def lab_4_get_graphics(student_data, source_data):
graphics = []
N0 = len(student_data["student_signal"])
d = student_data["student_signal"] # сигнал, вводимый студентом
b = np.array([float(student_data["student_b"])])
a = student_data["student_filter"] # фильтр, вводимый студентом
fig, ax = plt.subplots(figsize=(6, 6))
z = signal.lfilter(b, a, d)
ax.plot(np.arange(N0), z, 'y', linewidth=2.0)
ax.plot(np.arange(N0), np.ones((N0, 1)) * (0.05 * max(z)), 'r')
ax.plot(np.arange(N0), np.ones((N0, 1)) * (-0.05 * max(z)), 'r')
html = mpld3.fig_to_d3(fig)
graphics.append(
{
"id": "graphic_1",
"html": html
}
)
fig, ax = plt.subplots(figsize=(6, 6))
fz = np.abs(np.fft.fft(z))
plt.plot(np.arange(N0), fz, 'y', linewidth=2.0)
plt.plot(np.arange(N0), np.ones((N0, 1)) * (0.707 * max(fz)), 'r')
html = mpld3.fig_to_d3(fig)
graphics.append(
{
"id": "graphic_2",
"html": html
}
)
return graphics
def lab_1_get_graphics(student_data, source_data):
graphics = []
N0 = len(student_data["student_signal"])
d = student_data["student_signal"] # сигнал, вводимый студентом
b = student_data["student_filter"] # фильтр, вводимый студентом
a = float(student_data["student_a"])
if source_data["filter_type"]["window"]["name"] == "hamming":
w = np.hamming(len(b))
z = signal.lfilter(b * w, 1, d)
fz = np.abs(np.fft.fft(z))
elif source_data["filter_type"]["window"]["name"] == "blackman":
w = np.blackman(len(b))
z = signal.lfilter(b * w, a, d) # тут написать алгоритм для Блэкмана
fz = np.abs(np.fft.fft(z))
else: # прямоугольное окно
z = signal.lfilter(b, a, d)
fz = np.abs(np.fft.fft(z))
fig, ax = plt.subplots(figsize=(6, 6))
ax.stem(np.arange(N0), z, 'c')
ax.plot(np.arange(N0), z, 'y', linewidth=3.0)
ax.plot(np.arange(N0), np.ones((N0, 1)) * (0.707 * max(z)), 'r', linewidth=3.0)
# w = np.hamming(Ns)
# z = signal.lfilter(b*w, a, d)
# ax.stem(np.arange(N0), z)
# ax.plot(np.arange(N0), np.ones((N0, 1)) * (0.707 * max(z)), 'r')
html = mpld3.fig_to_d3(fig)
graphics.append(
{
"id": "graphic_1",
"html": html
}
)
fig, ax = plt.subplots(figsize=(6, 6))
# if source_data["filter_type"]["window"]["name"] == "hamming":
# ax.semilogy(fz)
# else:
ax.plot(np.arange(N0), fz, 'c', linewidth=3.0)
ax.plot(np.arange(N0), np.ones((N0, 1)) * (0.707 * max(fz)), 'r', linewidth=3.0)
html = mpld3.fig_to_d3(fig)
graphics.append(
{
"id": "graphic_2",
"html": html
}
)
return graphics
def lab_5_get_graphic_1(student_data, source_data):
graphics = []
s = student_data["student_s"]
s1 = student_data["student_s1"]
fig, ax = plt.subplots(figsize=(6, 6))
ax.stem(abs(np.fft.fft(s)))
html = mpld3.fig_to_d3(fig)
graphics.append({"id": "graphic_1", "html": html})
fig, ax = plt.subplots(figsize=(6, 6))
ax.stem(abs(np.fft.fft(s1)))
html = mpld3.fig_to_d3(fig)
graphics.append({"id": "graphic_2", "html": html})
return graphics
def lab_7_get_graphic_2(student_data):
student_sm = student_data["student_Sm"]
fig, ax = plt.subplots(figsize=(6, 6))
ax.plot(student_sm, linewidth=2.0)
html = mpld3.fig_to_d3(fig)
graphic = {"id": "graphic_2", "html": html}
return graphic
def combine_testplots(wildcard='test_plots/*.py',
outfile='test_plots.html',
d3_url=None):
"""Generate figures from the plots and save to an HTML file
Parameters
----------
wildcard : string
a regex matching files
outfile : string
the output HTML file for saving the results
d3_url : string
the URL of the d3 library to use. If not specified, a standard web
address will be used.
"""
fig_html = []
for filename in glob.glob('test_plots/*.py'):
dirname, fname = os.path.split(filename)
modulename = os.path.splitext(fname)[0]
if dirname not in sys.path:
sys.path.append(dirname)
f = __import__(modulename)
if hasattr(f, 'main'):
print "running {0}".format(filename)
fig = f.main()
fig_html.append(fig_to_d3(fig, d3_url))
print "writing results to {0}".format(outfile)
template = '<html>\n{content}\n</html>'
with open(outfile, 'w') as f:
f.write('<html>\n\n')
for fig in fig_html:
f.write(fig)
f.write('\n\n</html>')
def lab_2_get_graphics_2(source_data, correct_answer):
graphics = []
K = float(correct_answer["K_2"])
N3 = int(source_data["N3"])
fig, ax = plt.subplots(figsize=(6, 6))
d3 = [np.exp(2j * math.pi * K * x / N3) for x in np.arange(N3)]
ax.plot(np.arange(N3), np.real(d3), 'y', linewidth=2.0)
html = mpld3.fig_to_d3(fig)
graphics.append({"id": "graphic_3", "html": html})
fig, ax = plt.subplots(figsize=(6, 6))
sp = np.abs(np.fft.fft(d3))
ax.stem(np.arange(N3), sp, 'c')
html = mpld3.fig_to_d3(fig)
graphics.append({"id": "graphic_4", "html": html})
return graphics
def lab_7_get_graphic_3(source_data, correct_answer):
graphics = []
N1 = int(correct_answer["N1"])
S1p = correct_answer["S1p"]
SD = correct_answer["SD"]
fig, ax = plt.subplots(figsize=(6, 6))
ax.plot(np.arange(0, N1 * 8), S1p[0:np.int(N1 * 8)])
html = mpld3.fig_to_d3(fig)
graphics.append({"id": "graphic_3_1", "html": html})
fig, ax = plt.subplots(figsize=(6, 6))
ax.plot(np.arange(0, N1 * 8), SD[0:np.int(N1 * 8)])
html = mpld3.fig_to_d3(fig)
graphics.append({"id": "graphic_3_2", "html": html})
return graphics
def lab_2_get_graphics_1(source_data, correct_answer):
graphics = []
K = int(correct_answer["K_1"])
N3 = int(source_data["N3"])
fig, ax = plt.subplots(figsize=(6, 6))
# d3 = [math.cos((math.pi * x) / 2) for x in np.arange(N3)]
d3 = [math.cos((math.pi * x) / (K / 2)) for x in np.arange(N3)]
ax.plot(np.arange(N3), d3, 'y', linewidth=2.0)
html = mpld3.fig_to_d3(fig)
graphics.append({"id": "graphic_1", "html": html})
fig, ax = plt.subplots(figsize=(6, 6))
sp = np.abs(np.fft.fft(d3))
ax.stem(np.arange(N3), sp, 'c')
html = mpld3.fig_to_d3(fig)
graphics.append({"id": "graphic_2", "html": html})
return graphics
def lab_7_get_graphic_1(source_data, correct_answer):
graphics = []
N0 = source_data["N0"]
f0 = correct_answer["f0"]
fm = correct_answer["fm"]
m = correct_answer["m"]
d1 = (1 + m * np.cos(2 * math.pi * fm * np.arange(0, N0) / N0)) * (np.cos(
2 * math.pi * f0 * np.arange(0, N0) / N0))
fig, ax = plt.subplots(figsize=(6, 6))
ax.plot(np.arange(N0), d1)
html = mpld3.fig_to_d3(fig)
graphics.append({"id": "graphic_1_1", "html": html})
fig, ax = plt.subplots(figsize=(6, 6))
ax.stem(np.arange(N0), np.abs(np.fft.fft(d1)), 'c')
html = mpld3.fig_to_d3(fig)
graphics.append({"id": "graphic_1_2", "html": html})
return graphics
def convert_to_html_and_open(fig):
from mpld3 import fig_to_d3
html = fig_to_d3(fig)
file=open('index.html','w')
file.write('<style>body{background-color:#111111;color:#333333;font-size:10pt;font-family:sans-serif}')
file.write('a{color:#444444;text-decoration:none;}</style>')
file.write(html)
file.write("How Far Can You See? <a href=https://github.com/rkeisler/nakedeye target='_blank'>made in python/d3</a> by <a href=https://twitter.com/RyanKeisler target='_blank'>@RyanKeisler</a> using <a href=https://twitter.com/jakevdp target='_blank'>@jakevdp's</a> awesome <a href=https://github.com/jakevdp/mpld3 target='_blank'>mpld3</a> library. work in progress. <br> if you don't see a map of stars, try refreshing.")
file.close()
# I'm not sure why, but this makes it run much faster and more smoothly.
system("perl -pi -e 's/stroke-dasharray: 10,0/stroke-dasharray: 0,0/g' index.html")
system('open index.html')
def lab_5_get_graphic_2(student_data, source_data):
graphics = []
sl = np.array(student_data["student_sl"])
slc = np.array(student_data["student_slc"])
fig, ax = plt.subplots(figsize=(6, 6))
ax.plot(sl)
html = mpld3.fig_to_d3(fig)
graphics.append({"id": "graphic_3", "html": html})
fig, ax = plt.subplots(figsize=(6, 6))
ax.plot(slc)
html = mpld3.fig_to_d3(fig)
graphics.append({"id": "graphic_4", "html": html})
fig, ax = plt.subplots(figsize=(6, 6))
ax.plot(np.fft.fft(sl))
html = mpld3.fig_to_d3(fig)
graphics.append({"id": "graphic_5", "html": html})
fig, ax = plt.subplots(figsize=(6, 6))
ax.plot(np.fft.fft(slc))
html = mpld3.fig_to_d3(fig)
graphics.append({"id": "graphic_6", "html": html})
return graphics
def exec_file(self):
print("running {0}".format(self.filename))
with disable_mpld3():
import matplotlib.pyplot as plt
plt.close('all')
my_globals = {'pl': plt,
'plt': plt}
execfile(self.filename, my_globals)
fig = plt.gcf()
self.html = mpld3.fig_to_d3(fig)
thumbfile = os.path.join(self.target_dir,
self.pngfilename)
fig.savefig(thumbfile)
create_thumbnail(thumbfile, thumbfile)
def lab_2_get_graphics_3(source_data, correct_answer):
graphics = []
f = np.array(correct_answer["f"])
Nk0 = len(f)
N3 = int(source_data["N3"])
fig, ax = plt.subplots(figsize=(6, 6))
d9 = np.zeros(N3)
for i in np.arange(1, Nk0 + 1):
d9 = np.array(d9) + np.array(
[math.cos(2 * math.pi * f[i - 1] * x / N3) for x in np.arange(N3)])
ax.plot(np.arange(N3), d9, 'y', linewidth=2.0)
html = mpld3.fig_to_d3(fig)
graphics.append({"id": "graphic_5", "html": html})
fig, ax = plt.subplots(figsize=(6, 6))
sp = np.abs(np.fft.fft(d9))
ax.stem(np.arange(N3), sp, 'c')
html = mpld3.fig_to_d3(fig)
graphics.append({"id": "graphic_6", "html": html})
return graphics
def lab_3_get_graphic_1(student_data, source_data, correct_answer):
b = student_data["student_filter"]
N0 = len(b)
y = np.append(student_data["student_signal"], np.zeros(N0 * 2))
S = int(correct_answer["S"])
y1_et = np.roll(y, (1) * S)
ys1_et = y1_et + 0.5 * np.random.randn(1, 3 * N0)[0]
z = signal.lfilter(b, 1, ys1_et)
fig, ax = plt.subplots(figsize=(6, 6))
ax.plot(ys1_et, linewidth=2.0)
ax.plot(z, linewidth=2.0)
html = mpld3.fig_to_d3(fig)
graphic = {"id": "graphic_1", "html": html}
return graphic
def combine_testplots(wildcard='test_plots/*.py',
outfile='test_plots.html',
d3_url=None):
"""Generate figures from the plots and save to an HTML file
Parameters
----------
wildcard : string
a regex matching files
outfile : string
the output HTML file for saving the results
d3_url : string
the URL of the d3 library to use. If not specified, a standard web
address will be used.
"""
if isinstance(wildcard, basestring):
filenames = glob.glob(wildcard)
else:
filenames = sum([glob.glob(w) for w in wildcard], [])
fig_html = []
fig_names = []
for filename in filenames:
dirname, fname = os.path.split(filename)
modulename = os.path.splitext(fname)[0]
if dirname not in sys.path:
sys.path.append(dirname)
f = __import__(modulename)
if hasattr(f, 'main'):
print "running {0}".format(filename)
fig = f.main()
fig_html.append(fig_to_d3(fig, d3_url))
fig_png = os.path.splitext(filename)[0] + '.png'
fig.savefig(fig_png)
fig_names.append("\n<div class='fig'><img src={0}>"
"</div>\n".format(fig_png))
print "writing results to {0}".format(outfile)
with open(outfile, 'w') as f:
f.write(TEMPLATE.format(left_col="".join(fig_html),
right_col="".join(fig_names)))
def lab_3_get_graphic_3(student_data, source_data):
v = student_data["student_s"]
for idx, v_value in enumerate(v):
try:
v[idx] = float(v_value)
except:
v[idx] = 0
s = np.array(source_data["s"])
fig, ax = plt.subplots(figsize=(6, 6))
# (markers, stemlines, baseline) =
ax.stem(s, v, 'y')
# ax.setp(markers, marker='D', markersize=10, markeredgecolor="orange", markeredgewidth=2)
html = mpld3.fig_to_d3(fig)
graphic = {
"id": "graphic_3",
"html": html,
}
return graphic
def plot_data(list_of_dicts, list_of_prices, list_of_scores):
fig, ax = plt.subplots(subplot_kw=dict(axisbg='#f7f8f9'))
N = len(list_of_prices)
scatter = ax.scatter([i['score'] for i in list_of_dicts],
[i['price'] for i in list_of_dicts],
c=np.random.random(size=N),
alpha=0.7,
cmap=plt.cm.brg)
ax.grid(color='white', linestyle='solid')
ax.set_title("Lidl Wine vs. Score", size=30)
ax.set_xlabel('Score', fontsize=20)
ax.set_ylabel('Price (£)', fontsize=20)
ax.set_xlim([81.5, 90])
labels = ['{0}'.format(i['name']) for i in list_of_dicts]
tooltip = mpld3.plugins.PointLabelTooltip(scatter, labels=labels)
mpld3.plugins.connect(fig, tooltip)
html_string = mpld3.fig_to_d3(fig, template_type="simple")
Html_file = open("results.html", "w")
Html_file.write(html_string)
Html_file.close()
mpld3.show()
def lab_7_get_graphic_4(student_data, correct_answer):
graphics = []
b_st = np.array(student_data["student_b"])
a_st = np.array(student_data["student_a"])
SD = np.array(correct_answer["SD"])
N1 = int(correct_answer["N1"])
z = signal.lfilter(b_st, a_st, SD)
fig, ax = plt.subplots(figsize=(6, 6))
ax.plot(np.arange(0, np.int(N1 * 8)), z[0:np.int(N1 * 8)])
ax.stem(np.arange(N1 / 2, N1 * 8, N1),
np.take(z, np.arange(np.int(N1 / 2), np.int(N1 * 8), np.int(N1))),
'r',
linewidth=3.0)
html = mpld3.fig_to_d3(fig)
graphics.append({
"id": "graphic_4_1",
"html": html,
})
return graphics
def descriptive_multi_cores(data):
fig, ax = plt.subplots()
lines=tools.file_lines(data[3])
ncol=tools.file_col(data[3])-1
outputs_files=data[1]+data[2]
if lines==1:
file = open(outputs_files, "w")
writer=csv.writer(file, lineterminator=',')
b=[[0 for x in xrange(6)] for x in xrange(ncol-2)]
normality=[0 for x in xrange(1)]
file.write("Variables,Class,N,Mean,Std_Dev,Variance,Max,Min,Coeff_Var,Interquartile,Normality_distrib,Confident_intervals_left,Confident_intervals_right\n")
for col in xrange(ncol-2):
a = tools.read_float_tab(data[3],col+2,1)
b[col][0]=1
b[col][1]=float(a)
b[col][2]=0
b[col][3]=0
b[col][4]=float(a)
b[col][5]=float(a)
file.write("%s,"%data[4][col+2])
file.write("%s,"%(os.path.splitext(data[2])[0]))
file.write("%f,"%b[col][0])
file.write("%f,"%b[col][1])
file.write("%f,"%b[col][2])
file.write("%f,"%b[col][3])
file.write("%f,"%b[col][4])
file.write("%f,"%b[col][5])
file.write("100,")
file.write("0,")
file.write("0,")
file.write("0,")
file.write("0,\n")
file.close()
else:
file = open(outputs_files, "w")
writer=csv.writer(file, lineterminator=',')
b=[[0 for x in xrange(11)] for x in xrange(ncol-2)]
file.write("Variables,Class,N,Mean,Std_Dev,Variance,Max,Min,Coeff_Var,Interquartile,Normality_distrib,Confident_intervals_left,Confident_intervals_right\n")
a=[0 for x in xrange(lines)]
for col in xrange(ncol-2):
for j in xrange(lines):
a[j]=tools.read_float_tab(data[3],col+2,j)
b[col][0]=float(len(a))
b[col][1]=float(np.mean(a))
b[col][2]=float(np.std(a, dtype=float))
b[col][3]=float(np.var(a, dtype=float))
b[col][4]=float(max(a))
b[col][5]=float(min(a))
if np.around(b[col][2],decimals=12) != 0.0:
if float(len(a)) < 3:
b[col][6]=float(abs((np.std(a)/np.mean(a))*100))
file.write("%s,"%data[4][col+2])
file.write("%s,"%(os.path.splitext(data[2])[0]))
file.write("%f,"%b[col][0])
file.write("%f,"%b[col][1])
file.write("%f,"%b[col][2])
file.write("%f,"%b[col][3])
file.write("%f,"%b[col][4])
file.write("%f,"%b[col][5])
file.write("%f,"%b[col][6])
file.write("0,")
file.write("0,")
file.write("0,")
file.write("0,\n")
else:
b[col][6]=float(abs((np.std(a)/np.mean(a))*100))
X=sort(a)
upperQuartile = stats.scoreatpercentile(X,.75)
lowerQuartile = stats.scoreatpercentile(X,.25)
IQR = upperQuartile - lowerQuartile
b[col][7]=float(IQR)
normality=stats.shapiro(a)
b[col][8]=float(normality[1])
b[col][9]=np.mean(a)-1.96*(np.std(a)/math.sqrt(len(a)))
b[col][10]=np.mean(a)+1.96*(np.std(a)/math.sqrt(len(a)))
file.write("%s,"%data[4][col+2])
file.write("%s,"%(os.path.splitext(data[2])[0]))
file.write("%f,"%b[col][0])
file.write("%f,"%b[col][1])
file.write("%f,"%b[col][2])
file.write("%f,"%b[col][3])
file.write("%f,"%b[col][4])
file.write("%f,"%b[col][5])
file.write("%f,"%b[col][6])
file.write("%f,"%b[col][7])
file.write("%f,"%b[col][8])
file.write("%f,"%b[col][9])
file.write("%f,\n"%b[col][10])
if normality[1] >= 0.05:
norm_distrib = np.linspace(-150,150,100)
ax.set_title('Normality of %s class features'%os.path.splitext(data[2])[0])
ax.plot(norm_distrib,mlab.normpdf(norm_distrib,np.mean(a),math.sqrt(np.var(a))),label=data[4][col+2],ms=10, alpha=0.3)
ax.legend(loc=2, ncol=1, bbox_to_anchor=(0, 0, 1, 0.7),fancybox=True,shadow=False,fontsize=5)
ax.grid(color='lightgray', alpha=0.5)
ax.patch.set_facecolor('white')
else:
b[col][6]=0
X=sort(a)
upperQuartile = stats.scoreatpercentile(X,.75)
lowerQuartile = stats.scoreatpercentile(X,.25)
IQR = upperQuartile - lowerQuartile
b[col][7]=float(IQR)
b[col][8]=0
b[col][9]=np.mean(a)-1.96*(np.std(a)/math.sqrt(len(a)))
b[col][10]=np.mean(a)+1.96*(np.std(a)/math.sqrt(len(a)))
file.write("%s,"%data[4][col+2])
file.write("%s,"%(os.path.splitext(data[2])[0]))
file.write("%f,"%b[col][0])
file.write("%f,"%b[col][1])
file.write("%f,"%b[col][2])
file.write("%f,"%b[col][3])
file.write("%f,"%b[col][4])
file.write("%f,"%b[col][5])
file.write("%f,"%b[col][6])
file.write("%f,"%b[col][7])
file.write("%f,"%b[col][8])
file.write("%f,"%b[col][9])
file.write("%f,\n"%b[col][10])
file.close()
display_d3(fig)
html = mpld3.fig_to_d3(fig)
html_normality=data[1]+data[2]+".html"
normality_display = open(html_normality, "w")
normality_display.write("%s"%html)
normality_display.close()
plt.close()
"""Plot to test line styles"""
import matplotlib.pyplot as plt
import numpy as np
from mpld3 import plugins, fig_to_d3
def main():
fig, ax = plt.subplots()
colors = plt.rcParams['axes.color_cycle']
points = []
for i, color in enumerate(colors):
points = ax.plot(i, 0, 'o', c=color)
plugins.connect(fig,
plugins.PointLabelTooltip(points[0], [color]))
ax.set_xlim(-1, len(colors) + 1)
return fig
if __name__ == '__main__':
fig = main()
fig_to_d3(fig)
# Download d3 file locally
d3_filename = 'd3.v3.min.js'
if not os.path.exists(d3_filename):
page = urllib2.urlopen('http://d3js.org/d3.v3.min.js')
with open(d3_filename, 'w') as f:
f.write(page.read())
# create a plot
fig, ax = plt.subplots(subplot_kw={'axisbg':'#EEEEEE'}, facecolor='white')
ax.plot(np.random.random(10),
np.random.random(10),
'ob', markeredgecolor='lightblue',
markersize=20, markeredgewidth=10, alpha=0.5)
ax.plot(np.linspace(0.1, 0.9, 10),
np.random.random(10), '-c', lw=5, alpha=0.5)
ax.set_xlabel('x label')
ax.set_ylabel('y label')
ax.set_title('title', fontsize=20)
ax.text(0.2, 0.85, "left", fontsize=18, ha='left')
ax.text(0.2, 0.75, "center", fontsize=18, ha='center')
ax.text(0.2, 0.65, "right", fontsize=18, ha='right')
ax.grid(True, color='white', linestyle='solid')
filename = "example.html"
print "Writing output to {0}".format(filename)
open(filename, 'w').write(fig_to_d3(fig, d3_filename))
#plt.show()
def lab_3_get_graphic_2(correct_answer,
student_data,
source_data,
reload="True",
is_signal=""):
Ku_i_max = int(source_data["Ku"])
Ku_j_max = int(source_data["Ku"])
b = np.array(student_data["answer"]["student_filter"])
N0 = len(b)
y = np.append(np.array(student_data["answer"]["student_signal"]),
np.zeros(N0 * 2))
s_st = np.array(source_data["s"])
Ku_j = int(student_data["state"]["Ku_j"])
Ku_i = int(student_data["state"]["Ku_i"])
K = 13 # сделать не так
there_is_signal_count = int(student_data["state"]["there_is_signal_count"])
there_is_no_signal_count = int(
student_data["state"]["there_is_no_signal_count"])
if student_data["state"]["y2_s2"] is None:
student_data["state"]["y2_s2"], correct_answer["s"] = get_y2_s2(
Ku_j_max, Ku_i_max, N0, s_st, b, K, y)
if is_signal == "there_is_signal":
there_is_signal_count += 1
elif is_signal == "there_is_no_signal":
there_is_no_signal_count += 1
else:
pass
if not student_data["state"]["Ku_done"]:
student_data["state"]["there_is_signal_states"][Ku_j - 1] = {
"there_is_signal_count": there_is_signal_count,
"there_is_no_signal_count": there_is_no_signal_count
}
y2 = student_data["state"]["y2_s2"]["y2"][Ku_j - 1][Ku_i - 1]
s2 = student_data["state"]["y2_s2"]["s2"][Ku_j - 1][Ku_i - 1]
if not reload:
if Ku_i == Ku_i_max:
if Ku_j == Ku_j_max:
student_data["state"]["Ku_done"] = True
else:
Ku_j += 1
Ku_i = 1
there_is_signal_count = 0
there_is_no_signal_count = 0
else:
Ku_i += 1
student_data["state"]["Ku_j"] = Ku_j
student_data["state"]["Ku_i"] = Ku_i
student_data["state"]["there_is_signal_count"] = there_is_signal_count
student_data["state"][
"there_is_no_signal_count"] = there_is_no_signal_count
fig, ax = plt.subplots(figsize=(6, 6))
ax.plot(y2, linewidth=2.0)
ax.plot(s2, linewidth=2.0)
# ax.plot(np.arange(len(y)), np.full((len(y), 1), 0.707 * max(s2)), 'r')
ax.plot(np.arange(len(y)), np.ones((len(y), 1)) * (0.707 * 130), 'r')
ax.plot(np.arange(len(y)),
np.ones((len(y), 1)) * (2 * math.sqrt(130)), 'b')
html = mpld3.fig_to_d3(fig)
graphic = {"id": "graphic_2", "html": html}
return correct_answer, student_data, graphic
# itrace plots
itrace = pd.read_csv(TRACEDIR + "/itrace.csv", index_col=False,
names=["pid", "queue", "numContexts", "uop", "numUops", "cycleCount"])
# print itrace.head()
num_pid = len(itrace["pid"].get_values())
unique_pids = set(itrace["pid"].get_values())
num_unique_pid = len(unique_pids)
# print unique_pids
fig, ax = plt.subplots(figsize=(10, 6))
# plt.scatter(itrace["cycleCount"], itrace["pid"], c=cm.hot(np.abs(y)), edgecolor='none')
plt.scatter(itrace["cycleCount"], itrace["pid"], c=itrace["pid"])
ax.set_title("PID vs. Time")
ax.set_xlabel("Time (cycles)", labelpad=10)
ax.set_ylabel("PID", labelpad=10)
plt.yticks(list(unique_pids))
plt.gca().get_yaxis().get_major_formatter().set_useOffset(False)
plt.tight_layout()
plt.savefig(PLOTDIR + "/vcore_exec2.png")
# print mpld3.fig_to_d3(fig)
# instructions executed by vcore
fig, ax = plt.subplots(figsize=(10, 6))
sns.countplot(y="queue", hue="pid", data=itrace)
ax.set_title("Virtual Core Thread Execution")
ax.set_xlabel("Microinstructions Executed", labelpad=10)
ax.set_ylabel("Virtual Core", labelpad=10)
plt.savefig(PLOTDIR + "/vcore_exec.png")
print mpld3.fig_to_d3(fig)
def main():
fig, ax = plt.subplots()
N = 50
df = pd.DataFrame(index=range(N))
df['x'] = np.random.randn(N)
df['y'] = np.random.randn(N)
df['z'] = np.random.randn(N)
labels = []
for i in range(N):
label = df.ix[[i], :].T
label.columns = ['Row {0}'.format(i)]
labels.append(str(label.to_html())) # .to_html() is unicode, so make leading 'u' go away with str()
points = ax.plot(df.x, df.y, 'o', color='k', mec='w', ms=15, mew=1, alpha=.9)
ax.set_xlabel('x')
ax.set_ylabel('y')
tooltip = plugins.PointHTMLTooltip(
points[0], labels, voffset=10, hoffset=10, css=css)
plugins.connect(fig, tooltip)
return fig
if __name__ == '__main__':
fig = main()
print fig_to_d3(fig)
import numpy as np
import matplotlib.pyplot as plt
from mpld3 import fig_to_d3
fig, ax = plt.subplots()
ax.plot(np.random.random(10),
np.random.random(10),
'og')
ax.plot(np.linspace(0.1, 0.9, 10),
np.random.random(10), '-b', lw=5, alpha=0.2)
ax.set_xlabel('x label')
ax.set_ylabel('y label')
ax.set_title('title', fontsize=20)
ax.grid(True, color='lightgray', alpha=0.7)
filename = "example.html"
print "Writing output to {0}".format(filename)
open(filename, 'w').write(fig_to_d3(fig))
import numpy as np
import matplotlib.pyplot as plt
from mpld3 import fig_to_d3
fig, ax = plt.subplots(subplot_kw={'axisbg':'#EEEEEE'}, facecolor='white')
ax.plot(np.random.random(10),
np.random.random(10),
'ob', markeredgecolor='lightblue',
markersize=20, markeredgewidth=10, alpha=0.5)
ax.plot(np.linspace(0.1, 0.9, 10),
np.random.random(10), '-c', lw=5, alpha=0.5)
ax.set_xlabel('x label')
ax.set_ylabel('y label')
ax.set_title('title', fontsize=20)
ax.text(0.2, 0.85, "left", fontsize=18, ha='left')
ax.text(0.2, 0.75, "center", fontsize=18, ha='center')
ax.text(0.2, 0.65, "right", fontsize=18, ha='right')
ax.grid(True, color='white', linestyle='solid')
filename = "example.html"
print "Writing output to {0}".format(filename)
open(filename, 'w').write(fig_to_d3(fig, d3_location='d3.v3.min.js'))
plt.show()
