Reading MATLAB .mat files

In one of the radiation lecture, you are asked to read files in the MATLAB .mat files (one file per day with vectors of I measured at the surface at 450 nm, along with the sun elevation angle for each measurement SNH). There seem to be no time attached to these measurements. Here is an example of how to read one of the file into a pandas dataframe with help of the scipy library:

Reading mat files

from scipy.io import loadmat  # this is the SciPy module that loads mat-files
import pandas as pd
import matplotlib.pyplot as plt

mat = loadmat('I_and_SNH_20111003.mat')

# Put all columns which are not weird MATLAB ones into a dataframe
df = pd.DataFrame()
for k in mat:
    if '__' in k:
        continue
    df[k] = mat[k].flatten()

# Name it "day1" for clarity
df_day1 = df
df_day1

	SNH	I_450
0	10.028338	0.238662
1	10.838524	0.282054
2	11.646388	0.321627
3	12.446173	0.361128
4	13.246367	0.398293
...	...	...
109	13.503050	0.485676
110	12.684507	0.442991
111	11.890372	0.395319
112	11.071531	0.343366
113	10.293703	0.302224

114 rows × 2 columns

Plots

df_day1.plot();

df_day1.plot(x='SNH', y='I_450');

df_day1_morning = df_day1.loc[:df_day1['SNH'].argmax()]
df_day1_afternoon = df_day1.loc[df_day1['SNH'].argmax()+1:]

f, ax = plt.subplots()
df_day1_morning.plot(x='SNH', y='I_450', ax=ax, label='Morning');
df_day1_afternoon.plot(x='SNH', y='I_450', ax=ax, label='Afternoon');

Merge several days into one dataframe

import glob

all_df = []
for f in sorted(glob.glob('*.mat')):

    mat = loadmat(f)

    # Put all columns which are not weird MATLAB ones into a dataframe
    df = pd.DataFrame()
    for k in mat:
        if '__' in k:
            continue
        df[k] = mat[k].flatten()
    df['date'] = f.split('_')[-1].split('.')[0]

    all_df.append(df)

all_df = pd.concat(all_df, ignore_index=True)
all_df

	SNH	I_450	date
0	10.028338	0.238662	20111003
1	10.838524	0.282054	20111003
2	11.646388	0.321627	20111003
3	12.446173	0.361128	20111003
4	13.246367	0.398293	20111003
...	...	...	...
450	16.725457	0.630984	20120514
451	15.535872	0.577296	20120514
452	14.617152	0.532635	20120514
453	13.705881	0.487820	20120514
454	12.807493	0.449735	20120514

455 rows × 3 columns

all_df.plot(x='SNH', y='I_450', style='.');