def draw_line(self, pos):
if self.viewer._ocr and self.x_clicked or self.y_clicked:
img_line = cv.line(self.image.copy(),
(self.x_clicked, self.y_clicked),
(pos.x(), pos.y()), (0, 0, 0), 2)
image_height, image_width, image_depth = img_line.shape
QIm = cv.cvtColor(img_line, cv.COLOR_BGR2RGB)
QIm = QImage(QIm.data, image_width, image_height,
image_width * image_depth, QImage.Format_RGB888)
self.viewer.setPhoto(QPixmap.fromImage(QIm))
# 终止画线
if self.x_released or self.y_released:
self.choosePoints = [] # 初始化存储点组
inf = float("inf")
if self.x_released or self.y_released:
if (self.x_released - self.x_clicked) == 0:
slope = inf
else:
slope = (self.y_released - self.y_clicked) / (
self.x_released - self.x_clicked)
siteLenth = 0.5 * math.sqrt(
square(self.y_released - self.y_clicked) +
square(self.x_released - self.x_clicked))
mySiteLenth = 2 * siteLenth
self.siteLenth = ("%.2f" % mySiteLenth)
self.editSiteLenth.setText(self.siteLenth)
radian = math.atan(slope)
self.siteSlope = ("%.2f" % radian)
self.editSiteSlope.setText(self.siteSlope)
x_bas = math.ceil(math.fabs(0.5 * siteLenth *
math.sin(radian)))
y_bas = math.ceil(math.fabs(0.5 * siteLenth *
math.cos(radian)))
if slope <= 0:
self.choosePoints.append([(self.x_clicked - x_bas),
(self.y_clicked - y_bas)])
self.choosePoints.append([(self.x_clicked + x_bas),
(self.y_clicked + y_bas)])
self.choosePoints.append([(self.x_released + x_bas),
(self.y_released + y_bas)])
self.choosePoints.append([(self.x_released - x_bas),
(self.y_released - y_bas)])
elif slope > 0:
self.choosePoints.append([(self.x_clicked + x_bas),
(self.y_clicked - y_bas)])
self.choosePoints.append([(self.x_clicked - x_bas),
(self.y_clicked + y_bas)])
self.choosePoints.append([(self.x_released - x_bas),
(self.y_released + y_bas)])
self.choosePoints.append([(self.x_released + x_bas),
(self.y_released - y_bas)])
self.viewer._ocr = False
def _function(self, individual, function):
functions = []
set_ = {}
self._InOrder(individual["key"], functions)
'''para cada objeto, calcula a funcao correspondente a ele baseado no
individuo que chegou'''
if self._doing_train == True:
set_ = self._train_set
else:
set_ = self._test_set
for key, value in set_.iteritems():
function_ = 0
count = 0
operations = ""
for node in functions:
if node == "+" or node == "-" or node == "/" or node == "*":
operations = node
continue
if type(node) is float:
if count == 0:
function_ = node
count = 1
else:
if operations == "+":
function_ += node
elif operations == "-":
function_ -= node
elif operations == "*":
function_ *= node
elif operations == "/":
if math.fabs(node) <= 0.001:
function_ = function
else:
function_ /= node
else:
if count == 0:
function_ = float(value[int(float(node))])
count = 1
else:
if operations == "+":
function_ += float(value[int(node)])
elif operations == "-":
function_ -= float(value[int(node)])
elif operations == "*":
function_ *= float(value[int(node)])
elif operations == "/":
if math.fabs(float(value[int(node)])) <= 0.001:
function_ = function_
else:
function_ /= float(value[int(node)])
function[key] = function_
def BL2XYZ(lat, lon):
R = 6371000.0
#6371km
eps = 1.0E-10
xyz = zeros(3)
if math.fabs(lat - 90) < eps:
xyz[0] = 0
xyz[1] = 0
xyz[2] = R
elif math.fabs(lat + 90) < eps:
xyz[0] = 0
xyz[1] = 0
xyz[2] = -R
else:
xyz[0] = math.cos(lat * math.pi / 180.0) * math.cos(
lon * math.pi / 180.0) * R
xyz[1] = math.cos(lat * math.pi / 180.0) * math.sin(
lon * math.pi / 180.0) * R
xyz[2] = math.sin(lat * math.pi / 180.0) * R
return xyz
def update_metrics(self, value_label, model_value_prediction):
self.mae.append(math.fabs(model_value_prediction - value_label))
class_label = get_class(value_label, self.mode)
model_class_prediction = get_class(model_value_prediction, self.mode)
if model_value_prediction < 0:
return
self.conf['num_rel'] += 1
self.update_confusion(actual_class=class_label,
prediction_class=model_class_prediction)
self.update_prediction_err(actual_val=value_label,
prediction_val=model_value_prediction,
actual_class=class_label,
prediction_class=model_class_prediction)
def XYZ2BL(x, y, z):
blh = zeros(2)
t = math.sqrt(x * x + y * y)
eps = 1.0E-10
if math.fabs(t) < eps:
if z > 0:
blh[0] = 90.0
blh[1] = 0.0
elif z < 0:
blh[0] = -90
blh[1] = 0.0
else:
blh[0] = math.atan(z / t) * 180.0 / math.pi
# -90 to 90
# 0-360
blh[1] = math.atan2(y, x) * 180.0 / math.pi
if blh[1] < 0.0:
blh[1] = blh[1] + 360.0
return blh
def update_err(actual, prediction, false_pes, false_opt):
err = actual - prediction
if err > 0:
false_pes.append(err)
elif err < 0:
false_opt.append(math.fabs(err))
run = 0
canvas = {}
for line in dataset:
arr_LEt = {}
ls_LEt = []
run += 1
ls_L2Etcells = []
ls_line = line.split(",")
acc = float(ls_line[-1]) # acc = net-true/true
ls_acc.append(acc)
ls_run.append(run)
hist.Fill(acc)
sum_single += acc
sum_square += ((acc)**2)
if math.fabs(
float(ls_line[-1])
) < 0.001: # optional; only print epoch with net-true/true < 0.001
ls_LEtcells = []
for i in range(12):
ls_LEtcells.append(float(ls_line[i]))
extent = [0, 11, 3, 0]
fig, ax = pyplot.subplots()
pyplot.title("Pre-processed LEt 12 Weights: Adam Rate = 1, Epoch = " +
str(run))
pyplot.axis('off')
for j in range(0, 4):
arr_LEt[j] = np.asarray([0] * 33).reshape(11, 3).transpose()
ls_LEt.append(arr_LEt[j])
'''
sinsum.py
v. 1 8/27/18
calculate the sine of an angle from the series expansion
'''
# Import factorial from numpy
from numpy import math
# Initialization of variables
# Get the angle from the user
x = input("Enter the angle in degrees: ")
# convert angle to radians
x = x * math.pi / 180
# get the number of terms to compute from user
N = input("Enter number of terms to compute: ")
sum = 0
#create the loop for our calculation
for j in range (0, N+1):
sum = sum + (-1)**j*x**(2*j+1)/math.factorial(2*j+1)
#print out result
print "sin(x) = ", sum
print "Percent error = ", math.fabs((math.sin(x)) - sum) / (math.sin(x)) * 100
