mirror of https://github.com/Desuuuu/klipper.git
probe: Unify mean and median code between run_probe() and PROBE_ACCURACY
Factor out _calc_mean() and _calc_median() functions and call from both run_probe() and cmd_PROBE_ACCURACY(). This also fixes a subtle error in the run_probe() median function - on some kinematics the x and y position can change on a z move so the x and y should be taken from the z probe values actually used. Signed-off-by: Kevin O'Connor <kevin@koconnor.net>
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@ -33,9 +33,9 @@ class PrinterProbe:
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self.samples = config.getint('samples', 1, minval=1)
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self.sample_retract_dist = config.getfloat(
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'sample_retract_dist', 2., above=0.)
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self.samples_result = config.getchoice('samples_result',
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{'median': 0, 'average': 1},
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default='average')
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atypes = {'median': 'median', 'average': 'average'}
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self.samples_result = config.getchoice('samples_result', atypes,
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'average')
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# Register z_virtual_endstop pin
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self.printer.lookup_object('pins').register_chip('probe', self)
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# Register PROBE/QUERY_PROBE commands
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@ -86,6 +86,18 @@ class PrinterProbe:
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toolhead.move(curpos, speed)
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except homing.EndstopError as e:
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raise self.gcode.error(str(e))
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def _calc_mean(self, positions):
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count = float(len(positions))
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return [sum([pos[i] for pos in positions]) / count
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for i in range(3)]
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def _calc_median(self, positions):
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z_sorted = sorted(positions, key=(lambda p: p[2]))
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middle = len(positions) // 2
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if (len(positions) & 1) == 1:
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# odd number of samples
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return z_sorted[middle]
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# even number of samples
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return self._calc_mean(z_sorted[middle-1:middle+1])
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def run_probe(self):
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positions = []
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for i in range(self.samples):
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@ -95,26 +107,9 @@ class PrinterProbe:
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# retract
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liftpos = [None, None, pos[2] + self.sample_retract_dist]
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self._move(liftpos, self.speed)
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if self.samples_result == 1:
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# Calculate Average
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calculated_value = [sum([pos[i] for pos in positions]) /
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self.samples for i in range(3)]
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else:
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# Calculate Median
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sorted_z_positions = sorted([position[2]
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for position in positions])
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middle = self.samples // 2
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if (self.samples & 1) == 1:
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# odd number of samples
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median = sorted_z_positions[middle]
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else:
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# even number of samples
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median = (sorted_z_positions[middle] +
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sorted_z_positions[middle - 1]) / 2
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calculated_value = [positions[0][0],
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positions[0][1],
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median]
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return calculated_value
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if self.samples_result == 'median':
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return self._calc_median(positions)
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return self._calc_mean(positions)
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cmd_PROBE_help = "Probe Z-height at current XY position"
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def cmd_PROBE(self, params):
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pos = self.run_probe()
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@ -130,7 +125,6 @@ class PrinterProbe:
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cmd_PROBE_ACCURACY_help = "Probe Z-height accuracy at current XY position"
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def cmd_PROBE_ACCURACY(self, params):
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toolhead = self.printer.lookup_object('toolhead')
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probes = []
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pos = toolhead.get_position()
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number_of_reads = self.gcode.get_int('REPEAT', params, default=10,
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minval=4, maxval=50)
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@ -147,36 +141,25 @@ class PrinterProbe:
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x_start_position, y_start_position,
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z_start_position, number_of_reads, speed))
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# Probe bed "number_of_reads" times
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sum_reads = 0
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positions = []
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for i in range(number_of_reads):
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# Move Z to start reading position
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self._move(start_pos, speed)
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# Probe
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pos = self._probe(speed)
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# Get Z value, accumulate value to calculate average
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# and save it to calculate standard deviation
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sum_reads += pos[2]
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probes.append(pos[2])
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positions.append(pos)
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# Move Z to start reading position
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self._move(start_pos, speed)
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# Calculate maximum, minimum and average values
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max_value = max(probes)
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min_value = min(probes)
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avg_value = sum(probes) / number_of_reads
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max_value = max([p[2] for p in positions])
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min_value = min([p[2] for p in positions])
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avg_value = self._calc_mean(positions)[2]
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median = self._calc_median(positions)[2]
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# calculate the standard deviation
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deviation_sum = 0
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for i in range(number_of_reads):
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deviation_sum += pow(probes[i] - avg_value, 2)
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deviation_sum += pow(positions[i][2] - avg_value, 2)
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sigma = (deviation_sum / number_of_reads) ** 0.5
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# Median
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sorted_probes = sorted(probes)
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middle = number_of_reads//2
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if (number_of_reads & 1) == 1:
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# odd number of reads
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median = sorted_probes[middle]
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else:
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# even number of reads
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median = (sorted_probes[middle]+sorted_probes[middle-1])/2
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# Show information
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self.gcode.respond_info(
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"probe accuracy results: maximum %.6f, minimum %.6f, "
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