本文整理汇总了Python中options.Options.plot_one_pdf方法的典型用法代码示例。如果您正苦于以下问题：Python Options.plot_one_pdf方法的具体用法？Python Options.plot_one_pdf怎么用？Python Options.plot_one_pdf使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类options.Options的用法示例。
在下文中一共展示了Options.plot_one_pdf方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: event_classes
# 需要导入模块: from options import Options [as 别名]
# 或者: from options.Options import plot_one_pdf [as 别名]
def event_classes(DIC,save=False):
"""
- for each event, looks for the class it belongs to for each training set ;
if the event is not classified, class label is set to 99 by default.
- it the labels are different from a set to another, then displays the
waveform and ask the user to assign a class manually.
- if save=True: saves the new classification in a new file.
"""
from options import Options
opt = Options()
all = np.array(map(str,list(opt.raw_df[opt.raw_df.columns[0]])))
types = np.unique(opt.raw_df.Type).values
df = opt.raw_df
df.index = all
manuals = opt.manuals
manuals.index = map(str,list(manuals[manuals.columns[0]]))
new_class = []
all_classes = []
for event in all:
l = []
for iter in sorted(DIC):
if iter != 'features':
marker = 0
for it,t in enumerate(types):
if event in DIC[iter][t]['index_ok']:
l.append(it)
marker = 1
continue
for tup in DIC[iter][t]['i_other']:
if event in tup[1]:
itype = np.where(types==t)[0][0]
l.append(itype)
marker = 1
if marker == 0:
l.append(99)
print event, l
cl = np.unique(np.array(l))
date_ok = event[:8]+'_'+event[8:]
mant = manuals.reindex(index=[event],columns=['Type']).values[0][0]
m = 0
if len(cl) == 1 and cl[0] != 99 and types[cl[0]] != mant:
m = 1
if len(cl) > 1 or m==1:
if 99 not in cl:
print "\t", mant, types[cl]
else:
print "\t", mant, types[cl[:-1]], 'unclassified'
m = 2
if m == 2 and len(types[cl[:-1]])== 1:
final_cl = types[cl[:-1]][0]
elif len(cl) == 1: # if the automatic classification is systematically the same whatever training set is used, BUT different from the manual classification, then...
final_cl = types[cl][0]
#else:
file = glob.glob('/home/nadege/Desktop/IJEN_GOOD/DATA/*%s*.SAC'%date_ok)[0]
a = df.reindex(index=[event])
st = read(file)
st[0].plot()
for feat in opt.opdict['feat_list']:
if feat != 'NbPeaks':
opt.plot_one_pdf(feat,[(mant,a[feat].values,final_cl)])
if save:
final_cl = str(raw_input("\t Quelle classe ? "))
print "\n"
else:
if l[0] != 99:
final_cl = types[l[0]]
else:
final_cl = 'Unclass'
new_class.append(final_cl)
if save:
df_new = manuals.reindex(columns=['Filename','Type'])
df_new['NewType'] = new_class
df_new.to_csv('../lib/Ijen/svm_reclass.csv')