def load_style(directory='.', name='kf_book/custom.css'):
version = [
int(version_no) for version_no in matplotlib.__version__.split('.')
]
try:
if sys.version_info[0] >= 3:
style = json.load(open(os.path.join(directory,
"kf_book/538.json")))
else:
style = json.load(open(directory + "/kf_book/538.json"),
object_hook=_decode_dict)
plt.rcParams.update(style)
except:
pass
set_figsize()
reset_axis()
np.set_printoptions(suppress=True,
precision=3,
threshold=10000.,
linewidth=70,
formatter={'float': lambda x: ' {:.3}'.format(x)})
styles = open(os.path.join(directory, name), 'r').read()
set_figsize()
# I don't know why I have to do this, but I have to call
# with suppress a second time or the notebook doesn't suppress
# exponents
np.set_printoptions(suppress=True)
return HTML(styles)
def load_style(directory='.', name='kf_book/custom.css'):
version = [
int(version_no) for version_no in matplotlib.__version__.split('.')
]
try:
if sys.version_info[0] >= 3:
style = json.load(open(os.path.join(directory,
"kf_book/538.json")))
else:
style = json.load(open(directory + "/kf_book/538.json"),
object_hook=_decode_dict)
# matplotlib has deprecated the use of axes.color_cycle as of version
if version[0] > 1 or (version[0] == 1 and version[1] >= 5):
style[
"axes.prop_cycle"] = "cycler('color', ['#6d904f','#013afe', '#202020','#fc4f30','#e5ae38','#A60628','#30a2da','#008080','#7A68A6','#CF4457','#188487','#E24A33'])"
style.pop("axes.color_cycle", None)
plt.rcParams.update(style)
except:
pass
set_figsize()
reset_axis()
np.set_printoptions(suppress=True,
precision=3,
linewidth=70,
formatter={'float': lambda x: ' {:.3}'.format(x)})
styles = open(os.path.join(directory, name), 'r').read()
set_figsize()
return HTML(styles)
def load_style(directory='.', name='kf_book/custom.css'):
version = [
int(version_no) for version_no in matplotlib.__version__.split('.')
]
try:
if sys.version_info[0] >= 3:
style = json.load(open(os.path.join(directory,
"kf_book/538.json")))
else:
style = json.load(open(directory + "/kf_book/538.json"),
object_hook=_decode_dict)
plt.rcParams.update(style)
except:
pass
set_figsize()
reset_axis()
np.set_printoptions(suppress=True,
precision=3,
linewidth=70,
formatter={'float': lambda x: ' {:.3}'.format(x)})
styles = open(os.path.join(directory, name), 'r').read()
set_figsize()
return HTML(styles)
def load_style(directory = '.', name='kf_book/custom.css'):
version = [int(version_no) for version_no in matplotlib.__version__.split('.')]
try:
if sys.version_info[0] >= 3:
style = json.load(open(os.path.join(directory, "kf_book/538.json")))
else:
style = json.load(open(directory + "/kf_book/538.json"), object_hook=_decode_dict)
plt.rcParams.update(style)
except:
pass
set_figsize()
reset_axis ()
np.set_printoptions(suppress=True, precision=3,
threshold=10000., linewidth=70,
formatter={'float':lambda x:' {:.3}'.format(x)})
styles = open(os.path.join(directory, name), 'r').read()
set_figsize()
# I don't know why I have to do this, but I have to call
# with suppress a second time or the notebook doesn't suppress
# exponents
np.set_printoptions(suppress=True)
return HTML(styles)
def load_style(directory = '.', name='kf_book/custom.css'):
version = [int(version_no) for version_no in matplotlib.__version__.split('.')]
try:
if sys.version_info[0] >= 3:
style = json.load(open(os.path.join(directory, "kf_book/538.json")))
else:
style = json.load(open(directory + "/kf_book/538.json"), object_hook=_decode_dict)
# matplotlib has deprecated the use of axes.color_cycle as of version
if version[0] > 1 or (version[0] == 1 and version[1] >= 5):
style["axes.prop_cycle"] = "cycler('color', ['#6d904f','#013afe', '#202020','#fc4f30','#e5ae38','#A60628','#30a2da','#008080','#7A68A6','#CF4457','#188487','#E24A33'])"
style.pop("axes.color_cycle", None)
plt.rcParams.update(style)
except:
pass
set_figsize()
reset_axis ()
np.set_printoptions(suppress=True,precision=3, linewidth=70,
formatter={'float':lambda x:' {:.3}'.format(x)})
styles = open(os.path.join(directory, name), 'r').read()
set_figsize()
return HTML(styles)
estimated_weight = predicted_weight + scale_factor * (z -
predicted_weight)
# save and log
estimates.append(estimated_weight)
predictions.append(predicted_weight)
if do_print:
gh.print_results(estimates, predicted_weight, estimated_weight)
return estimates, predictions
initial_estimate = 160.
estimates, predictions = predict_using_gain_guess(
estimated_weight=initial_estimate, gain_rate=1, do_print=True)
book_plots.set_figsize(10)
# weights.insert(0, 160)
plt.figure()
gh.plot_gh_results(weights, estimates, predictions, [160, 172])
# plt.show()
print(weights)
e, p = predict_using_gain_guess(initial_estimate, -1.)
plt.figure()
gh.plot_gh_results(weights, e, p, [160, 172])
# plt.show()
print(weights)
# change gain rate
weight = 160. # initial guess
gain_rate = -1.0 # initial guess