workshop 4 files

Author: gcielniak

evaluation/numpy_stats.py

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+import csv
+import numpy as np
+import matplotlib.pyplot as plt
+
+# load data from csv file as a numpy array
+data = np.genfromtxt('evaluation/ref_data/head_size_gt.csv', delimiter=',')
+
+# Broccoli head size measurements (in mm) for training vision systems for robotic harvesters
+# for more details see Kusumam et al., 2017: https://onlinelibrary.wiley.com/doi/full/10.1002/rob.21726
+
+print('sample size {0:d}'.format(len(data)))
+
+bin_nr = 20
+bin_range = (70,210) # None for auto
+
+# calculate all stats
+st_mean = np.mean(data)
+st_std = np.std(data)
+st_min = np.min(data)
+st_max = np.max(data)
+st_median = np.median(data)
+st_qnt_05 = np.quantile(data, 0.05)
+st_qnt_95 = np.quantile(data, 0.95)
+st_loqrt = np.quantile(data, 0.25)
+st_upqrt = np.quantile(data, 0.75)
+h_count, h_range = np.histogram(data, bins=bin_nr, range=bin_range)
+
+# print out the results
+print(f'mean {st_mean:.2f} std {st_std:.2f}')
+print(f'min {st_min:.2f} max {st_max:.2f} range {st_max-st_min:.2f}')
+
+print(f'median {st_median:.2f}')
+print(f'quantile: qnt_05% {st_qnt_05:.2f} qnt_95% {st_qnt_95:.2f} range {st_qnt_95-st_qnt_05:.2f}')
+print(f'quartile: lower {st_loqrt:.2f} upper {st_upqrt:.2f} range {st_upqrt-st_loqrt:.2f}')
+
+print('histogram:')
+print(' - bin counts ', h_count)
+print(' - bin ranges ', h_range)
+
+#plotting histograms with the same settings as above
+plt.hist(data, bins=bin_nr, range=bin_range)
+
+# plot the stats, uncomment if desired
+
+# plt.axvline(st_mean, linestyle='dashed')
+# plt.axvline(st_min, linestyle='dashed')
+# plt.axvline(st_max, linestyle='dashed')
+
+# plt.axvline(st_median, color='tab:orange', linestyle='dotted')
+# plt.axvline(st_qnt_05, color='tab:orange', linestyle='dotted')
+# plt.axvline(st_qnt_95, color='tab:orange', linestyle='dotted')
+
+# min_ylim, max_ylim = plt.ylim()
+# x_offset = 1.01
+# y_offset = max_ylim*0.9
+# plt.text(st_mean*x_offset, y_offset, f'mean = {st_mean:.1f}')
+# plt.text(st_min*x_offset, y_offset, f'min = {st_min:.1f}')
+# plt.text(st_max*x_offset, y_offset, f'max = {st_max:.1f}')
+
+# y_offset = max_ylim*0.7
+# plt.text(st_median*x_offset, y_offset, f'median = {st_median:.1f}', color='tab:orange')
+# plt.text(st_qnt_05*x_offset, y_offset, f'qnt_05% = {st_qnt_05:.1f}', color='tab:orange')
+# plt.text(st_qnt_95*x_offset, y_offset, f'qnt_95% = {st_qnt_95:.1f}', color='tab:orange')
+
+plt.title(f'histogram bin_nr = {bin_nr:d}')
+
+plt.show()

evaluation/ref_data/head_size_gt.csv

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+138.0,168.0,163.5,170.5,149.0,150.0,156.5,136.5,127.5,177.5,145.0,154.0,140.5,165.5,178.0,129.5,148.5,122.5,149.0,140.5,141.0,169.5,110.5,93.5,173.0,167.5,135.0,178.5,203.5,176.0,178.5,173.0,97.5,160.0,163.0,173.5,151.5,92.5,152.5,155.0,150.0,168.5,136.0,142.5,149.0,143.0,141.0,152.5,133.5,130.0,125.5,157.5,155.5,163.5,145.5,81.5,76.5,191.0,139.5,101.0,94.0,133.0,178.5,174.5,110.5,162.5,101.5,155.0,163.0,146.0,172.5,137.5,154.0,142.0,143.5,178.5,169.0,154.5,129.5,165.0,169.0,149.5,105.5,167.5,153.5,166.0,167.0,167.0,177.5,145.5,133.5,150.5,141.0,168.0,147.5,109.5,157.5,167.5,127.5,141.5