# # Loading data in Colab - pick one way to do it
# # ---------------------------------------------------------------------
# # Importing data files from local machine
# from google.colab import files
# uploaded = files.upload()

# # Mounting the Google Drive to access files
# from google.colab import drive
# drive.mount('/content/drive')

# # Import data files using the user interface

# # Mount drive using the user interface

from google.colab import drive
drive.mount('/content/drive')

# Using readlines()
# ---------------------------------------------------------------------
filepath = 'drive/My Drive/Data_folder/Seattle_tides_predicted_20201001_20201024.txt'

# Open the file
file_obj = open(filepath,'r')

# Read the file
lines = file_obj.readlines()

# Close the file
file_obj.close()

print(lines)
print(len(lines))

# Using readline()
# ---------------------------------------------------------------------
filepath = 'drive/My Drive/Data_folder/Seattle_tides_predicted_20201001_20201024.txt'

# Open the file
file_obj = open(filepath,'r')

# Read the file - first 30 lines
for index in range(30):
  line = file_obj.readline()
  print(line)

# Close the file
file_obj.close()

# Using np.genfromtxt()
# ---------------------------------------------------------------------
import numpy as np
filepath = 'drive/My Drive/Data_folder/Seattle_tides_predicted_20201001_20201024.txt'

# Read the data and the date information separately
# Use function arguments and your knowledge of the file structure to format these lines
data = np.genfromtxt(filepath,skip_header=14,dtype=float,usecols=3,delimiter=None)
data_time = np.genfromtxt(filepath,skip_header=14,dtype=str,usecols=(0,1,2),delimiter=None)

# Looking at the results
print('Length:',len(data))
print(data)
print()
print('Length:',len(data_time))
print(data_time)

import matplotlib.pyplot as plt

# Figure and empty axes
# ---------------------------------------------------------------------
fig,ax = plt.subplots()

# Figure and empty axes with custom size
# ---------------------------------------------------------------------
fig,ax = plt.subplots(figsize=(15,5))

# Figure and multiple empty axes
# ---------------------------------------------------------------------
fig,(ax0,ax1) = plt.subplots(nrows=2,ncols=1)

# Line plot
# ---------------------------------------------------------------------
import numpy as np
import matplotlib.pyplot as plt
filepath = 'drive/My Drive/Data_folder/Seattle_tides_predicted_20201001_20201024.txt'

# Read the data and create a time array
data = np.genfromtxt(filepath,skip_header=14,dtype=float,usecols=3,delimiter=None)
time = np.linspace(0,len(data)/10,len(data)) # 6 min freq. so len(data)/10 = # of hours

# Create the plot and put the data in it
fig,ax = plt.subplots()
ax.plot(time, data, c='r',linestyle='-', linewidth=2, marker=None)

# Figure formatting
ax.grid()
ax.set_title('Seattle tides (Oct. 1-24, 2020)', fontsize=18)
ax.set_xlabel('Time since Oct. 1st 00:00 (hours)', fontsize=14)
ax.set_ylabel('Daily tide predictions (m)', fontsize=14)


# Scatter plot - CTD data
# ---------------------------------------------------------------------

# Look at the file
filepath = 'drive/My Drive/Data_folder/a03_00011_1993CTD_data.csv'

file_obj = open(filepath, 'r')

for index in range(90):
  line = file_obj.readline()
  print(line)

file_obj.close()

# Scatter plot - creating the figure
# ---------------------------------------------------------------------
filepath = 'drive/My Drive/Data_folder/a03_00011_1993CTD_data.csv'

# Load the data
data = np.genfromtxt(filepath,skip_header=20,skip_footer=1,delimiter=',',usecols=(0,2,4))

# Separate out the columns into individual variables
P = data[:,0]
T = data[:,1]
S = data[:,2]

# Create the figure and scatter the data
fig,ax = plt.subplots(figsize=(10,8))
scpl = ax.scatter(S, T, s=30, c=P, alpha=0.5)

# Format the figure
ax.set_title('Temperature and Salinity, 1993 CTD', fontsize=18)
ax.set_ylabel('Temperature (degC)', fontsize=14)
ax.set_xlabel('Salinity (PSU)', fontsize=14)
ax.grid(linestyle='-.')
c = fig.colorbar(scpl,ax=ax)
c.set_label('Pressure (dbar)',fontsize=12)