%pylab inline --no-import-all
Populating the interactive namespace from numpy and matplotlib
from skimage.io import imread
import glob
import matplotlib.pyplot as plt
# neserazeny seznam
pth = '/home/mjirik/tmp/Falling_frequency_resampled/*.jpg'
pth = "E:\\data\\lynx_lynx\\fotopasti_20170825\\fotky\\bez rysa\\lok3\\2016_04_23\\*.JPG"
filelist = glob.glob(pth)
# print(filelist)
# seradit
filelist.sort()
# vizualizace
plt.figure(figsize=(15,10))
for i in range(6):
img = plt.imread(filelist[i])
plt.subplot(2,3,i+1)
plt.axis('off')
plt.imshow(img)
# Toto je důležité vložit nekomentované na začátek jupyter notebooku pro spuštění externího editoru sed3 i ginput
# % matplotlib qt
plt.imshow(img)
# left mouse button - add point
# right mouse button - remove last point
# middle mouse button - finish
plt.ginput(-1)
C:\Users\miros\Miniconda3\envs\animalwatch\lib\site-packages\matplotlib\figure.py:459: UserWarning: matplotlib is currently using a non-GUI backend, so cannot show the figure "matplotlib is currently using a non-GUI backend, "
[]
import pandas as pd
df = pd.DataFrame({
'time':[1.0, 2.0, 3., 2., 3., 4.],
'id': [1, 1, 1, 2, 2, 2],
'x_px': [10, 12, 13, 5, 8, 10],
'y_px': [11, 10, 12, 5, 7, 6],
}
)
df.to_csv('vystup.csv')
df =pd.read_csv('vystup.csv', index_col=0)
df
time | id | x_px | y_px | |
---|---|---|---|---|
0 | 1.0 | 1 | 10 | 11 |
1 | 2.0 | 1 | 12 | 10 |
2 | 3.0 | 1 | 13 | 12 |
3 | 2.0 | 2 | 5 | 5 |
4 | 3.0 | 2 | 8 | 7 |
5 | 4.0 | 2 | 10 | 6 |
df.sort_values(["time", "id"])
time | id | x_px | y_px | |
---|---|---|---|---|
0 | 1.0 | 1 | 10 | 11 |
1 | 2.0 | 1 | 12 | 10 |
3 | 2.0 | 2 | 5 | 5 |
2 | 3.0 | 1 | 13 | 12 |
4 | 3.0 | 2 | 8 | 7 |
5 | 4.0 | 2 | 10 | 6 |
import numpy as np
# df['x_px'][1:].ast
# df['x_px'][:-1]
dfid2 = df[df['id'] == 2]
dfid2
time | id | x_px | y_px | |
---|---|---|---|---|
3 | 2.0 | 2 | 5 | 5 |
4 | 3.0 | 2 | 8 | 7 |
5 | 4.0 | 2 | 10 | 6 |
df2 = df[['x_px', 'y_px']]
df2
x_px | y_px | |
---|---|---|
0 | 10 | 11 |
1 | 12 | 10 |
2 | 13 | 12 |
3 | 5 | 5 |
4 | 8 | 7 |
5 | 10 | 6 |
df['x_px'].mean()
9.666666666666666
df ['soucin'] = df['x_px'] * df['y_px']
df
time | id | x_px | y_px | soucin | |
---|---|---|---|---|---|
0 | 1.0 | 1 | 10 | 11 | 110 |
1 | 2.0 | 1 | 12 | 10 | 120 |
2 | 3.0 | 1 | 13 | 12 | 156 |
3 | 2.0 | 2 | 5 | 5 | 25 |
4 | 3.0 | 2 | 8 | 7 | 56 |
5 | 4.0 | 2 | 10 | 6 | 60 |
df3 = df2.rename(columns={"x_px": 'X_px', 'y_px': "Y_px"})
df3
X_px | Y_px | |
---|---|---|
0 | 10 | 11 |
1 | 12 | 10 |
2 | 13 | 12 |
3 | 5 | 5 |
4 | 8 | 7 |
5 | 10 | 6 |
df3["new column"] = 0
for i in range(0, len(df3['Y_px'])):
df3.loc[i]["new column"] = df3.iloc[i]["X_px"] + 5
df3
X_px | Y_px | new column | |
---|---|---|---|
0 | 10 | 11 | 15 |
1 | 12 | 10 | 17 |
2 | 13 | 12 | 18 |
3 | 5 | 5 | 10 |
4 | 8 | 7 | 13 |
5 | 10 | 6 | 15 |
import seaborn as sns
sns.boxplot(data=df, x="id", y="x_px")
<AxesSubplot:xlabel='id', ylabel='x_px'>
sns.lineplot(data=df, x="x_px", y="y_px", hue="id")
<AxesSubplot:xlabel='x_px', ylabel='y_px'>
import numpy as np
def main():
print np.random.random([3,4])
if __name__ == "__main__":
main()
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("-i", '--inputdata', help="input data directory")
parser.add_argument('-dt', '--time')
parser.add_argument('-d', '--debug', action="store_true")
args = parser.parse_args()
args.inputdata
args.time
if args.debug:
print "debugovaci rezim"
import folium
from IPython.display import HTML
map1 = folium.Map(location=[49.726578, 13.352427])
folium.Marker([49.726578, 13.352427], popup='FAV').add_to(map1)
# m.add_children(folium.Marker([49.726578, 13.352427]))
map1
map1.save("map.html")