try:
from AutoFeedback.plotchecks import check_plot
except:
import subprocess
import sys
subprocess.check_call([sys.executable, "-m", "pip", "install", "AutoFeedback"])
from AutoFeedback.plotchecks import check_plot
from AutoFeedback.plotclass import line
from AutoFeedback.randomclass import randomvar
import unittest
from main import *
x = np.linspace(2,201,200)
var = randomvar( 0.5, variance=1/12, dist="chi2", isinteger=False, meanconv=True )
line1=line( x, var )
axislabels=["Number of random variables", "Sample variance"]
class UnitTests(unittest.TestCase) :
def test_variables(self) :
assert(check_plot([line1],explabels=axislabels,explegend=False,output=True))
try:
import AutoFeedback.plotchecks as pc
from AutoFeedback.plotclass import line
except:
import subprocess
import sys
subprocess.check_call(
[sys.executable, "-m", "pip", "install", "AutoFeedback"])
import AutoFeedback.plotchecks as pc
from AutoFeedback.plotclass import line
import unittest
from main import *
xvals = np.linspace(0, 29, 30)
yvals = xvals * xvals
line1 = line(xvals, yvals)
axislabels = ["Index", "Square"]
class UnitTests(unittest.TestCase):
def test_fib(self):
assert (pc.check_plot([line1],
explabels=axislabels,
explegend=False,
output=True))
class tmod:
plt.plot([0, 1, 2], [0, 1, 4], 'r-', label='quadratic')
plt.plot([0.5, 1.5], [1.5, 2.5], 'bD', label='linear')
plt.legend()
plt.axis([-1, 1, -2, 2])
plt.xlabel('x')
plt.ylabel('y')
plt.title('z')
fighand = plt.gca()
line_data,axes_data,labels,legend_data = \
pc.extract_plot_elements(fighand,lines=True,axislabels=True,axes=True,legend=True)
l1, l2 = line_data[0], line_data[1]
line1=line([0,1,2],[0,1,4],linestyle=['-','solid'],\
colour=['r','red',(1.0,0.0,0.0,1)],\
label='quadratic')
line2=line([0.5,1.5],[1.5,2.5],marker=['D','d'],\
colour=['b','blue',(0.0,0.0,1.0,1)],\
label='linear')
axislabels = ["x", "y", "z"]
axeslimits = [-1, 1, -2, 2]
class ExtractTests(unittest.TestCase):
def test_legend_extract(self):
assert (tmod.legend_data == ['quadratic', 'linear'])
def test_axes_extract(self):
import subprocess
import sys
subprocess.check_call(
[sys.executable, "-m", "pip", "install", "AutoFeedback"])
from AutoFeedback.plotchecks import check_plot
from AutoFeedback.plotclass import line
from AutoFeedback.randomclass import randomvar
import unittest
from main import *
x, expect, variance, isi = np.linspace(1, 50,
50), np.zeros(50), np.zeros(50), []
for i in range(50):
expect[i], variance[i] = 0.5, 1 / 12 / (i + 1)
isi.append(False)
y = randomvar(expect, variance=variance, dist="chi2", dof=9, isinteger=isi)
line1 = line(x, y)
axislabels = ["Number of variables used to calculate mean", "Variance"]
class UnitTests(unittest.TestCase):
def test_variables(self):
assert (check_plot([line1],
explabels=axislabels,
explegend=False,
output=True))
try:
from AutoFeedback.plotchecks import check_plot
except:
import subprocess
import sys
subprocess.check_call(
[sys.executable, "-m", "pip", "install", "AutoFeedback"])
from AutoFeedback.plotchecks import check_plot
from AutoFeedback.plotclass import line
import unittest
from main import *
myx = np.loadtxt("data.dat")
myx.sort()
myy = range(1, len(myx) + 1)
myy = [a / len(myx) for a in myy]
line1 = line(myx, myy)
axislabels = ["x", "cumulative distribution"]
class UnitTests(unittest.TestCase):
def test_plot(self):
assert (check_plot([line1],
explabels=axislabels,
explegend=False,
output=True))