def main():
data_frame = pandasReader.read_from_excel()
min_data_row = appearTimes.get_min_data_row(data_frame)
print('MinDataRow=', min_data_row)
last_data = pandasReader.get_last_red_data(data_frame)
count = 20
plat_whole = plt.subplot2grid((1, count + 1), (0, 0))
list_ball_all = appearTimes.get_all_ball_times(data_frame)
appearTimes.draw_appear_times(list_ball_all, plat_whole, last_data)
start_row = data_frame.size - min_data_row - count
for index in range(start_row, data_frame.size - min_data_row):
data_frame_latest_all = data_frame.tail(data_frame.size - index)
data_frame_latest_30 = data_frame_latest_all.head(min_data_row)
# print (data_frame_latest_30)
list_balls = appearTimes.get_all_ball_times(data_frame_latest_30)
plat_latest_30 = plt.subplot2grid((1, count + 1),
(0, index - start_row + 1))
appearTimes.draw_appear_times(list_balls, plat_latest_30, last_data)
#
# plat_inner_10 = plt.subplot2grid((1,5),(0,2))
# data_frame_latest_30_10 = data_frame_latest_30.head(10)
# QuartileAnalysis(data_frame_latest_30_10, plat_inner_10,last_data)
# plat_inner_30 = plt.subplot2grid((1,5),(0,3))
# data_frame_latest_30_30 = data_frame_latest_30.tail(10)
# QuartileAnalysis(data_frame_latest_30_30, plat_inner_30,last_data)
# plat_inner_20 = plt.subplot2grid((1,5),(0,4))
# data_frame_latest_30_20_whole = data_frame_latest_30.tail(20)
# data_frame_latest_30_20 = data_frame_latest_30_20_whole.head(10)
# QuartileAnalysis(data_frame_latest_30_20, plat_inner_20,last_data)
plt.show()
def main():
"""
绘制出现次数和选中的点阵图
:return:
"""
data_frame = pandasReader.read_from_excel()
min_data_row = 5
step = 5
list_num_times, list_sel_flags = appearTimesInGroup.get_appear_times_list(
data_frame, min_data_row, step)
x = range(0, 6)
index_row = 0
index_col = 0
for index, list_times in enumerate(list_num_times):
list_flags = list_sel_flags[index]
res_fit_count = [0] * 6
res_unfit_count = [0] * 6
for i, val in enumerate(list_times):
if list_flags[i] != 0:
res_fit_count[val] += 1
else:
res_unfit_count[val] -= 1
plt_c = plt.subplot2grid((4, 10), (index_row, index_col))
index_col += 1
if index_col >= 10:
index_row += 1
index_col = 0
matBar(plt_c, res_fit_count, res_unfit_count, x)
# matBar(res_fit_count, res_unfit_count, x)
plt.show()
def main():
data_frame = pandasReader.read_from_excel()
min_data_row = 5
step = 5
list_num_times, list_sel_flags = appearTimesInGroup.get_appear_times_list(data_frame, min_data_row, step)
list_probability = cycle_times_probability(list_num_times, list_sel_flags, min_data_row)
print list_probability
list_probability_fit = cycle_times_probability_fit(list_num_times, list_sel_flags, min_data_row)
print list_probability_fit
list_probability_unfit = cycle_times_probability_unfit(list_num_times, list_sel_flags, min_data_row)
print list_probability_unfit
def main():
data_frame = pandasReader.read_from_excel()
list_numbers = get_appear_matrix(data_frame)
list_space = get_appear_space_times(list_numbers)
print(list_numbers)
print(list_space)
print(len(list_space))
for one_ball in enumerate(list_space):
dict_space = get_appear_space_frequency(one_ball[1])
x = dict_space.keys()
y = dict_space.values()
for index, times in enumerate(y):
y *= 100
plt.bar(x, y, facecolor='blue')
plt.show()
def main():
data_frame = pandasReader.read_from_excel()
#min_data_row = appearTimes.get_min_data_row(data_frame)
min_data_row = 5
step = 5
list_num_times = appearTimesInGroup.get_appear_frequency_list(
data_frame, min_data_row, step)
print(list_num_times)
count = appearTimesInGroup.get_count_groups(data_frame, min_data_row)
col_count = appearTimesInGroup.get_column_count(count, step)
list_index = range(0, col_count)
row = 0
col = 0
min_fre = 100
max_fre = 0
for x in list_num_times:
for item in x:
min_fre = min(min_fre, item)
max_fre = max(max_fre, item)
for x in list_num_times:
plot_w = plt.subplot2grid((1, 1), (0, 0))
std_cha = np.std(x)
middle_val = np.mean(x)
percent_25 = middle_val - std_cha
percent_75 = middle_val + std_cha
plot_w.set_ylim(min_fre, max_fre)
plot_w.plot(list_index, x, color='green')
plot_w.set_title(row * 10 + col + 1)
plot_w.hlines(percent_25, 1, len(list_index), colors='r')
plot_w.hlines(middle_val, 1, len(list_index), colors='r')
plot_w.hlines(percent_75, 1, len(list_index), colors='r')
plt.show()
col = col + 1
if col >= 10:
row = row + 1
col = 0
def main():
data_frame = pandasReadExcel.read_from_excel()
print(data_frame)
last_data = pandasReadExcel.get_last_red_data(data_frame)
print(last_data)
#-*- coding:utf-8 -*-
import matplotlib.pyplot as plt
import pandasReadExcel as pandasReader
import numpy as np
import appearTimesInGroup
data_frame = pandasReader.read_from_excel()
min_data_row = 10
step = 10
def main():
list_num_times_freq = appearTimesInGroup.get_appear_times_frequency_list(
data_frame, min_data_row, step)
# count = appearTimesInGroup.get_count_groups(data_frame, min_data_row)
# col_count = appearTimesInGroup.get_column_count(count, step)
# row = 0
# col = 0
# list_index = range(0, min_data_row+1)
#
# for x in list_num_times_freq:
# plot_w = plt.subplot2grid((4, 10), (row, col))
# plot_w.bar(list_index, x, facecolor ='green')
# plot_w.set_title(row* 10+ col+1)
# col = col+ 1
# if col>= 10:
# row= row+ 1
# col = 0
# plt.show()