipperdir="~/klipper", max_freq=200.):
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ax2 = fig.add_subplot(gs[1])
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ax2 = fig.add_subplot(gs[1])
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# Add title
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# Add title
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filename = lognames[0].split('/')[-1]
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dt = datetime.strptime(f"{filename.split('_')[1]} {filename.split('_')[2]}", "%Y%m%d %H%M%S")
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title_line1 = "RELATIVE BELT CALIBRATION TOOL"
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title_line1 = "RELATIVE BELT CALIBRATION TOOL"
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title_line2 = dt.strftime('%x %X')
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fig.text(0.12, 0.965, title_line1, ha='left', va='bottom', fontsize=20, color=KLIPPAIN_COLORS['purple'], weight='bold')
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fig.text(0.12, 0.965, title_line1, ha='left', va='bottom', fontsize=20, color=KLIPPAIN_COLORS['purple'], weight='bold')
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try:
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filename = lognames[0].split('/')[-1]
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dt = datetime.strptime(f"{filename.split('_')[1]} {filename.split('_')[2]}", "%Y%m%d %H%M%S")
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title_line2 = dt.strftime('%x %X')
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except:
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print("Warning: CSV filenames look to be different than expected (%s , %s)" % (lognames[0], lognames[1]))
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title_line2 = lognames[0].split('/')[-1] + " / " + lognames[1].split('/')[-1]
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fig.text(0.12, 0.957, title_line2, ha='left', va='top', fontsize=16, color=KLIPPAIN_COLORS['dark_purple'])
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fig.text(0.12, 0.957, title_line2, ha='left', va='top', fontsize=16, color=KLIPPAIN_COLORS['dark_purple'])
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# Plot the graphs
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# Plot the graphs
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@@ -311,11 +311,15 @@ def shaper_calibration(lognames, klipperdir="~/klipper", max_smoothing=None, max
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ax2 = fig.add_subplot(gs[1])
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ax2 = fig.add_subplot(gs[1])
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# Add title
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# Add title
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filename_parts = (lognames[0].split('/')[-1]).split('_')
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dt = datetime.strptime(f"{filename_parts[3]} {filename_parts[4].split('.')[0]}", "%Y%m%d %H%M%S")
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title_line1 = "INPUT SHAPER CALIBRATION TOOL"
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title_line1 = "INPUT SHAPER CALIBRATION TOOL"
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title_line2 = dt.strftime('%x %X') + ' -- ' + filename_parts[2].upper() + ' axis'
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fig.text(0.12, 0.965, title_line1, ha='left', va='bottom', fontsize=20, color=KLIPPAIN_COLORS['purple'], weight='bold')
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fig.text(0.12, 0.965, title_line1, ha='left', va='bottom', fontsize=20, color=KLIPPAIN_COLORS['purple'], weight='bold')
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try:
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filename_parts = (lognames[0].split('/')[-1]).split('_')
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dt = datetime.strptime(f"{filename_parts[3]} {filename_parts[4].split('.')[0]}", "%Y%m%d %H%M%S")
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title_line2 = dt.strftime('%x %X') + ' -- ' + filename_parts[2].upper() + ' axis'
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except:
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print("Warning: CSV filename look to be different than expected (%s)" % (lognames[0]))
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title_line2 = lognames[0].split('/')[-1]
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fig.text(0.12, 0.957, title_line2, ha='left', va='top', fontsize=16, color=KLIPPAIN_COLORS['dark_purple'])
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fig.text(0.12, 0.957, title_line2, ha='left', va='top', fontsize=16, color=KLIPPAIN_COLORS['dark_purple'])
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# Plot the graphs
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# Plot the graphs
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@@ -368,11 +368,15 @@ def vibrations_calibration(lognames, klipperdir="~/klipper", axisname=None, max_
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ax1 = fig.add_subplot(gs[0])
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ax1 = fig.add_subplot(gs[0])
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ax2 = fig.add_subplot(gs[1])
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ax2 = fig.add_subplot(gs[1])
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filename_parts = (lognames[0].split('/')[-1]).split('_')
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dt = datetime.strptime(f"{filename_parts[1]} {filename_parts[2].split('-')[0]}", "%Y%m%d %H%M%S")
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title_line1 = "VIBRATIONS MEASUREMENT TOOL"
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title_line1 = "VIBRATIONS MEASUREMENT TOOL"
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title_line2 = dt.strftime('%x %X') + ' -- ' + axisname.upper() + ' axis'
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fig.text(0.12, 0.965, title_line1, ha='left', va='bottom', fontsize=20, color=KLIPPAIN_COLORS['purple'], weight='bold')
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fig.text(0.12, 0.965, title_line1, ha='left', va='bottom', fontsize=20, color=KLIPPAIN_COLORS['purple'], weight='bold')
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try:
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filename_parts = (lognames[0].split('/')[-1]).split('_')
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dt = datetime.strptime(f"{filename_parts[1]} {filename_parts[2].split('-')[0]}", "%Y%m%d %H%M%S")
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title_line2 = dt.strftime('%x %X') + ' -- ' + axisname.upper() + ' axis'
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except:
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print("Warning: CSV filename look to be different than expected (%s)" % (lognames[0]))
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title_line2 = lognames[0].split('/')[-1]
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fig.text(0.12, 0.957, title_line2, ha='left', va='top', fontsize=16, color=KLIPPAIN_COLORS['dark_purple'])
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fig.text(0.12, 0.957, title_line2, ha='left', va='top', fontsize=16, color=KLIPPAIN_COLORS['dark_purple'])
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# Remove speeds duplicates and graph the processed datas
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# Remove speeds duplicates and graph the processed datas
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