Analyse pitch in gpx file

pitch.py

import math
import xml.etree.ElementTree as ET
import matplotlib.pyplot as plt
from pyo5m import OsmData

if __name__=="__main__":

	tree = ET.parse("/home/tim/Desktop/CampingMapping/20170709.gpx")
	root = tree.getroot()
	prevPos = None
	prevEle = None
	cumDist = 0.0
	distData, gradData = [], []
	latLonData, eleData = [], []
	nid = -1

	osmData = OsmData.OsmData()

	for k in root:
		if k.tag != "{http://www.topografix.com/GPX/1/1}trk": continue

		for ks in k:
			if ks.tag != "{http://www.topografix.com/GPX/1/1}trkseg": continue

			for trkpt in ks:
				if trkpt.tag != "{http://www.topografix.com/GPX/1/1}trkpt": continue
			
				lat = float(trkpt.attrib["lat"])
				lon = float(trkpt.attrib["lon"])
				
				ele = None
				for prop in trkpt:
					if prop.tag == "{http://www.topografix.com/GPX/1/1}ele":
						ele = float(prop.text)

				R = 6371000.0
				latr = math.radians(lat)
				lonr = math.radians(lon)
				x = R * math.cos(latr) * math.cos(lonr)
				y = R * math.cos(latr) * math.sin(lonr)
				z = R * math.sin(latr)

				if prevPos is not None:
					dist2d = ((x-prevPos[0])**2.0+(y-prevPos[1])**2.0+(z-prevPos[2])**2.0)**0.5

					distData.append(cumDist)
					cumDist += dist2d
					eleData.append(ele)
					latLonData.append((lat, lon))
				prevPos = (x, y, z)

	distData2 = []
	for i, (cumDist, ele, (lat, lon)) in enumerate(zip(distData, eleData, latLonData)):
		if i+10 >= len(distData): continue

		cumDist2, ele2 = distData[i+10], eleData[i+10]
		dist2d = cumDist2 - cumDist
		dele = ele2 - ele
		#print cumDist, dist2d, dele

		gradient = math.atan2(dele, dist2d) * 100.0

		if dist2d > 1.0:
			#print cumDist, gradient
			gradData.append(gradient)
			distData2.append(0.5*(cumDist+cumDist2))
			#print 0.5*(cumDist+cumDist2), gradient
			metaData = (1, None, None, None, None, True)
			osmData.nodes.append([nid, metaData, {"pitch": str(gradient)}, [lat, lon]])
			nid -= 1

		prevPos = (x, y, z)
		prevEle = ele



	fi = open("export.osm", "wb")
	osmData.SaveToOsmXml(fi)
	fi.close()

	plt.plot(distData2, gradData)
	plt.show()