Skip to content

Remove duplicate open_data function #38

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
wants to merge 1 commit into
base: master
Choose a base branch
from
Open

Remove duplicate open_data function #38

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
141 changes: 0 additions & 141 deletions imdlib/core.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -514,147 +514,6 @@ def open_data(var_type, start_yr, end_yr=None, fn_format=None, file_dir=None):
# Get total no of days (considering leap years)
no_days = total_days(start_day, end_day)

# Decide which variable we are looking into
if var_type == 'rain':
lat_size_class = lat_size_rain
lon_size_class = lon_size_rain
elif var_type == 'tmin' or var_type == 'tmax':
lat_size_class = lat_size_temp
lon_size_class = lon_size_temp
else:
raise Exception("Error in variable type declaration."
"It must be 'rain'/'tmin'/'tmax'. Note: 'rain_gpm' is only available for real-time data.")

# Loop through all the years
# all_data -> container to store data for all the year
# all_data.shape = (no_days, len(lon), len(lat))
all_data = np.empty((no_days, lon_size_class, lat_size_class))
# Counter for total days. It helps filling 'all_data' array.
count_day = 0
for i in range(start_yr, end_yr + 1):

# Decide resolution of input file name
fname = get_filename(i, var_type, fn_format, file_dir)

# Check if current year is leap year or not
if LeapYear(i):
days_in_year = 366
else:
days_in_year = 365

# length of total data point for current year
nlen = days_in_year * lat_size_class * lon_size_class

# temporary variable to read binary data
temp = array.array("f")
with open(fname, 'rb') as f:
temp.fromfile(f, os.stat(fname).st_size // temp.itemsize)

data = np.array(list(map(lambda x: x, temp)))

# Added for new url (dated:Oct 10, 2022)
# Removing first element for rain for new url: https://imdpune.gov.in/lrfindex.php
# Removing (commented out) as it was no longer needed to remove the first element anymore. (dated: March 31, 2023)
# if var_type == 'rain':
# data = data[1:]

# Check consistency of data points
if len(data) != nlen:
raise Exception("Error in file reading,"
"mismatch in size of data-length")

# Reshape data into a shape of
# (days_in_year, lon_size_class, lat_size_class)
data = np.transpose(np.reshape(data, (days_in_year, lat_size_class,
lon_size_class), order='C'), (0, 2, 1))
all_data[count_day:count_day + len(data), :, :] = data
count_day += len(data)
# Stack data vertically to get multi-year data
# if i != time_range[0]:
# all_data = np.vstack((all_data, data))
# else:
# all_data = data

# Create a IMD object
if var_type == 'rain':
data = IMD(all_data, 'rain', start_day, end_day, no_days,
lat_rain, lon_rain)
elif var_type == 'tmin':
data = IMD(all_data, 'tmin', start_day, end_day, no_days,
lat_temp, lon_temp)
elif var_type == 'tmax':
data = IMD(all_data, 'tmax', start_day, end_day, no_days,
lat_temp, lon_temp)
else:
raise Exception("Error in variable type declaration."
"It must be 'rain'/'tmin'/'tmax'. Note: 'rain_gpm' is only available for real-time data.")

return data


def open_data(var_type, start_yr, end_yr=None, fn_format=None, file_dir=None):
"""
Function to read binary data and return an IMD class object
time range is tuple or list or numpy array of 2 int number

Parameters
----------
var_type : str
Three possible values.
1. "rain" -> input files are for daily rainfall values
2. "tmin" -> input files are for daily minimum temperature values
3. "tmax" -> input files are for daily maximum tempereature values

start_yr : int
Starting year for opening data

end_yr : int
Ending year for opening data

fn_format : str or None
fn_format represent filename format. Default vales is None.
Which means filesnames are accoding to the IMD conventionm and
they are not changed after downloading from IMD server.
If we specify fn_format = 'yearwise',
filenames are renamed like <year.grd> (e.g. 2018.grd)

file_dir : str or None
Directory cache the files for future processing.
If None, the currently working directory is used.
If specify the directory address,
Main directory should contain 3 subdirectory. <rain>, <tmin>, <tmax>

Returns
-------
IMD object

"""

# Parameters about IMD grid from:
# http://www.imdpune.gov.in/Clim_Pred_LRF_New/Grided_Data_Download.html
#######################################
lat_size_rain = 129
lon_size_rain = 135
lat_rain = np.linspace(6.5, 38.5, lat_size_rain)
lon_rain = np.linspace(66.5, 100.0, lon_size_rain)

lat_size_temp = 31
lon_size_temp = 31
lat_temp = np.linspace(7.5, 37.5, lat_size_temp)
lon_temp = np.linspace(67.5, 97.5, lon_size_temp)
#######################################
# Format Date into <yyyy-mm-dd>

# Handling ending year not given case
if sum([bool(start_yr), bool(end_yr)]) == 1:
end_yr = start_yr

start_day = "{}{}{:02d}{}{:02d}".format(start_yr, '-', 1, '-', 1)
end_day = "{}{}{:02d}{}{:02d}".format(end_yr, '-', 12, '-', 31)

# Get total no of days (considering leap years)
no_days = total_days(start_day, end_day)

# Decide which variable we are looking into
if var_type == 'rain':
lat_size_class = lat_size_rain
Expand Down