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--- amc:ss2025:group-a:start [2025/07/29 14:58] – [Data analysis] 35120_students.hsrw
+++ amc:ss2025:group-a:start [2025/07/29 15:11] (current) – [Data analysis] 35120_students.hsrw
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 ==== Data analysis ====
+**Data Cleaning:**
+Selection of a segment of interest, discarding outliers or unreliable data.
+Due some hardware limitations, the reading of the marks was not reliable enough, therefore the data had to be conditioned manually.
+The expected data is 12 marks readings, but due to problems in the data acquisition there were just 8 marks usable, and there were also some duplicated readings, this was determined manually based on the time and pattern expected.
+**Path Segmentation:**
+getPath(df) constructs segments ("paths") marked by zero in the zone_1 column, grouping each set of four zeros as a new path.
+**Speed Calculation:**
+mean_speed(data) estimates the average speed between time marks by measuring intervals between zeros.
+  * After interpolating sensor data along the location axis (temporal/spatial sequence), each 8×8 frame is upscaled to 64×64 pixels using cubic spline interpolation (zoom with order=3).
+  * This spatial interpolation significantly enhances intra-frame resolution.
+  * The aggregation step then merges these larger frames horizontally with value averaging over overlapping columns, preserving continuity.
+  * The plot displays a much higher-resolution heatmap representing the sensor data over the scanned path.
 <code python>
 import pandas as pd
@@ Line 884: / Line 904: @@
 plt.show()
 </code>
+{{ :amc:ss2025:group-a:screenshot_2025-07-29_142824.png?800 |Map of the path of the Gießwagen}}
 ===== Discussion =====