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()