172 lines
6.2 KiB
Python
172 lines
6.2 KiB
Python
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# -------------------------------------------------------------------
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# ORTHOGRAPHIC
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# Your personal aerial satellite. Always on. At any altitude.*
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# Developed by MarStrMind
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# License: Open Software License 3.0
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# Up to date version always on marstr.online
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# -------------------------------------------------------------------
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# osmxml.py
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# Performs calls to Overpass API to acquire XML files which we can
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# then store into a much faster SQLite3 database.
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# -------------------------------------------------------------------
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import xml.dom.minidom
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import requests
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import os
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from defines import *
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from log import *
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class mstr_osmxml:
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def __init__(self, lat, lng):
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self._latv = lat
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self._lngv = lng
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self._lat = lat
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self._lng = lng
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self._curB_lat = lat + mstr_zl_18
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self._curB_lng = lng + mstr_zl_18
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# Adjust bbox for when this class should persost, but acquire data for a different bbox
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def adjust_bbox(self, lat, lng, lat_e, lng_e):
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self._lat = round(lat, 4)
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self._lng = round(lng, 4)
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self._curB_lat = round(lat_e, 4)
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self._curB_lng = round(lng_e, 4)
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# Acquire XMLs in chunks, then store them
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def acquire_osm(self, v, h, asobject=False):
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mstr_msg("osmxml", "Acquiring OSM data for " + str(self._lat)+","+str(self._lng)+" - "+str(self._curB_lat)+","+str(self._curB_lng))
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# We will use our self-hosted API for this.
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data = {
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"bbox": {
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"lat": str(self._lat),
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"lng": str(self._lng),
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"lat_b": str(self._curB_lat),
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"lng_b": str(self._curB_lng)
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},
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"tile_lat": str(self._lat),
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"tile_lng": str(self._lng),
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"square_lat": str(v),
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"square_lng": str(h)
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}
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r = requests.post(mstr_osm_endpoint, json=data)
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xmlf = mstr_datafolder + "_cache/tile.xml"
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if os.path.isfile(xmlf):
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os.remove(xmlf)
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with open(xmlf, 'wb') as textfile:
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textfile.write(r.content)
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# Provide the object directly
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if asobject == True:
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xml_doc = xml.dom.minidom.parse("_cache/tile.xml")
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return xml_doc
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# Get all nodes from the specified OSM file
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def acquire_nodes(self, xmlfile):
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xml_doc = xml.dom.minidom.parse(xmlfile)
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nodedata = xml_doc.getElementsByTagName("node")
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nodes = []
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for node in nodedata:
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p = (node.getAttribute("id"), node.getAttribute("lat"), node.getAttribute("lon"))
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nodes.append(p)
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return nodes
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# Get all waypoint data
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def acquire_waypoint_data(self, xmlfile):
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xml_doc = xml.dom.minidom.parse(xmlfile)
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wpdata = xml_doc.getElementsByTagName("way")
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wps = []
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for wp in wpdata:
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nddata = wp.getElementsByTagName("nd")
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for nd in nddata:
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p = (wp.getAttribute("id"), nd.getAttribute("ref"), "", "")
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wps.append(p)
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for wp in wpdata:
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tagdata = wp.getElementsByTagName("tag")
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for tag in tagdata:
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c = tag.getAttribute("v").replace(",", "")
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c = c.replace("'", "")
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p = (wp.getAttribute("id"), "NULL", tag.getAttribute("k"), c)
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wps.append(p)
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return wps
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# Checks if there is an airport or many airports with an ICAO code in the
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# supplied XML data chunk
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def find_icao_codes(self, xmlfile):
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icao = []
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xml_doc = xml.dom.minidom.parse(xmlfile)
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wpdata = xml_doc.getElementsByTagName("way")
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for wp in wpdata:
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tags = wp.getElementsByTagName("tag")
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for tag in tags:
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a = tag.getAttribute("k")
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if a == "icao":
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v = tag.getAttribute("v")
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icao.append(v)
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# Return list of found airports
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return icao
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# Finds the surface type of a runway in the current data chunk.
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# If no surface type is specified, the runway will be rendered similar
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# to how motorways are rendered.
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# This gets called only if some ICAO code was found
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def find_runway_surface(self, xmlfile):
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surface = ""
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wpid = ""
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xml_doc = xml.dom.minidom.parse(xmlfile)
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wpdata = xml_doc.getElementsByTagName("way")
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for wp in wpdata:
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tags = wp.getElementsByTagName("tag")
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for tag in tags:
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a = tag.getAttribute("k")
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v = tag.getAttribute("v")
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if a == "aeroway" and v == "runway":
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wpid = wp.getAttribute("id")
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break
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for wp in wpdata:
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wid = wp.getAttribute("id")
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if wid == wpid:
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tags = wp.getElementsByTagName("tag")
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for tag in tags:
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a = tag.getAttribute("k")
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v = tag.getAttribute("v")
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if a == "surface":
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surface = v
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# Return the found surface type
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return surface
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# It turns out that some features hide themselves in the relations section.
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# I figured this out during testing, and almost going insane over the
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# question as to why some parts like forests are missing in the masks, while
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# it is clearly labeled as forest on openstreetmap. We need to scan
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# the relations and then scan through the outer and inner way IDs.
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#
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# Get all relation entries of importance.
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def acquire_relations(self, xmlfile):
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xml_doc = xml.dom.minidom.parse(xmlfile)
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rlxml = xml_doc.getElementsByTagName("relation")
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rls = []
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for rl in rlxml:
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rldata = rl.getElementsByTagName("member")
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tagdata = rl.getElementsByTagName("tag")
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for rp in rldata:
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t = rp.getAttribute("role")
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if t == "inner" or t == "outer":
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tgd = []
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for i in tagdata:
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tgd.append(i.getAttribute("k"))
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tgd.append(i.getAttribute("v"))
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rls.append((rp.getAttribute("ref"), tgd))
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return rls
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