#!/usr/bin/env python

# Planets
# Phil Bordelon

import math
import os
import sys

DEBUG = os.getenv("DEBUG", False)

# The maximum diameter of a planet is 1,000,000 km, which means that
# the maximum distance between two cities is half of the circumference.
# pi * 1000000 / 2 = ~1570796 ... so let's call infinity 100,000,000.
INFINITY = 100000000.0

# Yeah, classes structures blah.
class Struct(object):
   pass

###
# llToVector takes a latitude and longitude and returns a unit vector
# pointing from the center of the planet to that point on the globe.
def llToVector(latitude, longitude):

   # First, let's get them in degrees.
   theta = float(90 - latitude)

   # Note that this is probably not the /real/ longitudinal degrees,
   # but as long as we're consistent with this calculation, it's
   # irrelevant; even if the cities are all 180 degrees away from
   # their "real" locations, they're /all/ 180 degrees away, so the
   # relative distances are identical.
   phi = float(longitude)

   # Math functions require radians.  I would like to point out that
   # I've been in the workforce for five years since graduating from
   # college and I've never used a radian other than for writing
   # these solutions.  Thanks, trig and calculus!
   theta = (theta / 360) * 2 * math.pi
   phi = (phi / 360) * 2 * math.pi

   # Now to calculate the components of this vector.
   x = math.sin(theta) * math.cos(phi)
   y = math.sin(theta) * math.sin(phi)
   z = math.cos(theta)

   return (x, y, z)

###
# angleBetweenVectors calculates the angle between two 3D vectors.
def angleBetweenVectors (v1, v2):

   # This is more bleh maths.  The proper equation is that
   # the magnitudes of the vectors times the cosine of the angle
   # equals their cross product.  Now, we're using unit vectors,
   # so all of their magnitudes are 1.  So it becomes the rather
   # simple:
   #    angle = cos^-1(v1 * v2)
   # where * is the cross-product.  So let's do that.
   cross_product = v1[0] * v2[0] + v1[1] * v2[1] + v1[2] * v2[2]
   angle = math.acos(cross_product)

   return angle

####
# prim runs Prim's Algorithm with the given edges, returning the total length
# of all edges selected to be part of the minimal spanning tree.
def prim(vertex_count, edges):

   # First, we build a list of vertices.
   vertex_list = []
   for v in range(vertex_count):
      vertex = Struct()
      vertex.number = v
      vertex.distance = INFINITY
      vertex.edge_list = [x for x in edges if x[0] == v]

      vertex_list.append(vertex)

   # Set the very first vertex's distance to 0 to start.
   vertex_list[0].distance = 0

   # Set the total length of the MST to 0.
   length = 0

   # The list of unhandled vertices ...
   unhandled_vertices = range(vertex_count)

   while len(unhandled_vertices) > 0:
      best_distance = INFINITY
      best_vertex = -1
      for vertex in unhandled_vertices:
         if vertex_list[vertex].distance < best_distance:
            best_vertex = vertex
            best_distance = vertex_list[vertex].distance

      if DEBUG:
         print("Best new distance: %f (vertex %d)" % (best_distance, best_vertex))

      # Got a vertex.  Add its length to the total and remove it from the list.
      unhandled_vertices.remove(best_vertex)

      real_vertex = vertex_list[best_vertex]
      length += real_vertex.distance

      # For every unvisited vertex adjacent to this one, if this distance plus
      # the edge length is less than its current distance, update.
      for edge in real_vertex.edge_list:
         if edge[1] in unhandled_vertices:
            new_distance = edge[2]
            if new_distance < vertex_list[edge[1]].distance:
               vertex_list[edge[1]].distance = new_distance

   # Return the length we determined.

   if DEBUG:
      print("Total length of cable required: %f" % length)
   return length

####
# calculateCableNeeded does the gruntwork of determining how much cable a
# planet needs to be fully connected.  It first calculates distances between
# each city, building a full graph out of that, then runs Prim's over that
# graph to determine the length of a minimal spanning tree.
def calculateCableNeeded(planet):

   # First we build a full list of edges, potentially connecting every city
   # to every other city.  We build edges in both directions at the same
   # time.  Because of that, we can optimize a bit and only loop over half
   # of the full N*N city "grid."

   edges = []
   for i in range(planet.city_count - 1):
      for j in range(i + 1, planet.city_count):
         angle = angleBetweenVectors(planet.cities[i], planet.cities[j])

         if DEBUG:
            print("Angle between city %d and %d: %f" % (i, j, angle))

         # The distance between the two cities is the percentage of the
         # great arc between the two of them.  A great arc is the same
         # length as the circumference of the planet, which is pi*d,
         # and the angle returned above is some fraction of that.  Thus
         # the distance!
         distance = (angle / (2 * math.pi)) * math.pi * planet.diameter

         if DEBUG:
            print("Distance between city %d and %d: %f" % (i, j, distance))

         # Add edges in both directions.
         edges.append((i, j, distance))
         edges.append((j, i, distance))

   # Now that we're done with that, we run Prim's and get the distance
   # returned.

   return prim(planet.city_count, edges)

def main():

   dataset_count = int(sys.stdin.readline())
   for dataset_loop in range(dataset_count):

      # A new planet to cable up.
      planet = Struct()

      # Get the diameter.
      planet.diameter = int(sys.stdin.readline())

      # Get the amount of cable we have.
      planet.cable = int(sys.stdin.readline())

      # Get the number of cities we have to connect.
      planet.city_count = int(sys.stdin.readline())

      planet.cities = []

      # Read the cities in, converting their coordinates to vectors.
      for city_loop in range(planet.city_count):
         latitude, longitude = [float(x) for x in
          sys.stdin.readline().strip().split()]

         planet.cities.append(llToVector(latitude, longitude))

      # Get how much cable we need.
      cable_needed = calculateCableNeeded(planet)

      if cable_needed <= planet.cable:
         print("IS POSSIBLE")
      else:
         print("IS NOT POSSIBLE")

if "__main__" == __name__:
   main()