def main():
host = "localhost"
#port = 6499
#host = "192.168.1.64"
port = 5050
app = QtGui.QApplication(sys.argv)
filename = ""
if len(sys.argv) > 2:
usage()
return
elif len(sys.argv) == 2:
filename = sys.argv[1]
#df = DataFetcher(host=host, port=port)
#df.update()
root = getNode('/', create=True)
props_xml.load(filename, root)
ex = Tuner(host=host, port=port)
sys.exit(app.exec_())
def load(self, cal_file):
config = PropertyNode()
try:
name, ext = os.path.splitext(cal_file)
if ext == '.json':
props_json.load(cal_file, config)
self.valid = True
elif ext == '.xml':
props_xml.load(cal_file, config)
self.valid = True
else:
return False
except:
print(cal_file + ": load error:\n" + str(sys.exc_info()[1]))
return False
root.pretty_print()
self.min_temp = config.getFloat('min_temp_C')
self.max_temp = config.getFloat('max_temp_C')
node = config.getChild('p')
if node:
p1, p2, p3 = node.getString('bias').split()
self.p_bias = np.array([p1, p2, p3], dtype=np.float64)
p1, p2, p3 = node.getString('scale').split()
self.p_scale = np.array([p1, p2, p3], dtype=np.float64)
node = config.getChild('q')
if node:
p1, p2, p3 = node.getString('bias').split()
self.q_bias = np.array([p1, p2, p3], dtype=np.float64)
p1, p2, p3 = node.getString('scale').split()
self.q_scale = np.array([p1, p2, p3], dtype=np.float64)
node = config.getChild('r')
if node:
p1, p2, p3 = node.getString('bias').split()
self.r_bias = np.array([p1, p2, p3], dtype=np.float64)
p1, p2, p3 = node.getString('scale').split()
self.r_scale = np.array([p1, p2, p3], dtype=np.float64)
node = config.getChild('ax')
if node:
p1, p2, p3 = node.getString('bias').split()
self.ax_bias = np.array([p1, p2, p3], dtype=np.float64)
p1, p2, p3 = node.getString('scale').split()
self.ax_scale = np.array([p1, p2, p3], dtype=np.float64)
node = config.getChild('ay')
if node:
p1, p2, p3 = node.getString('bias').split()
self.ay_bias = np.array([p1, p2, p3], dtype=np.float64)
p1, p2, p3 = node.getString('scale').split()
self.ay_scale = np.array([p1, p2, p3], dtype=np.float64)
node = config.getChild('az')
if node:
p1, p2, p3 = node.getString('bias').split()
self.az_bias = np.array([p1, p2, p3], dtype=np.float64)
p1, p2, p3 = node.getString('scale').split()
self.az_scale = np.array([p1, p2, p3], dtype=np.float64)
tokens = config.getString('mag_affine').split()
if len(tokens) == 16:
r = 0
c = 0
for i, x in enumerate(tokens):
self.mag_affine[r, c] = float(x)
c += 1
if c > 3:
c = 0
r += 1
self.mag_affine_inv = np.linalg.inv(self.mag_affine)
else:
print("mag_affine requires 16 values")
#print 'mag_affine:\n', self.mag_affine
#print 'mag_affine_inv:\n', self.mag_affine_inv
return True
#!/usr/bin/python from props import PropertyNode, root, getNode import props_xml import props_json import sys # run the system through it's paces xmlfile = sys.argv[1] jsonfile = sys.argv[2] config = PropertyNode() props_xml.load(xmlfile, config) props_json.save(jsonfile, config)
def load(self, cal_file):
config = PropertyNode()
try:
name, ext = os.path.splitext(cal_file)
if ext == '.json':
props_json.load(cal_file, config)
self.valid = True
elif ext == '.xml':
props_xml.load(cal_file, config)
self.valid = True
else:
return False
except:
print cal_file + ": load error:\n" + str(sys.exc_info()[1])
return False
root.pretty_print()
self.min_temp = config.getFloat('min_temp_C')
self.max_temp = config.getFloat('max_temp_C')
node = config.getChild('p')
if node:
p1, p2, p3 = node.getString('bias').split()
self.p_bias = np.array([p1, p2, p3], dtype=np.float64)
p1, p2, p3 = node.getString('scale').split()
self.p_scale = np.array([p1, p2, p3], dtype=np.float64)
node = config.getChild('q')
if node:
p1, p2, p3 = node.getString('bias').split()
self.q_bias = np.array([p1, p2, p3], dtype=np.float64)
p1, p2, p3 = node.getString('scale').split()
self.q_scale = np.array([p1, p2, p3], dtype=np.float64)
node = config.getChild('r')
if node:
p1, p2, p3 = node.getString('bias').split()
self.r_bias = np.array([p1, p2, p3], dtype=np.float64)
p1, p2, p3 = node.getString('scale').split()
self.r_scale = np.array([p1, p2, p3], dtype=np.float64)
node = config.getChild('ax')
if node:
p1, p2, p3 = node.getString('bias').split()
self.ax_bias = np.array([p1, p2, p3], dtype=np.float64)
p1, p2, p3 = node.getString('scale').split()
self.ax_scale = np.array([p1, p2, p3], dtype=np.float64)
node = config.getChild('ay')
if node:
p1, p2, p3 = node.getString('bias').split()
self.ay_bias = np.array([p1, p2, p3], dtype=np.float64)
p1, p2, p3 = node.getString('scale').split()
self.ay_scale = np.array([p1, p2, p3], dtype=np.float64)
node = config.getChild('az')
if node:
p1, p2, p3 = node.getString('bias').split()
self.az_bias = np.array([p1, p2, p3], dtype=np.float64)
p1, p2, p3 = node.getString('scale').split()
self.az_scale = np.array([p1, p2, p3], dtype=np.float64)
tokens = config.getString('mag_affine').split()
if len(tokens) == 16:
r = 0
c = 0
for i, x in enumerate(tokens):
self.mag_affine[r,c] = float(x)
c += 1
if c > 3:
c = 0
r += 1
self.mag_affine_inv = np.linalg.inv(self.mag_affine)
else:
print "mag_affine requires 16 values"
#print 'mag_affine:\n', self.mag_affine
#print 'mag_affine_inv:\n', self.mag_affine_inv
return True
