def task_1_ShowBase():
strOf_FuncName = "task_1_ShowBase"
'''###################
step : 1
opening, vars
###################'''
print()
print ("[%s:%d] starting : %s (time=%s)" % (
os.path.basename(os.path.basename(libs.thisfile()))
, libs.linenum()
, strOf_FuncName
, libs.get_TimeLabel_Now()
)
)
'''###################
step : 2
###################'''
# class MyApp(ShowBase):
#
# def __init__(self):
# ShowBase.__init__(self)
#
# # Load the environment model.
# self.scene = self.loader.loadModel("models/environment")
# # Reparent the model to render.
# self.scene.reparentTo(self.render)
# # Apply scale and position transforms on the model.
# self.scene.setScale(0.25, 0.25, 0.25)
#
# #code:20210708_162726
# # valOf_Pos_X, valOf_Pos_Y, valOf_Pos_Z = -100, 42, 0
# # valOf_Pos_X, valOf_Pos_Y, valOf_Pos_Z = -400, 42, 0
# # valOf_Pos_X, valOf_Pos_Y, valOf_Pos_Z = -400, 420, 0
# # valOf_Pos_X, valOf_Pos_Y, valOf_Pos_Z = -400, 42, 100
# valOf_Pos_X, valOf_Pos_Y, valOf_Pos_Z = -800, 42, 0
# # valOf_Pos_X = -100
# # # valOf_Pos_X = -50
# # valOf_Pos_Y = 42
# # valOf_Pos_Z = 0
# self.scene.setPos(valOf_Pos_Y, valOf_Pos_Y, valOf_Pos_Z)
# # self.scene.setPos(-8, 42, 0)
'''###################
step : 3
###################'''
app = MyApp()
print()
print ("[%s:%d] 'MyApp' ==> instantiated" % (
os.path.basename(os.path.basename(libs.thisfile()))
, libs.linenum()
)
)
app.run()
def task_1_Bullet_Hello_World():
strOf_FuncName = "task_1_Bullet_Hello_World"
'''###################
step : 1
opening, vars
###################'''
print()
print ("[%s:%d] starting : %s (time=%s)" % (
os.path.basename(os.path.basename(libs.thisfile()))
, libs.linenum()
, strOf_FuncName
, libs.get_TimeLabel_Now()
)
)
'''###################
step : 2
###################'''
base.cam.setPos(0, -10, 0)
base.cam.lookAt(0, 0, 0)
# World
world = BulletWorld()
world.setGravity(Vec3(0, 0, -9.81))
# Plane
shape = BulletPlaneShape(Vec3(0, 0, 1), 1)
node = BulletRigidBodyNode('Ground')
node.addShape(shape)
np = render.attachNewNode(node)
np.setPos(0, 0, -2)
world.attachRigidBody(node)
# Box
shape = BulletBoxShape(Vec3(0.5, 0.5, 0.5))
node = BulletRigidBodyNode('Box')
node.setMass(1.0)
node.addShape(shape)
np = render.attachNewNode(node)
np.setPos(0, 0, 2)
world.attachRigidBody(node)
model = loader.loadModel('models/box.egg')
model.flattenLight()
model.reparentTo(np)
# Update
def update(task):
dt = globalClock.getDt()
world.doPhysics(dt)
return task.cont
taskMgr.add(update, 'update')
base.run()
'''###################
def test_13_Scale():
strOf_FuncName = "test_13_Scale"
'''###################
step : 1
opening, vars
###################'''
print()
print ("[%s:%d] starting : %s (time=%s)" % (
os.path.basename(os.path.basename(libs.thisfile()))
, libs.linenum()
, strOf_FuncName
, libs.get_TimeLabel_Now()
)
)
'''###################
step : 1.1
load : data
###################'''
'''###################
step : 2
prep
###################'''
#ref https://www.w3schools.com/python/python_ml_multiple_regression.asp
df = pandas.read_csv("cars2.csv")
X = df[['Weight', 'Volume']]
scale = StandardScaler()
'''###################
step : 3
scale
###################'''
scaledX = scale.fit_transform(X)
'''###################
step : 4
report
###################'''
#debug
# message
print ("[%s:%d] scaledX ==>"
%
(
os.path.basename(libs.thisfile())
, libs.linenum()
)
)
print(scaledX)
def test_1():
strOf_FuncName = "test_1"
'''###################
step : 1
opening, vars
###################'''
print()
print("[%s:%d] starting : %s (time=%s)" %
(os.path.basename(os.path.basename(libs.thisfile())), libs.linenum(),
strOf_FuncName, libs.get_TimeLabel_Now()))
'''###################
step : 2
prep
###################'''
aryOf_Numbers = [1, 2, 3, 4, 5]
print()
print(
"[%s:%d] aryOf_Numbers =>" %
(os.path.basename(os.path.basename(libs.thisfile())), libs.linenum()))
print(aryOf_Numbers)
print()
'''###################
step : 3
transposition
###################'''
#code:20210728_132436
# pointOf_Tsp = 0
pointOf_Tsp = 3
print("[%s:%d] pointOf_Tsp => %d" % (os.path.basename(
os.path.basename(libs.thisfile())), libs.linenum(), pointOf_Tsp))
print(
"[%s:%d] calling ... => tsp()" %
(os.path.basename(os.path.basename(libs.thisfile())), libs.linenum()))
print()
#code:20210728_132743
aryOf_Numbers = tsp(aryOf_Numbers, pointOf_Tsp)
# tsp(aryOf_Numbers, pointOf_Tsp)
print(
"[%s:%d] tsp() => complete" %
(os.path.basename(os.path.basename(libs.thisfile())), libs.linenum()))
print(
"[%s:%d] aryOf_Numbers is now ... =>" %
(os.path.basename(os.path.basename(libs.thisfile())), libs.linenum()))
print(aryOf_Numbers)
print()
def build_VTK_File():
fname_In = "data/paradata.%s.vtk" % (libs.get_TimeLabel_Now())
fout = open(fname_In, "w")
grid = 10
dim = grid*2+1
points = dim**3
r = 0.8
fout.write("# vtk DataFile Version 1.0\n")
fout.write("test\n")
fout.write("ASCII\n")
fout.write("DATASET STRUCTURED_POINTS\n")
#ref sprintf https://blog.udemy.com/ruby-sprintf/
fout.write( "DIMENSIONS %d %d %d\n" % (dim, dim, dim))
# fout.write( sprintf("DIMENSIONS %d %d %d\n",dim, dim, dim))
fout.write("ORIGIN 0.0 0.0 0.0\n")
fout.write("ASPECT_RATIO 1.0 1.0 1.0\n")
fout.write("\n")
fout.write( "POINT_DATA %s\n" % (points))
fout.write("SCALARS scalars float\n")
fout.write("LOOKUP_TABLE default\n")
'''###################
data
###################'''
for ix in range(-grid, grid + 1) :
for iy in range(-grid, grid + 1) :
for iz in range(-grid, grid + 1) :
x = ix * 1.0 / grid
y = iy * 1.0 / grid
z = iz * 1.0 / grid
# x = ix.to_f/grid
# y = iy.to_f/grid
# z = iz.to_f/grid
v = r*r - (x*x + y*y + z*z)
if v < 0:
v = 0
fout.write("%d\n" % (v))
else:
fout.write("%.7f\n" % (v))
fout.close()
def test_1():
strOf_FuncName = "test_1"
'''###################
step : 1
opening, vars
###################'''
print()
print("[%s:%d] starting : %s (time=%s)" %
(os.path.basename(os.path.basename(libs.thisfile())), libs.linenum(),
strOf_FuncName, libs.get_TimeLabel_Now()))
'''###################
step : 2
build : string
###################'''
strOf_Coordinates = "(a_i^%d)*(a_j^%d)"
# strOf_Coordinates = "(a_i^k)*(a_i^l)"
# strOf_Coordinates = "a_i^k*a_i^l"
strOf_Formula = ""
# strOf_Formula = strOf_Coordinates
# wedge
#ref https://wiki.python.org/moin/ForLoop
for x in range(1, 4):
for y in range(1, 4):
#ref https://stackoverflow.com/questions/5309978/sprintf-like-functionality-in-python
strOf_Formula += strOf_Coordinates % (x, y)
strOf_Formula += "("
strOf_Formula += "e->_%d∧e->_%d" % (x, y)
# strOf_Formula += "e->_%d" % (x)
strOf_Formula += ")"
strOf_Formula += "+"
#/for x in range(1, 4):
print()
print(
"[%s:%d] strOf_Formula ==> " %
(os.path.basename(os.path.basename(libs.thisfile())), libs.linenum()))
print(strOf_Formula)
print()
'''###################
def test_5__Numbering():
'''###################
prep : get root
###################'''
fpath = cons31.FPath.dpath_In_CSV.value \
+ "/" \
+ cons31.FPath.fname_In_XML.value
### backup
fname_Out_Backup = "%s.copy.%s.mm" % (fpath, libs.get_TimeLabel_Now())
copyfile(fpath, fname_Out_Backup)
'''###################
parse
###################'''
tree = ET.parse(fpath)
tree = libmt.add_Numbering__Through(tree)
# tree = libmt.add_Numbering(tree)
'''###################
append : child
###################'''
# #ref https://stackoverflow.com/questions/31259847/python-appending-children-to-an-already-created-xml-files-root-using-xml-dom
# data1 = ET.Element("node", {"TEXT": "something_" + libs.get_TimeLabel_Now()})
# # data1 = ET.Element("node", {"TEXT": "something_v001.0002.ma"})
#
# data2 = ET.Element("attribute", {"NAME": "created"
#
# , "VALUE" : "18/01/23"
# })
#
# data1.append(data2)
#
# g2[0].append(data1)
#
'''###################
save xml
###################'''
label = "add-numbering-through"
fpath_Out = fpath
# fpath_Out = "new.%s.%s.mm" % (label, libs.get_TimeLabel_Now())
tree.write(fpath_Out)
print()
print ("[%s:%d] mm => written : %s" % \
(os.path.basename(libs.thisfile()), libs.linenum(), fpath_Out))
def test_1():
strOf_FuncName = "test_1"
'''###################
step : 1
opening, vars
###################'''
print()
print("[%s:%d] starting : %s (time=%s)" %
(os.path.basename(os.path.basename(libs.thisfile())), libs.linenum(),
strOf_FuncName, libs.get_TimeLabel_Now()))
# path var
print(
"[%s:%d] PATH variable : " %
(os.path.basename(os.path.basename(libs.thisfile())), libs.linenum()))
print(sys.path)
'''###################
step : 2
sys.argv
###################'''
print()
print(
"[%s:%d] sys.argv ==>" %
(os.path.basename(os.path.basename(libs.thisfile())), libs.linenum()))
print(sys.argv)
'''###################
step : 2 : 1
arg : 2nd arg
###################'''
arg_2 = sys.argv[1]
print()
print(
"[%s:%d] sys.argv[1] ==>" %
(os.path.basename(os.path.basename(libs.thisfile())), libs.linenum()))
print(arg_2)
print("type(arg_2) => ", type(arg_2))
def test_2__WriteFile():
### write file
dpath = "./blog/data"
# dpath = "./blog"
fname_Out = "test.%s.txt" % (libs.get_TimeLabel_Now())
# fname_Out = "./test.%s.txt" % (libs.get_TimeLabel_Now())
fpath = "%s/%s" % (dpath, fname_Out)
f = open(fpath, "w")
# f = open(fname_Out, "w")
# f = open("test.txt", "w")
f.write("yes\n")
f.close()
return fpath
def test_1():
strOf_FuncName = "test_1"
'''###################
step : 1
opening, vars
###################'''
print()
print("[%s:%d] starting : %s (time=%s)" %
(os.path.basename(os.path.basename(libs.thisfile())), libs.linenum(),
strOf_FuncName, libs.get_TimeLabel_Now()))
# path var
print(
"[%s:%d] PATH variable : " %
(os.path.basename(os.path.basename(libs.thisfile())), libs.linenum()))
print(sys.path)
def test_1():
strOf_FuncName = "test_1"
'''###################
step : 1
opening, vars
###################'''
print()
print ("[%s:%d] starting : %s (time=%s)" % (
os.path.basename(os.path.basename(libs.thisfile()))
, libs.linenum()
, strOf_FuncName
, libs.get_TimeLabel_Now()
)
)
'''###################
step : 2
###################'''
fig = plt.figure()
# syntax for 3-D projection
ax = plt.axes(projection ='3d')
# defining all 3 axes
x = [1,1,-1, 2,2,2,2]
y = [-1,1,1, -1,1,2,-2]
z = [1,-1,1, 1/2,-1/2,-1/4,1/4]
# z = np.linspace(0, 1, 100)
# x = z * np.sin(25 * z)
# y = z * np.cos(25 * z)
# plotting
ax.plot3D(x, y, z, 'green')
ax.set_title('3D line plot geeks for geeks')
plt.show()
'''###################
def test_2_statistics_StdDev():
strOf_FuncName = "test_2_statistics_StdDev"
'''###################
step : 1
std
###################'''
print()
print ("[%s:%d] starting : %s (time=%s)" % (
os.path.basename(os.path.basename(libs.thisfile()))
, libs.linenum()
, strOf_FuncName
, libs.get_TimeLabel_Now()
)
)
# from scipy import stats
speed = [99,86,87,88,111,86,103,87,94,78,77,85,86]
x_std = numpy.std(speed)
print()
print("speed : ", speed)
print()
print("x_std : ", x_std)
'''###################
step : 2
variance
###################'''
x_var = numpy.var(speed)
print()
print("x_var : ", x_var)
def test_3_stats_Percentile():
strOf_FuncName = "test_2_statistics_StdDev"
'''###################
step : 1
opening, vars
###################'''
print()
print ("[%s:%d] starting : %s (time=%s)" % (
os.path.basename(os.path.basename(libs.thisfile()))
, libs.linenum()
, strOf_FuncName
, libs.get_TimeLabel_Now()
)
)
#code:20210411_171845
ages = [5,31,43,48,50,41,7,11,15,39,80,82,32,2,8,6,25,36,27,61,31]
numOf_Percentile = 75
'''###################
step : 2
percentile
###################'''
x_Percentile = numpy.percentile(ages, numOf_Percentile)
print()
print("ages : ", ages)
print()
print("x_Percentile : ", x_Percentile)
'''###################
def exec_prog(): # upto : 20180109_161654
'''######################################
get data : raw csv rows
######################################'''
#ref enum https://qiita.com/methane/items/8612bdefd8fa4238cc44
#ref https://docs.python.org/3.5/library/enum.html
fname_In = cons.FPath.dpath_In_CSV.value \
+ "/" \
+ cons.FPath.fname_In_CSV.value
# fname_In = cons.FPath.fpath_In_CSV.value
# fname_In = cons.FPath.fname_In_CSV.value
# fname_In = "../data/49_11_file-io.USDJPY.Period-H1.Days-720.Bars-17280.20171231_233725.csv" #=>
'''### ###'''
header_Length = 2
# header_Length = 3
# skip_Header = True
skip_Header = False
result = libfx.get_ChartData_CSV(\
fname_In, header_Length, skip_Header)
### Validate
if result == None: #if result == None
print ("[%s:%d] get_ChartData_CSV => Returned 'None'" % \
(libs.thisfile(), libs.linenum()))
# print "[%s:%d] get_ChartData_CSV => Returned 'None'" % \
# (libs.thisfile(), libs.linenum())
return
#/if result == None
### report
print()
print("[%s:%d] CSV rows => %d" %
(os.path.basename(libs.thisfile()), libs.linenum(), len(result)))
print()
print("[%s:%d] row[%d] => %s" %
(os.path.basename(libs.thisfile()), libs.linenum(), 0, result[0]))
print()
'''######################################
Conv : CSV rows ---> array of BarData class instances
######################################'''
# aryOf_BarDatas = libfx.conv_CSVRows_2_BarDatas(result)
aryOf_BarDatas = libfx.conv_CSVRows_2_BarDatas(result[header_Length:])
### Validate
if aryOf_BarDatas == None: #if aryOf_BarDatas == None
print("[%s:%d] aryOf_BarDatas => None" %
(os.path.basename(libs.thisfile()), libs.linenum()))
print()
return
#/if aryOf_BarDatas == None
'''###################
get : high-lows
###################'''
id_Start = cons.BarData.HighLowDiff_ID_Start.value
id_End = cons.BarData.HighLowDiff_ID_End.value
# typeOf_Data = cons.typeOf_Data_OPENCLOSE
# typeOf_Data = "OpenClose"
result_HighLowDiffs = libfx.get_HighLowDiffs(aryOf_BarDatas, id_Start,
id_End)
# result = libfx.get_HighLowDiffs(aryOf_BarDatas, typeOf_Data, id_Start, id_End)
print ("[%s:%d] result => %s" % \
(libs.thisfile(), libs.linenum(), result_HighLowDiffs))
# print "[%s:%d] result[%s] => %s" % \
# (libs.thisfile(), libs.linenum(), cons.LABEL_OC, result_HighLowDiffs[cons.LABEL_OC])
# print "[%s:%d] result[%s] => %s" % \
# (libs.thisfile(), libs.linenum(), cons.LABEL_HL, result_HighLowDiffs[cons.LABEL_HL])
print()
'''###################
add : data
###################'''
whole_Data = {}
whole_Data['data'] = result_HighLowDiffs
print()
print("[%s:%d] whole data =>" %
(os.path.basename(libs.thisfile()), libs.linenum()))
print(whole_Data)
'''###################
build : meta info
###################'''
dictOf_MetaInfo = libfx.get_BarData_MetaInfo(fname_In, header_Length)
print()
print ("[%s:%d] dictOf_MetaInfo => %s" % \
(os.path.basename(libs.thisfile()), libs.linenum(), dictOf_MetaInfo))
print()
### add : meta info
whole_Data['meta'] = dictOf_MetaInfo
'''###################
write to file
###################'''
# [82_1.py:163] dictOf_MetaInfo => {'PAIR': 'USDJPY', 'PERIOD': 'H1', 'DAYS': '720
# ', 'SHIFT': '1'}
# fname_Out_HighLowDiffs = \
fpath_Out_HighLowDiffs = \
cons.FPath.fpath_Out_HighLowDiff.value \
+ "/" \
+ "_HighLowDiff_." \
+ cons.Label_ColNames.PAIR.value + "-" \
+ dictOf_MetaInfo[cons.Label_ColNames.PAIR.value] \
+ "." \
+ cons.Label_ColNames.PERIOD.value + "-" \
+ dictOf_MetaInfo[cons.Label_ColNames.PERIOD.value] \
+ "." \
+ cons.Label_ColNames.DAYS.value + "-" \
+ dictOf_MetaInfo[cons.Label_ColNames.DAYS.value] \
+ "." \
+ cons.Label_ColNames.SHIFT.value + "-" \
+ dictOf_MetaInfo[cons.Label_ColNames.SHIFT.value] \
+ "." \
+ libs.get_TimeLabel_Now() \
+ ".csv"
# + ".txt"
print ("[%s:%d] fname out => %s" % \
(os.path.basename(libs.thisfile()), libs.linenum(), fpath_Out_HighLowDiffs))
### write to file
f_Out = open(fpath_Out_HighLowDiffs, "w")
'''###################
meta info
###################'''
f_Out.write(
'\t'.join(
[cons.Label_ColNames.PAIR.value, \
cons.Label_ColNames.PERIOD.value, \
cons.Label_ColNames.DAYS.value, \
cons.Label_ColNames.SHIFT.value, \
"id_Start", \
"id_End", \
"source csv"
])
)
f_Out.write('\n')
f_Out.write(
'\t'.join(
[
dictOf_MetaInfo[cons.Label_ColNames.PAIR.value], \
dictOf_MetaInfo[cons.Label_ColNames.PERIOD.value], \
dictOf_MetaInfo[cons.Label_ColNames.DAYS.value], \
dictOf_MetaInfo[cons.Label_ColNames.SHIFT.value], \
str(id_Start), \
str(id_End), \
cons.FPath.fname_In_CSV.value
])
)
f_Out.write('\n')
f_Out.write("\t\t\t\t" \
+ aryOf_BarDatas[id_Start - 1].dateTime_Local \
+ '\t' \
+ aryOf_BarDatas[id_End - 1].dateTime_Local
)
f_Out.write('\n')
'''###################
High, low, diff
###################'''
# f_Out.write('\t'.join([cons.BarData.LABEL_OC.value].extend(result_HighLowDiffs[cons.BarData.LABEL_OC.value])))
# tmp = [cons.BarData.LABEL_OC.value]
# tmp = result_HighLowDiffs[cons.BarData.LABEL_OC.value]
# tmp = [cons.BarData.LABEL_OC.value].extend(['aaa'])
# tmp = [cons.BarData.LABEL_OC.value] \
# .extend(result_HighLowDiffs[cons.BarData.LABEL_OC.value])
### OC
tmp = [cons.BarData.LABEL_OC.value]
tmp.extend(result_HighLowDiffs[cons.BarData.LABEL_OC.value])
f_Out.write('\t'.join([str(x) for x in tmp]))
# f_Out.write('\t'.join(tmp))
f_Out.write('\n')
### HL
tmp = [cons.BarData.LABEL_HL.value]
tmp.extend(result_HighLowDiffs[cons.BarData.LABEL_HL.value])
f_Out.write('\t'.join([str(x) for x in tmp]))
# f_Out.write('\t'.join(tmp))
f_Out.write('\n')
### RSI
tmp = [cons.BarData.LABEL_RSI.value]
tmp.extend(result_HighLowDiffs[cons.BarData.LABEL_RSI.value])
f_Out.write('\t'.join([str(x) for x in tmp]))
# f_Out.write('\t'.join(tmp))
f_Out.write('\n')
### MFI
tmp = [cons.BarData.LABEL_MFI.value]
tmp.extend(result_HighLowDiffs[cons.BarData.LABEL_MFI.value])
f_Out.write('\t'.join([str(x) for x in tmp]))
# f_Out.write('\t'.join(tmp))
f_Out.write('\n')
### BB_MAIN
tmp = [cons.BarData.LABEL_BB_MAIN.value]
tmp.extend(result_HighLowDiffs[cons.BarData.LABEL_BB_MAIN.value])
f_Out.write('\t'.join([str(x) for x in tmp]))
# f_Out.write('\t'.join(tmp))
f_Out.write('\n')
### BB_1S
tmp = [cons.BarData.LABEL_BB_1S.value]
tmp.extend(result_HighLowDiffs[cons.BarData.LABEL_BB_1S.value])
f_Out.write('\t'.join([str(x) for x in tmp]))
# f_Out.write('\t'.join(tmp))
f_Out.write('\n')
### BB_2S
tmp = [cons.BarData.LABEL_BB_2S.value]
tmp.extend(result_HighLowDiffs[cons.BarData.LABEL_BB_2S.value])
f_Out.write('\t'.join([str(x) for x in tmp]))
# f_Out.write('\t'.join(tmp))
f_Out.write('\n')
### BB_M1S
tmp = [cons.BarData.LABEL_BB_M1S.value]
tmp.extend(result_HighLowDiffs[cons.BarData.LABEL_BB_M1S.value])
f_Out.write('\t'.join([str(x) for x in tmp]))
# f_Out.write('\t'.join(tmp))
f_Out.write('\n')
### BB_M2S
tmp = [cons.BarData.LABEL_BB_M2S.value]
tmp.extend(result_HighLowDiffs[cons.BarData.LABEL_BB_M2S.value])
f_Out.write('\t'.join([str(x) for x in tmp]))
# f_Out.write('\t'.join(tmp))
f_Out.write('\n')
# print()
# print ("[%s:%d] OC data => " % (os.path.basename(libs.thisfile()), libs.linenum()))
# print(tmp)
# print()
'''###################
file : close
###################'''
f_Out.close()
print()
print ("[%s:%d] file closed => %s" % \
(os.path.basename(libs.thisfile()), libs.linenum(), fpath_Out_HighLowDiffs))
print()
# #test
# print()
# print ("[%s:%d] aryOf_BarDatas[id_Start(%d)] => %s" % \
# (os.path.basename(libs.thisfile()), libs.linenum(),
# id_Start, aryOf_BarDatas[id_Start]))
#
# print(aryOf_BarDatas[id_Start].dateTime_Local)
# # print(aryOf_BarDatas[id_Start])
#
# print()
'''###################
Report
###################'''
print("[%s:%d] exec_prog => done" %
(os.path.basename(libs.thisfile()), libs.linenum()))
def task_1_PyBullet_Hello_World():
strOf_FuncName = "task_1_PyBullet_Hello_World"
'''###################
step : 1
opening, vars
###################'''
print()
print ("[%s:%d] starting : %s (time=%s)" % (
os.path.basename(os.path.basename(libs.thisfile()))
, libs.linenum()
, strOf_FuncName
, libs.get_TimeLabel_Now()
)
)
'''###################
step : 2
tut codes
https://docs.google.com/document/d/10sXEhzFRSnvFcl3XxNGhnD4N2SedqwdAvK3dsihxVUA/edit#
###################'''
physicsClient = p.connect(p.GUI)#or p.DIRECT for non-graphical version
p.setAdditionalSearchPath(pybullet_data.getDataPath()) #optionally
p.setGravity(0,0,-10)
print()
print ("[%s:%d] tut : first 3 lines" % (
os.path.basename(os.path.basename(libs.thisfile()))
, libs.linenum()
)
)
print("type(physicsClient).__name__ ==> ", type(physicsClient).__name__)
print() # separator line
'''###################
step : 2 : 2
###################'''
planeId = p.loadURDF("plane.urdf")
startPos = [0,0,1]
startOrientation = p.getQuaternionFromEuler([0,0,0])
boxId = p.loadURDF("r2d2.urdf",startPos, startOrientation)
print ("[%s:%d] tut : next 4 lines" % (
os.path.basename(os.path.basename(libs.thisfile()))
, libs.linenum()
)
)
print("type(planeId).__name__ ==> ", type(planeId).__name__)
print() # separator line
#n:20210715_180327
#set the center of mass frame (loadURDF sets base link frame) startPos/Ornp.resetBasePositionAndOrientation(boxId, startPos, startOrientation)
for i in range (10000):
p.stepSimulation()
time.sleep(1./240.)
#debug:20210717_174601
print ("[%s:%d] for loop ==> ended" % (
os.path.basename(os.path.basename(libs.thisfile()))
, libs.linenum()
)
)
print() # separator line
cubePos, cubeOrn = p.getBasePositionAndOrientation(boxId)
print("cubePos = %d, cubeOrn = %d" % (cubePos, cubeOrn))
# print(cubePos,cubeOrn)
p.disconnect()
print ("[%s:%d] pybullet ==> disconnected" % (
os.path.basename(os.path.basename(libs.thisfile()))
, libs.linenum()
)
)
print() # separator line
'''###################
def test_1():
strOf_FuncName = "test_1"
'''###################
step : 1
opening, vars
###################'''
print()
print("[%s:%d] starting : %s (time=%s)" %
(os.path.basename(os.path.basename(libs.thisfile())), libs.linenum(),
strOf_FuncName, libs.get_TimeLabel_Now()))
print()
'''###################
step : 2
data : load
###################'''
#mark:20210421_164025
iris_dataset = load_iris()
#debug
print("[%s:%d] load_iris => done" %
(os.path.basename(libs.thisfile()), libs.linenum()))
# print("iris_dataset['DESCR'] ==>")
# print(iris_dataset['DESCR'])
# print(iris_dataset)
'''###################
step : 3
data : train
###################'''
X_train, X_test, y_train, y_test = train_test_split(iris_dataset["data"],
iris_dataset["target"],
random_state=0)
#debug
print("[%s:%d] train_test_split => done" %
(os.path.basename(libs.thisfile()), libs.linenum()))
# print("X_train ==>")
# print(X_train)
#
# print()
# print("X_test ==>")
# print(X_test)
'''###################
step : 4
data : neighbor
###################'''
'''###################
step : 4 : 1
data : setup
###################'''
kn = KNeighborsClassifier(n_neighbors=1)
#debug
print("[%s:%d] KNeighborsClassifier => done" %
(os.path.basename(libs.thisfile()), libs.linenum()))
print("kn ==>")
print(kn)
'''###################
step : 4 : 2
data : fit
###################'''
kn.fit(X_train, y_train)
#debug
print("[%s:%d] KNeighborsClassifier : fit => done" %
(os.path.basename(libs.thisfile()), libs.linenum()))
print("kn ==>")
print(kn)
'''###################
step : 4 : 3
data : prep
###################'''
x_new = np.array([[5, 2.9, 1, 0.2]])
#debug
print("[%s:%d] np.array => done" %
(os.path.basename(libs.thisfile()), libs.linenum()))
print("x_new ==>")
print(x_new)
'''###################
step : 5
data : predict
###################'''
prediction = kn.predict(x_new)
#debug
print("[%s:%d] predict => done" %
(os.path.basename(libs.thisfile()), libs.linenum()))
# print("prediction ==>")
# print(prediction)
'''###################
step : 6
results
###################'''
prediction = kn.predict(x_new)
#debug
print("[%s:%d] results => " %
(os.path.basename(libs.thisfile()), libs.linenum()))
print("probe data =>")
print(x_new)
print()
print("Predicted target value: {}\n".format(prediction))
print("Predicted feature name: {}\n".format(
iris_dataset["target_names"][prediction]))
print("Test score: {:.2f}".format(kn.score(X_test, y_test)))
#debug
print("[%s:%d] X_test => " %
(os.path.basename(libs.thisfile()), libs.linenum()))
print("X_test =>")
print(X_test)
print()
print("y_test =>")
print(y_test)
'''###################
def test_S_14_No_2_Scipy():
strOf_FuncName = "test_S_14_No_2_Scipy"
'''###################
step : 1
opening, vars
###################'''
#ref https://stackoverflow.com/questions/56711424/how-can-i-count-time-in-python-3
t_start = time.time()
print()
print("[%s:%d] starting : %s (time=%s)" %
(os.path.basename(os.path.basename(libs.thisfile())), libs.linenum(),
strOf_FuncName, libs.get_TimeLabel_Now()))
print()
'''###################
step : 2
data : prep
###################'''
x = np.array([[1, 2], [3, 4]])
y = np.array([[5, 6], [7, 8]])
#debug
print("[%s:%d] x, y :" %
(os.path.basename(libs.thisfile()), libs.linenum()))
print(x)
print(y)
v = np.array([9, 10])
w = np.array([11, 12])
'''###################
step : 2 : 1
inner prod
###################'''
valOf_InnerProd = np.dot(v, w)
#debug
print("[%s:%d] valOf_InnerProd :" %
(os.path.basename(libs.thisfile()), libs.linenum()))
print(v)
print(w)
print(valOf_InnerProd)
print()
'''###################
step : 2 : 2
vector prod
###################'''
valOf_Vector_Prod = np.dot(x, v)
#debug
print("[%s:%d] valOf_Vector_Prod :" %
(os.path.basename(libs.thisfile()), libs.linenum()))
print(x)
print(v)
print(valOf_Vector_Prod)
print()
'''###################
step : 2 : 3
prod : matrix
###################'''
valOf_Prod_Matrix = np.dot(x, y)
#debug
print("[%s:%d] valOf_Prod_Matrix :" %
(os.path.basename(libs.thisfile()), libs.linenum()))
print(x)
print(y)
print(valOf_Prod_Matrix)
print()
'''###################
step : 2 : 1
data : store
###################'''
'''###################
step : 6
results
###################'''
'''###################
step : 6 : 1
time
###################'''
t_end = time.time()
#debug
# print ("[%s:%d] time => %s"
#ref https://www.pythonpool.com/python-float-to-string/#5_Using_NumPy
print("[%s:%d] time => %.03f sec" %
(os.path.basename(libs.thisfile()), libs.linenum(),
(t_end - t_start)))
print()
'''###################
def main_20210506_164920():
strOf_FuncName = "main_20210506_164920()"
'''###################
step : 1
opening, vars
###################'''
#ref https://stackoverflow.com/questions/56711424/how-can-i-count-time-in-python-3
t_start = time.time()
print()
print("[%s:%d] starting : %s (time=%s)" %
(os.path.basename(os.path.basename(libs.thisfile())), libs.linenum(),
strOf_FuncName, libs.get_TimeLabel_Now()))
print()
'''###################
step : 2
vars
###################'''
#code:20210506_170631
dataset = np.array([['Asset Flip', 100, 1000], ['Text Based', 500, 3000],
['Visual Novel', 1500, 5000],
['2D Pixel Art', 3500, 8000],
['2D Vector Art', 5000, 6500],
['Strategy', 6000, 7000],
['First Person Shooter', 8000, 15000],
['Simulator', 9500, 20000], ['Racing', 12000, 21000],
['RPG', 14000, 25000], ['Sandbox', 15500, 27000],
['Open-World', 16500, 30000], ['MMOFPS', 25000, 52000],
['MMORPG', 30000, 80000]])
print(
"[%s:%d] dataset =>" %
(os.path.basename(os.path.basename(libs.thisfile())), libs.linenum()))
# print the dataset
print(dataset)
print()
'''###################
step : 3
data : select
###################'''
# select all rows by : and column 1
# by 1:2 representing features
X = dataset[:, 1:2].astype(int)
print(
"[%s:%d] X = dataset[:, 1:2] =>" %
(os.path.basename(os.path.basename(libs.thisfile())), libs.linenum()))
# print X
print(X)
print()
'''###################
step : 4
data : select
###################'''
#code:20210506_171149
# select all rows by : and column 2
# by 2 to Y representing labels
y = dataset[:, 2].astype(int)
print(
"[%s:%d] y = dataset[:, 2] =>" %
(os.path.basename(os.path.basename(libs.thisfile())), libs.linenum()))
# print y
print(y)
print()
'''###################
step : 5
regressor
###################'''
# create a regressor object
regressor = DecisionTreeRegressor(random_state=0)
# fit the regressor with X and Y data
regressor.fit(X, y)
print(
"[%s:%d] regressor =>" %
(os.path.basename(os.path.basename(libs.thisfile())), libs.linenum()))
# print y
print(regressor)
print()
'''###################
step : 6
predict
###################'''
#code:20210506_172247
valOf_Target_Val = 3750
# test the output by changing values, like 3750
y_pred = regressor.predict(
valOf_Target_Val) #=> 3,7550 as a val for 2nd column
# y_pred = regressor.predict(3750) #=> 3,7550 as a val for 2nd column
print("[%s:%d] y_pred => (for target : %d" % (os.path.basename(
os.path.basename(libs.thisfile())), libs.linenum(), valOf_Target_Val))
# print the predicted price
print("Predicted price: % d\n" % y_pred)
print()
#n:20210506_172536
'''###################
step : 2 : 1
data : store
###################'''
'''###################
step : 6
results
###################'''
'''###################
step : 6 : 1
time
###################'''
t_end = time.time()
#debug
# print ("[%s:%d] time => %s"
#ref https://www.pythonpool.com/python-float-to-string/#5_Using_NumPy
print("[%s:%d] time => %.03f sec" %
(os.path.basename(libs.thisfile()), libs.linenum(),
(t_end - t_start)))
print()
'''###################
def test_1():
strOf_FuncName = "test_1"
'''###################
step : 1
opening, vars
###################'''
print()
print("[%s:%d] starting : %s (time=%s)" %
(os.path.basename(os.path.basename(libs.thisfile())), libs.linenum(),
strOf_FuncName, libs.get_TimeLabel_Now()))
'''###################
step : 2
prep
###################'''
'''###################
step : 3
###################'''
a = math.pi
cos_a = math.cos(a)
print()
print("[%s:%d] a = %.03f / cos(a) = %.03f" % (os.path.basename(
os.path.basename(libs.thisfile())), libs.linenum(), a, cos_a))
'''###################
step : 4
###################'''
'''###################
step : 4 : 1
prep : data
###################'''
'''###################
step : 4 : 1 :
prep : data : basics
###################'''
#ref https://numpy.org/doc/stable/reference/generated/numpy.linspace.html
# numOf_Data_X = 12
numOf_Data_X = 24
valOf_Linspace_Start = -math.pi / 2
valOf_Linspace_End = math.pi / 2
# valOf_Linspace_Start = 0
# valOf_Linspace_End = math.pi
#ref https://matplotlib.org/stable/tutorials/introductory/customizing.html#sphx-glr-tutorials-introductory-customizing-py
data_x = np.linspace(valOf_Linspace_Start, valOf_Linspace_End,
numOf_Data_X)
'''###################
step : 4 : 1 : 2
prep : data : cosine values
###################'''
k = 1
data_x_1 = [(2 * k + 1) * x for x in data_x]
data_y = np.cos(data_x)
data_y_1 = np.cos(data_x_1)
data_y_1_final = [math.pow(-1, k) / (2 * k + 1) * x for x in data_y_1]
print()
print("[%s:%d] numOf_Data_X = %d" % (os.path.basename(
os.path.basename(libs.thisfile())), libs.linenum(), numOf_Data_X))
print()
# print ("[%s:%d] data_x =>" % (
# os.path.basename(os.path.basename(libs.thisfile()))
# , libs.linenum()
# )
# )
#
# print(data_x)
#
# print ("[%s:%d] data_y =>" % (
# os.path.basename(os.path.basename(libs.thisfile()))
# , libs.linenum()
# )
# )
#
# print(data_y)
'''###################
step : 4 : 2
plot
###################'''
'''###################
step : 4 : 2 : 1
plot : prep savefig
###################'''
strOf_Time_Label = libs.get_TimeLabel_Now()
#ref C:\WORKS_2\WS\WS_Others.JVEMV6\JVEMV6\73_ai\1_start\1_1.py
fig = plt.figure()
dpath_PlotImage = "./data"
fname_PlotImage = "plot_image_%s_[test]" % (strOf_Time_Label)
fpath_PlotImage = os.path.join(dpath_PlotImage, fname_PlotImage)
# title
# plt.title("cos(a)\n numOf_Data_X = %d\n x [%.02f, %.02f]"
# plt.title("cos(a), data_y_1\n numOf_Data_X = %d\n x [%.02f, %.02f]"
plt.title("cos(a), data_y_1_final\n numOf_Data_X = %d\n x [%.02f, %.02f]" %
(numOf_Data_X, valOf_Linspace_Start, valOf_Linspace_End))
# axis
#ref https://matplotlib.org/stable/tutorials/introductory/pyplot.html#sphx-glr-tutorials-introductory-pyplot-py
plt.axis([-math.pi / 2, math.pi / 2, -1.5, 1.5])
# plt.axis([- math.pi/2, math.pi/2, -1.0, 1.0])
'''###################
step : 4 : 2 : 2
plot : set data
###################'''
plt.plot(data_x, data_y + data_y_1_final, 'y-o')
plt.plot(data_x, data_y_1_final, 'b-o')
plt.plot(data_x, data_y, 'r-o')
# plt.plot(data_x, data_y_1, 'r-o')
# plt.plot(data_x, data_y, 'r-o')
# plt.show()
'''###################
step : 4 : 2 : 3
plot : save image
###################'''
fig.savefig(fpath_PlotImage)
print("[%s:%d] plot image saved => %s" % (os.path.basename(
os.path.basename(libs.thisfile())), libs.linenum(), fpath_PlotImage))
def test_2_1():
'''###################
ops
###################'''
init_Val = 10
a = [10 for x in range(10)]
b = [10 for x in range(10)]
# de-homogenize
#ref mean https://stackoverflow.com/questions/9039961/finding-the-average-of-a-list answered Jan 28 '12 at 3:59
a[-1] = 5
b[-1] = 5
# a[-1] = 9
# b[-1] = 9
'''###################
write file
###################'''
# fname_Out = "data/pval.a-%d.%s.txt" % \
label = "test_2_1"
fname_Out = "data/pval.%s.%s.txt" % \
(
label
, libs.get_TimeLabel_Now()
)
# fname_Out = "/data/pval.%s.txt" % (libs.get_TimeLabel_Now())
fout = open(fname_Out, "w")
'''###################
correl : basic
###################'''
msg = "[%s:%d] a=\n" % (os.path.basename(libs.thisfile()), libs.linenum())
fout.write(msg)
# fout.write("a=\n")
fout.write(','.join([str(x) for x in a]))
# fout.write(','.join(a))
fout.write('\n')
fout.write('\n')
msg = "[%s:%d] b=\n" % (os.path.basename(libs.thisfile()), libs.linenum())
fout.write(msg)
# fout.write("b=\n")
fout.write(','.join([str(x) for x in b]))
# fout.write(','.join(b))
fout.write('\n')
fout.write('\n')
'''###################
correl : basic
###################'''
lo_Final = []
for i in range(10):
# tmp list
lo_Tmp = []
### copy a
#ref copy https://stackoverflow.com/questions/2612802/how-to-clone-or-copy-a-list answered Apr 10 '10 at 8:55
a_ = copy.copy(a)
lo_Tmp.append(i)
a1 = stats.pearsonr(a_, b)
print()
print("[%s:%d] i => %d / a1 =>" % \
(os.path.basename(libs.thisfile()), libs.linenum()
,i
), file=sys.stderr)
print(a1)
print("a_ =>")
print(a_)
print("b =>")
print(b)
a_[i] /= 2.0
a2 = stats.pearsonr(a_, b)
print()
print("a1 => ")
print(a1)
print("a_ =>")
print(a_)
print("b =>")
print(b)
a_[i] = 0
a3 = stats.pearsonr(a_, b)
### append
lo_Tmp.append(a1)
lo_Tmp.append(a2)
lo_Tmp.append(a3)
#debug
print()
print("[%s:%d] lo_Tmp =>" % \
(os.path.basename(libs.thisfile()), libs.linenum()
), file=sys.stderr)
print(lo_Tmp)
### append
lo_Final.append(lo_Tmp)
'''###################
write
###################'''
fout.write("index\t=1.0\t/2.0\t=0")
fout.write("\n")
for item in lo_Final:
#debug
print()
print("[%s:%d] item =>" % \
(os.path.basename(libs.thisfile()), libs.linenum()
), file=sys.stderr)
print(item)
# print(item[0])
# print('\t')
# print('\n')
fout.write("%d\t%.10f\t%.10f\t%.10f" % \
# fout.write("%d\t%.4f\t%.4f\t%.4f" % \
(
item[0], item[1][0], item[2][0], item[3][0]
)
)
# print("%.4f %.4f %.4f" % (item[1][0], item[2][0], item[3][0]))
fout.write('\n')
'''###################
file : close
###################'''
fout.close()
# msg = "[%s:%d] \na[%d]\tcorrel" % \
# (
# os.path.basename(libs.thisfile()), libs.linenum()
# , index_a
# )
# fout.write(msg)
#
# fout.write('\n')
# fout.write('\n')
return None
def test_2():
'''###################
prep : get root
###################'''
fpath = cons31.FPath.dpath_In_CSV.value \
+ "/" \
+ cons31.FPath.fname_In_XML.value
tree = ET.parse(fpath)
root = tree.getroot()
'''###################
nodes : g-1
###################'''
print()
print ("[%s:%d] root.tag => '%s' / root.attrib => '%s'" % \
(os.path.basename(libs.thisfile()), libs.linenum()
, root.tag, root.attrib))
g1 = root[0]
print()
print ("[%s:%d] g1.tag => '%s' / g1.attrib => '%s'" % \
(os.path.basename(libs.thisfile()), libs.linenum()
, g1.tag, g1.attrib))
'''###################
nodes : g-2
###################'''
g2 = []
lenOf_g2 = len(g1)
for i in range(lenOf_g2):
g2.append(g1[i])
#/for i in range(lenOf_g2):
#debug
for item in g2:
attrib_Created = item.get('CREATED')
#ref append child https://stackoverflow.com/questions/31259847/python-appending-children-to-an-already-created-xml-files-root-using-xml-dom "answered Jul 8 '15 at 11:26"
data2 = ET.Element("attribute", {
"NAME": "created",
"VALUE": attrib_Created
})
item.append(data2)
# print()
# print ("[%s:%d] item.tag = '%s' | item.get('CREATED') = '%s'" % \
# (os.path.basename(libs.thisfile()), libs.linenum()
# , item.tag, item.get('CREATED')))
#/for item in g2:
'''###################
append : child
###################'''
# #ref https://stackoverflow.com/questions/31259847/python-appending-children-to-an-already-created-xml-files-root-using-xml-dom
# data1 = ET.Element("node", {"TEXT": "something_" + libs.get_TimeLabel_Now()})
# # data1 = ET.Element("node", {"TEXT": "something_v001.0002.ma"})
#
# data2 = ET.Element("attribute", {"NAME": "created"
#
# , "VALUE" : "18/01/23"
# })
#
# data1.append(data2)
#
# g2[0].append(data1)
#
'''###################
save xml
###################'''
label = "add_Attrib_Created"
fpath_Out = "new.%s.%s.mm" % (label, libs.get_TimeLabel_Now())
tree.write(fpath_Out)
print()
print("[%s:%d] xml => written : %s" %
(os.path.basename(libs.thisfile()), libs.linenum(), fpath_Out))
def exec_prog(): #
'''###################
prep : text
###################'''
# fin = open("article.txt", "r", encoding='CP932')
# # fin = open("article.txt", "r", encoding='shift-jis')
# # fin = open("article.txt", "r", encoding='UTF-8')
# # fin = open("article.txt", "r")
#
# text = fin.read()
#
# fin.close()
#
# print(text)
# regex
#ref https://stackoverflow.com/questions/4995892/python-split-string-on-regex
p = re.compile('[。、]')
ary = p.split(text)
# ary = text.split("。")
# ary of num
aryOf_TokenLen = []
for item in ary:
lenOf_Item = len(item)
# print ("len => %d [%s]" % (lenOf_Item, item))
if lenOf_Item > 5: aryOf_TokenLen.append(lenOf_Item)
# aryOf_TokenLen.append(lenOf_Item)
### report
print ("[%s:%d] average => %.3f" % \
(os.path.basename(libs.thisfile()), libs.linenum(),
#ref sum https://stackoverflow.com/questions/4362586/sum-a-list-of-numbers-in-python
sum(aryOf_TokenLen) / len(aryOf_TokenLen)))
# aryOf_TokenLen.sum() / len(aryOf_TokenLen)))
print(aryOf_TokenLen)
'''###################
write to file
###################'''
fname = "data/report.%s.txt" % (libs.get_TimeLabel_Now())
f = open(fname, "w")
#ref sort https://www.tutorialspoint.com/python/list_sort.htm
aryOf_TokenLen__Sorted = aryOf_TokenLen.sort()
# get max
len_Max = -1
for item in aryOf_TokenLen:
# get max
if len_Max < item: len_Max = item
for i in range(item):
f.write("*")
# return
f.write("\n")
f.close()
print ("[%s:%d] file => closed : %s" % \
(os.path.basename(libs.thisfile()), libs.linenum(), fname))
print ("[%s:%d] max len => %d" % \
(os.path.basename(libs.thisfile()), libs.linenum(), len_Max))
'''###################
Out : histogram
###################'''
aryOf_Histogram = {}
#test
print()
print(range(len_Max))
# init
for i in range(len_Max + 1):
aryOf_Histogram[i] = 0
# for i in range(len_Max) : aryOf_Histogram[i] = 0
for item in aryOf_TokenLen:
aryOf_Histogram[item] += 1
### report
print()
print(aryOf_Histogram)
### write to file
fname = "data/report.histogram.%s.txt" % (libs.get_TimeLabel_Now())
f = open(fname, "w")
for i in range(len_Max + 1):
f.write("%d : " % (i))
for j in range(aryOf_Histogram[i]):
f.write("*")
# return
f.write("\n")
f.close()
print ("[%s:%d] file => closed : %s" % \
(os.path.basename(libs.thisfile()), libs.linenum(), fname))
'''###################
Out : raw data
###################'''
### write to file
fname = "data/report.rawdata.%s.txt" % (libs.get_TimeLabel_Now())
f = open(fname, "w")
for i in aryOf_TokenLen:
f.write("%d" % i)
# return
f.write("\n")
f.close()
print ("[%s:%d] file => closed : %s" % \
(os.path.basename(libs.thisfile()), libs.linenum(), fname))
# '''###################
# Out : sentences
# ###################'''
# ### write to file
# fname = "data/report.sentences.%s.txt" % (libs.get_TimeLabel_Now())
#
# f = open(fname, "wb")
# # f = open(fname, "w")
#
# for i in ary :
#
# # f.write(i) #=> UnicodeEncodeError: 'cp932' codec can't encode character '\u2003'
# # f.write("%s" % i) #=> UnicodeEncodeError: 'cp932' codec can't encode character '\u2003'
# # f.write(i.encode('utf-8'))
# # f.write(i.decode('utf-8')) #=> AttributeError: 'str' object has no attribute 'decode'
# # f.write(i.encode('utf-8')) #=> TypeError: write() argument must be str, not bytes
# # f.write("%s" % i.encode('utf-8')) #=> TypeError: write() argument must be str, not bytes
# f.write(i.encode('utf-8')) #=>
# # f.write(i.decode('ascii', 'ignore')) #=> AttributeError: 'str' object has no attribute 'decode'
# # return
# f.write("\n")
#
# f.close()
#
# print ("[%s:%d] file => closed : %s" % \
# (os.path.basename(libs.thisfile()), libs.linenum(), fname))
#
'''###################
Report
###################'''
print("[%s:%d] exec_prog => done" %
(os.path.basename(libs.thisfile()), libs.linenum()))
def test_4():
'''###################
prep : get root
###################'''
fpath = cons31.FPath.dpath_In_CSV.value \
+ "/" \
+ cons31.FPath.fname_In_XML.value
### backup
fname_Out_Backup = "%s.copy.%s.mm" % (fpath, libs.get_TimeLabel_Now())
copyfile(fpath, fname_Out_Backup)
'''###################
parse
###################'''
tree = ET.parse(fpath)
tree = libmt.add_Node_Attribute_Created(tree)
# root = tree.getroot()
#
# '''###################
# nodes : g-1
# ###################'''
# print()
# print ("[%s:%d] root.tag => '%s' / root.attrib => '%s'" % \
# (os.path.basename(libs.thisfile()), libs.linenum()
# , root.tag, root.attrib))
#
# g1 = root[0]
#
# print()
# print ("[%s:%d] g1.tag => '%s' / g1.attrib => '%s'" % \
# (os.path.basename(libs.thisfile()), libs.linenum()
# , g1.tag, g1.attrib))
#
# '''###################
# nodes : g-2
# ###################'''
# g2 = []
#
# lenOf_g2 = len(g1)
#
# for i in range(lenOf_g2):
#
# g2.append(g1[i])
#
# #/for i in range(lenOf_g2):
#
# #debug
# for item in g2:
#
# for subitem in item:
#
# if subitem.tag == 'attribute' : #if subitem.tag == 'attribute'
#
# item.remove(subitem)
#
# print()
# print ("[%s:%d] item.tag = '%s', subitem.tag = '%s'" % \
# (os.path.basename(libs.thisfile()), libs.linenum()
# , item.tag, subitem.tag))
#/if subitem.tag == 'attribute'
#/for subitem in item:
# attrib_Created = item.get('CREATED')
#
# #ref append child https://stackoverflow.com/questions/31259847/python-appending-children-to-an-already-created-xml-files-root-using-xml-dom "answered Jul 8 '15 at 11:26"
# data2 = ET.Element("attribute"
# , {"NAME": "created"
# , "VALUE" : attrib_Created
# })
# item.remove('attribute')
# item.append(data2)
# print()
# print ("[%s:%d] item.tag = '%s' | item.get('CREATED') = '%s'" % \
# (os.path.basename(libs.thisfile()), libs.linenum()
# , item.tag, item.get('CREATED')))
#/for item in g2:
'''###################
append : child
###################'''
# #ref https://stackoverflow.com/questions/31259847/python-appending-children-to-an-already-created-xml-files-root-using-xml-dom
# data1 = ET.Element("node", {"TEXT": "something_" + libs.get_TimeLabel_Now()})
# # data1 = ET.Element("node", {"TEXT": "something_v001.0002.ma"})
#
# data2 = ET.Element("attribute", {"NAME": "created"
#
# , "VALUE" : "18/01/23"
# })
#
# data1.append(data2)
#
# g2[0].append(data1)
#
'''###################
save xml
###################'''
label = "add-attribute-CREATED"
fpath_Out = fpath
# fpath_Out = "new.%s.%s.mm" % (label, libs.get_TimeLabel_Now())
tree.write(fpath_Out)
print()
print("[%s:%d] xml => written : %s" %
(os.path.basename(libs.thisfile()), libs.linenum(), fpath_Out))
<usage>
'''
if __name__ == "__main__":
'''###################
validate : help option
###################'''
triangle = [(0.2, 0.2), (0.8, 0.2), (0.5, 0.8)] #初期三角形の座標
fig = plt.figure(figsize=(5, 5))
ax = fig.add_subplot(1, 1, 1)
p = pat.Polygon(xy=triangle, fc="white", ec="black")
ax.add_patch(p)
produce_fractal1(triangle, 6)
fname_Out = "./fractal." + libs.get_TimeLabel_Now() + ".png"
fig.savefig(fname_Out) #画像の保存
# fig.savefig("./fractal.png") #画像の保存
'''###################
Report
###################'''
print("[%s:%d] file gen-ed => %s" % (os.path.basename(
os.path.basename(libs.thisfile())), libs.linenum(), fname_Out))
'''###################
validate : help option
###################'''
'''###################
get options
###################'''
'''###################
def main_202105XX():
strOf_FuncName = "main_202105XX()"
'''###################
step : 1
opening, vars
###################'''
#ref https://stackoverflow.com/questions/56711424/how-can-i-count-time-in-python-3
t_start = time.time()
print()
print("[%s:%d] starting : %s (time=%s)" %
(os.path.basename(os.path.basename(libs.thisfile())), libs.linenum(),
strOf_FuncName, libs.get_TimeLabel_Now()))
print()
'''###################
step : 2
data : prep
###################'''
# Building Phase
data = importdata()
print(
"[%s:%d] importdata ==> comp." %
(os.path.basename(os.path.basename(libs.thisfile())), libs.linenum()))
print()
'''###################
step : 2 : 1
data : store
###################'''
X, Y, X_train, X_test, y_train, y_test = splitdataset(data)
#n:20210502_171207
#debug
print(
"[%s:%d] type(X) ==>" %
(os.path.basename(os.path.basename(libs.thisfile())), libs.linenum()))
print(type(X))
print()
#debug:20210503_160446
print(
"[%s:%d] X.shape ==>" %
(os.path.basename(os.path.basename(libs.thisfile())), libs.linenum()))
#ref https://note.nkmk.me/en/python-numpy-ndarray-ndim-shape-size/
print(X.shape)
print()
# (625, 4)
#debug:20210503_160757
print(
"[%s:%d] X[:3] ==>" %
(os.path.basename(os.path.basename(libs.thisfile())), libs.linenum()))
print(X[:3])
print()
# [[1 1 1 1]
# [1 1 1 2]
# [1 1 1 3]]
#code:20210503_162445
clf_gini = train_using_gini(X_train, X_test, y_train)
#debug:20210503_162611
print(
"[%s:%d] clf_gini ==>" %
(os.path.basename(os.path.basename(libs.thisfile())), libs.linenum()))
print(clf_gini)
print()
# DecisionTreeClassifier(class_weight=None,...
#code:20210503_162857
clf_entropy = tarin_using_entropy(X_train, X_test, y_train)
#debug:20210503_163047
print(
"[%s:%d] clf_entropy ==>" %
(os.path.basename(os.path.basename(libs.thisfile())), libs.linenum()))
print(clf_entropy)
print()
'''###################
step : 2 : 2
data : graphviz, png file
###################'''
data = tree.export_graphviz(clf_gini, out_file=None)
# data = tree.export_graphviz(dtree, out_file=None, feature_names=features)
#debug:20210503_164342
print(
"[%s:%d] export_graphviz ==> comp" %
(os.path.basename(os.path.basename(libs.thisfile())), libs.linenum()))
# print(clf_entropy)
print()
#
graph = pydotplus.graph_from_dot_data(data)
strOf_Time_Label = libs.get_TimeLabel_Now()
dpath_PlotImage = "./data/s-18"
# dpath_PlotImage = "./data/s-9"
fname_PlotImage = "decisiontree.%s.png" % (strOf_Time_Label)
# fname_PlotImage = "mydecisiontree.%s.png" % (strOf_Time_Label)
# fname_PlotImage = "plot_image_%s" % (strOf_Time_Label)
fpath_PlotImage = os.path.join(dpath_PlotImage, fname_PlotImage)
graph.write_png(fpath_PlotImage)
#debug:20210503_165123
print("[%s:%d] decisiontree png file ==> comp : %s" % (os.path.basename(
os.path.basename(libs.thisfile())), libs.linenum(), fpath_PlotImage))
print()
'''###################
step : 2 : 2.2
data : graphviz, png file
###################'''
data_entropy = tree.export_graphviz(clf_entropy, out_file=None)
#debug:20210503_165911
print(
"[%s:%d] export_graphviz (clf_entropy) ==> comp" %
(os.path.basename(os.path.basename(libs.thisfile())), libs.linenum()))
# print(clf_entropy)
print()
#
graph = pydotplus.graph_from_dot_data(data_entropy)
strOf_Time_Label = libs.get_TimeLabel_Now()
dpath_PlotImage = "./data/s-18"
# dpath_PlotImage = "./data/s-9"
fname_PlotImage = "decisiontree.%s.[clf_entropy].png" % (strOf_Time_Label)
fpath_PlotImage = os.path.join(dpath_PlotImage, fname_PlotImage)
graph.write_png(fpath_PlotImage)
print("[%s:%d] decisiontree png file ==> comp : %s" % (os.path.basename(
os.path.basename(libs.thisfile())), libs.linenum(), fpath_PlotImage))
print()
'''###################
step : 3 : 1
prediction : gini
###################'''
#n:20210503_170550
# Prediction using gini
y_pred_gini = prediction(X_test, clf_gini)
cal_accuracy(y_test, y_pred_gini)
'''###################
step : 3 : 1
prediction : gini
###################'''
#code:20210505_164310
# Prediction using entropy
y_pred_entropy = prediction(X_test, clf_entropy)
cal_accuracy(y_test, y_pred_entropy)
'''###################
step : 2 : 1
data : store
###################'''
'''###################
step : 6
results
###################'''
'''###################
step : 6 : 1
time
###################'''
t_end = time.time()
#debug
# print ("[%s:%d] time => %s"
#ref https://www.pythonpool.com/python-float-to-string/#5_Using_NumPy
print("[%s:%d] time => %.03f sec" %
(os.path.basename(libs.thisfile()), libs.linenum(),
(t_end - t_start)))
print()
'''###################
def test_1():
'''###################
ops
###################'''
a = np.arange(1, 11)
b = np.arange(1, 11)
pval = stats.pearsonr(a, b)
print(a)
'''###################
write file
###################'''
index_a = -2
fname_Out = "data/pval.a[%d].%s.txt" % \
(
index_a
, libs.get_TimeLabel_Now()
)
# fname_Out = "/data/pval.%s.txt" % (libs.get_TimeLabel_Now())
fout = open(fname_Out, "w")
'''###################
correl : basic
###################'''
msg = "[%s:%d] a=\n" % (os.path.basename(libs.thisfile()), libs.linenum())
fout.write(msg)
# fout.write("a=\n")
fout.write(','.join([str(x) for x in a]))
# fout.write(','.join(a))
fout.write('\n')
fout.write('\n')
msg = "[%s:%d] b=\n" % (os.path.basename(libs.thisfile()), libs.linenum())
fout.write(msg)
# fout.write("b=\n")
fout.write(','.join([str(x) for x in b]))
# fout.write(','.join(b))
fout.write('\n')
fout.write('\n')
correl = stats.pearsonr(a, b)
msg = "[%s:%d] correl=%.4f\n" % \
(os.path.basename(libs.thisfile()), libs.linenum()
, correl[0]
)
fout.write(msg)
fout.write('\n')
fout.write('\n')
'''###################
correl : basic
###################'''
# index_a = -2
test_1_2(fout, a, b)
# test_1_1(fout, a, b, index_a)
# test_1_1(fout, a, b)
'''###################
file : close
###################'''
fout.close()
return None
def test_2():
strOf_FuncName = "test_2"
'''###################
step : 1
opening, vars
###################'''
print()
print ("[%s:%d] starting : %s (time=%s)" % (
os.path.basename(os.path.basename(libs.thisfile()))
, libs.linenum()
, strOf_FuncName
, libs.get_TimeLabel_Now()
)
)
'''###################
step : 2
prep
###################'''
'''###################
step : 2 : 1
prep : data : x
###################'''
#mark:20211030_153553
# numOf_Data_X = 24
numOf_Data_X = 36
valOf_Linspace_Start = - math.pi / 2
valOf_Linspace_End = math.pi / 2
#ref https://matplotlib.org/stable/tutorials/introductory/customizing.html#sphx-glr-tutorials-introductory-customizing-py
data_x = np.linspace(
valOf_Linspace_Start
, valOf_Linspace_End
, numOf_Data_X)
# print()
#
# print ("[%s:%d] data_x =>" % (
# os.path.basename(os.path.basename(libs.thisfile()))
# , libs.linenum()
# )
# )
#
# print(data_x)
'''###################
step : 2 : 2
prep : data : y --> cos(x)
###################'''
#mark:20211030_154118
k = 3
# k = 1
# k = 2
coord_1 = math.pow(-1, k) / (2*k+1)
data_y = [math.cos(x) for x in data_x]
data_y_with_coord = [coord_1 * y for y in data_y]
# y vals --> add
#mark:20211030_155934
data_y_sum = data_y + data_y_with_coord
#mark:20211030_162412
lenOf_data_y = len(data_y)
data_y_sum_2 = [data_y[i] + data_y_with_coord[i] for i in range(lenOf_data_y)]
#debug:20211030_160239
print()
print ("[%s:%d] len(data_y) => %d / len(data_y_with_coord) => %d" % (
os.path.basename(os.path.basename(libs.thisfile()))
, libs.linenum()
, len(data_y)
, len(data_y_with_coord)
)
)
print ("[%s:%d] len(data_y_sum) => %d / len(data_y_sum_2) => %d" % (
os.path.basename(os.path.basename(libs.thisfile()))
, libs.linenum()
, len(data_y_sum)
, len(data_y_sum_2)
)
)
print()
# #debug
# return
# print()
#
# print ("[%s:%d] data_y =>" % (
# os.path.basename(os.path.basename(libs.thisfile()))
# , libs.linenum()
# )
# )
#
# print(data_y)
#
# print()
#
# print ("[%s:%d] data_y_with_coord =>" % (
# os.path.basename(os.path.basename(libs.thisfile()))
# , libs.linenum()
# )
# )
#
# print(data_y_with_coord)
'''###################
step : 3
plot
###################'''
'''###################
step : 3 : 1
plot : prep
###################'''
# folder
strOf_Time_Label = libs.get_TimeLabel_Now()
# dpath_data = "./data"
dpath_data = "data"
dname_PlotImage = "plot_%s" % (strOf_Time_Label)
# dname_PlotImage = "plot_image_%s" % (strOf_Time_Label)
dpath_PlotImage = os.path.join(dpath_data, dname_PlotImage)
# file name
#mark:20211030_163128
fname_Plot = "plot_%s_(k=%d)" % (strOf_Time_Label, k)
# fname_Plot = "plot_%s" % (strOf_Time_Label)
fpath_PlotImage = os.path.join(dpath_PlotImage, fname_Plot)
#ref https://www.askpython.com/python/examples/create-a-directory-in-python
res = os.mkdir(dpath_PlotImage)
print()
print ("[%s:%d] os.mkdir for => : %s" % (
os.path.basename(os.path.basename(libs.thisfile()))
, libs.linenum()
, dpath_PlotImage
)
)
print(res)
'''###################
step : 3 : 2
plot : plot
###################'''
#ref C:\WORKS_2\WS\WS_Others.JVEMV6\JVEMV6\73_ai\1_start\1_1.py
fig = plt.figure()
# title
# plt.title("cos(a), data_y_1_final\n numOf_Data_X = %d\n x [%.02f, %.02f]"
# plt.title("cos(a), data_y_with_coord\n numOf_Data_X = %d\n x [%.02f, %.02f]"
plt.title("cos(a), data_y_with_coord\n numOf_Data_X = %d\n x [%.02f, %.02f] / k = %d"
% (
numOf_Data_X
, valOf_Linspace_Start
, valOf_Linspace_End
, k
)
)
# axis
#ref https://matplotlib.org/stable/tutorials/introductory/pyplot.html#sphx-glr-tutorials-introductory-pyplot-py
plt.axis([- math.pi/2, math.pi/2, -1.5, 1.5])
# plot
#mark:20211030_154535
plt.plot(data_x, data_y,'b-o')
plt.plot(data_x, data_y_with_coord,'r-o')
#mark:20211030_160000
plt.plot(data_x, data_y_sum_2,'y-+')
# plt.plot(data_x, data_y_sum,'y-+')
# grid
#ref https://www.w3schools.com/python/matplotlib_grid.asp
plt.grid()
# save image
res = fig.savefig(fpath_PlotImage)
print()
print ("[%s:%d] result for 'fig.savefig' : %s" % (
os.path.basename(os.path.basename(libs.thisfile()))
, libs.linenum()
, fpath_PlotImage
)
)
print(res)
'''###################
step : 4
###################'''
'''###################
def test_2_2():
'''###################
ops
###################'''
init_Val = 10
a = [10 for x in range(10)]
b = [10 for x in range(10)]
# de-homogenize
#ref mean https://stackoverflow.com/questions/9039961/finding-the-average-of-a-list answered Jan 28 '12 at 3:59
# a[-1] = 5
# b[-1] = 5
val = 5
a[-1] = val
b[-1] = val
# a[-1] = 9
# b[-1] = 9
'''###################
write file
###################'''
# fname_Out = "data/pval.a-%d.%s.txt" % \
label = "test_2_2(val-%d)" % (val)
fname_Out = "data/pval.%s.%s.txt" % \
(
label
, libs.get_TimeLabel_Now()
)
# fname_Out = "/data/pval.%s.txt" % (libs.get_TimeLabel_Now())
fout = open(fname_Out, "w")
'''###################
correl : basic
###################'''
msg = "[%s:%d] a=\n" % (os.path.basename(libs.thisfile()), libs.linenum())
fout.write(msg)
# fout.write("a=\n")
fout.write(','.join([str(x) for x in a]))
# fout.write(','.join(a))
fout.write('\n')
fout.write('\n')
msg = "[%s:%d] b=\n" % (os.path.basename(libs.thisfile()), libs.linenum())
fout.write(msg)
# fout.write("b=\n")
fout.write(','.join([str(x) for x in b]))
# fout.write(','.join(b))
fout.write('\n')
fout.write('\n')
'''###################
correl : basic
###################'''
lo_Final = []
for i in range(10):
# tmp list
lo_Tmp = []
### copy a
#ref copy https://stackoverflow.com/questions/2612802/how-to-clone-or-copy-a-list answered Apr 10 '10 at 8:55
a_ = copy.copy(a)
lo_Tmp.append(i)
lo_Tmp.append(a[0])
a1 = stats.pearsonr(a_, b)
lo_Tmp.append(a1)
### append
lo_Final.append(lo_Tmp)
# decrement
a[0] -= 1
'''###################
write
###################'''
fout.write("index\ta[0]\tcorrel")
fout.write("\n")
for item in lo_Final:
fout.write("%d\t%d\t%.10f" % \
# fout.write("%d\t%.4f\t%.4f\t%.4f" % \
(
item[0], item[1], item[2][0]
)
)
# print("%.4f %.4f %.4f" % (item[1][0], item[2][0], item[3][0]))
fout.write('\n')
'''###################
file : close
###################'''
fout.close()
# msg = "[%s:%d] \na[%d]\tcorrel" % \
# (
# os.path.basename(libs.thisfile()), libs.linenum()
# , index_a
# )
# fout.write(msg)
#
# fout.write('\n')
# fout.write('\n')
return None
def test_1():
strOf_FuncName = "test_1"
'''###################
step : 1
opening, vars
###################'''
print()
print ("[%s:%d] starting : %s (time=%s)" % (
os.path.basename(os.path.basename(libs.thisfile()))
, libs.linenum()
, strOf_FuncName
, libs.get_TimeLabel_Now()
)
)
'''###################
step : 2
prep
###################'''
'''###################
step : 2 : 1
prep : data : x
###################'''
#mark:20211030_153553
# numOf_Data_X = 24
numOf_Data_X = 36
valOf_Linspace_Start = - math.pi / 2
valOf_Linspace_End = math.pi / 2
#ref https://matplotlib.org/stable/tutorials/introductory/customizing.html#sphx-glr-tutorials-introductory-customizing-py
data_x = np.linspace(
valOf_Linspace_Start
, valOf_Linspace_End
, numOf_Data_X)
print()
print ("[%s:%d] data_x =>" % (
os.path.basename(os.path.basename(libs.thisfile()))
, libs.linenum()
)
)
print(data_x)
'''###################
step : 2 : 2
prep : data : y --> cos(x)
###################'''
data_y = [math.cos(x) for x in data_x]
print()
print ("[%s:%d] data_y =>" % (
os.path.basename(os.path.basename(libs.thisfile()))
, libs.linenum()
)
)
print(data_y)
'''###################
step : 3
plot
###################'''
'''###################
step : 3 : 1
plot : prep
###################'''
# folder
strOf_Time_Label = libs.get_TimeLabel_Now()
# dpath_data = "./data"
dpath_data = "data"
dname_PlotImage = "plot_%s" % (strOf_Time_Label)
# dname_PlotImage = "plot_image_%s" % (strOf_Time_Label)
dpath_PlotImage = os.path.join(dpath_data, dname_PlotImage)
# file name
fname_Plot = "plot_%s" % (strOf_Time_Label)
fpath_PlotImage = os.path.join(dpath_PlotImage, fname_Plot)
#ref https://www.askpython.com/python/examples/create-a-directory-in-python
res = os.mkdir(dpath_PlotImage)
print()
print ("[%s:%d] os.mkdir for => : %s" % (
os.path.basename(os.path.basename(libs.thisfile()))
, libs.linenum()
, dpath_PlotImage
)
)
print(res)
'''###################
step : 3 : 2
plot : plot
###################'''
#ref C:\WORKS_2\WS\WS_Others.JVEMV6\JVEMV6\73_ai\1_start\1_1.py
fig = plt.figure()
# title
plt.title("cos(a), data_y_1_final\n numOf_Data_X = %d\n x [%.02f, %.02f]"
% (
numOf_Data_X
, valOf_Linspace_Start
, valOf_Linspace_End
)
)
# axis
#ref https://matplotlib.org/stable/tutorials/introductory/pyplot.html#sphx-glr-tutorials-introductory-pyplot-py
plt.axis([- math.pi/2, math.pi/2, -1.5, 1.5])
# plot
plt.plot(data_x, data_y,'b-o')
# grid
#ref https://www.w3schools.com/python/matplotlib_grid.asp
plt.grid()
# save image
res = fig.savefig(fpath_PlotImage)
print()
print ("[%s:%d] result for 'fig.savefig' : %s" % (
os.path.basename(os.path.basename(libs.thisfile()))
, libs.linenum()
, fpath_PlotImage
)
)
print(res)
'''###################
step : 4
###################'''
'''###################
def test_2_Multiple_Tsp():
strOf_FuncName = "test_2_Multiple_Tsp"
'''###################
step : 1
opening, vars
###################'''
print()
print("[%s:%d] starting : %s (time=%s)" %
(os.path.basename(os.path.basename(libs.thisfile())), libs.linenum(),
strOf_FuncName, libs.get_TimeLabel_Now()))
'''###################
step : 2
prep
###################'''
aryOf_Numbers__Orig = [1, 2, 3, 4, 5]
#ref https://www.geeksforgeeks.org/array-copying-in-python/
aryOf_Numbers__Copy = aryOf_Numbers__Orig.copy()
# aryOf_Numbers__Copy = aryOf_Numbers__Orig
print()
print(
"[%s:%d] aryOf_Numbers__Orig =>" %
(os.path.basename(os.path.basename(libs.thisfile())), libs.linenum()))
print(aryOf_Numbers__Orig)
print()
'''###################
step : 3
transposition
###################'''
#code:20210728_132436
# pointOf_Tsp = 0
pointsOf_Tsp = [3, 1, 4, 1]
# pointsOf_Tsp = [1,3,4,1]
# pointsOf_Tsp = [1,1,3,4]
# pointsOf_Tsp = [1,3,1,4]
# pointOf_Tsp = 3
print(
"[%s:%d] pointsOf_Tsp =>" %
(os.path.basename(os.path.basename(libs.thisfile())), libs.linenum()))
print(pointsOf_Tsp)
print()
cntr = 0
for pointOf_Tsp in pointsOf_Tsp:
'''###################
counter
###################'''
cntr += 1
print("[%s:%d] ----------------- for : %d" % (os.path.basename(
os.path.basename(libs.thisfile())), libs.linenum(), cntr))
print()
print("[%s:%d] calling ... => tsp()" % (os.path.basename(
os.path.basename(libs.thisfile())), libs.linenum()))
print()
#code:20210728_132743
aryOf_Numbers__Copy = tsp(aryOf_Numbers__Copy, pointOf_Tsp)
# aryOf_Numbers = tsp(aryOf_Numbers, pointOf_Tsp)
# tsp(aryOf_Numbers, pointOf_Tsp)
print("[%s:%d] tsp() => complete" % (os.path.basename(
os.path.basename(libs.thisfile())), libs.linenum()))
print("[%s:%d] aryOf_Numbers__Copy is now ... =>" % (os.path.basename(
os.path.basename(libs.thisfile())), libs.linenum()))
print(aryOf_Numbers__Copy)
print()
#/for pointOf_Tsp in pointsOf_Tsp:
print(
"[%s:%d] aryOf_Numbers : compare =>" %
(os.path.basename(os.path.basename(libs.thisfile())), libs.linenum()))
print("orig / tsp / pointsOf_Tsp")
print(aryOf_Numbers__Orig)
print(aryOf_Numbers__Copy)
print(pointsOf_Tsp)
