Well ID and other comments in stress period data in flopy
up vote
1
down vote
favorite
I would like to assign a commented out Well ID number to my well file, (also do the same for ghb cells) but I cannot find anything on how to do so.
I wrote something to create my own ghb file but if I try to load it back into my flopy mf class, and later write it out my other packages with mf.write_input() the comments do not stay and it gets overwritten.
I know in mf.wrtie_input() I can specify what packages to write out, and if I take away the ghb file I made earlier (or well file) then the original file does not get written over which is good.
But I would like to know if there is a way to straight up add comments to the stress_period_data for each package so I can keep it all contained in the flopy class.
Thanks
python flopy
add a comment |
up vote
1
down vote
favorite
I would like to assign a commented out Well ID number to my well file, (also do the same for ghb cells) but I cannot find anything on how to do so.
I wrote something to create my own ghb file but if I try to load it back into my flopy mf class, and later write it out my other packages with mf.write_input() the comments do not stay and it gets overwritten.
I know in mf.wrtie_input() I can specify what packages to write out, and if I take away the ghb file I made earlier (or well file) then the original file does not get written over which is good.
But I would like to know if there is a way to straight up add comments to the stress_period_data for each package so I can keep it all contained in the flopy class.
Thanks
python flopy
add a comment |
up vote
1
down vote
favorite
up vote
1
down vote
favorite
I would like to assign a commented out Well ID number to my well file, (also do the same for ghb cells) but I cannot find anything on how to do so.
I wrote something to create my own ghb file but if I try to load it back into my flopy mf class, and later write it out my other packages with mf.write_input() the comments do not stay and it gets overwritten.
I know in mf.wrtie_input() I can specify what packages to write out, and if I take away the ghb file I made earlier (or well file) then the original file does not get written over which is good.
But I would like to know if there is a way to straight up add comments to the stress_period_data for each package so I can keep it all contained in the flopy class.
Thanks
python flopy
I would like to assign a commented out Well ID number to my well file, (also do the same for ghb cells) but I cannot find anything on how to do so.
I wrote something to create my own ghb file but if I try to load it back into my flopy mf class, and later write it out my other packages with mf.write_input() the comments do not stay and it gets overwritten.
I know in mf.wrtie_input() I can specify what packages to write out, and if I take away the ghb file I made earlier (or well file) then the original file does not get written over which is good.
But I would like to know if there is a way to straight up add comments to the stress_period_data for each package so I can keep it all contained in the flopy class.
Thanks
python flopy
python flopy
asked Nov 11 at 14:56
rosskush
91
91
add a comment |
add a comment |
2 Answers
2
active
oldest
votes
up vote
2
down vote
Like in this example, you can extend the default dtype
to include extra attributes that the MfList
instance will carry to the write:
well_dtype = [('k', '<i8'), ('i', '<i8'), ('j', '<i8'),('flux', '<f4'), ('wel_id', object)]
stress_period_data = np.zeros((3), dtype=well_dtype)
wel = flopy.modflow.ModflowWel(m, stress_period_data=stress_period_data, dtype=well_dtype)
I'm not sure of an easy way to load an existing wel
package with extra attributes - just FYI
Awesome, thanks, changing the dtype makes perfect sense.
– rosskush
Nov 11 at 18:23
So for stress period data I typically use dictionaries and not arrays, for example: spd = 0:[l,r,c,flux],1:[l,r,c,flux]... etc, how would I go about making it to where I can use a dictionary that looks like 0:[l,r,c,flux,well_ID],1:[l,r,c,flux,well_ID]? or if it's easier, convert my dictionaries to arrays, I know I could force my dictionary to an array but would be curious to know if it is possible to stick with only dictionaries
– rosskush
Nov 26 at 19:17
add a comment |
up vote
0
down vote
The only way I know to carry remarks over from an existing package is to open the file in read mode, create a pandas DataFrame with the column data, and build a new package out of it. Here is an example:
import os
import pandas as pd
import flopy.modflow as fpm
from collections import OrderedDict
pak_nam = 'drn'
mf_version = 'mfnwt'
# the model from which the DRN package will be copied
inmod = fpm.Modflow.load('10kTDS.nam',
model_ws=r'..10kTDS',
version=mf_version,
load_only=['drn'],
check=False)
# the model where the new DRN package will be attached
mf = fpm.Modflow.load('ss2010.nam',
model_ws=os.path.join('..', 'ss2010'),
version=mf_version,
load_only=['dis', 'bas6'],
check=False)
# read the contents of the DRN package
with open(inmod.drn.fn_path, 'r') as f:
lines = f.readlines()
# create pandas DataFrame
data =
for line in lines[3:]:
pieces = line.strip().split('#')
t = pieces[0].strip().split()
remark = pieces[-1]
if t[0] == '-1':
break
else:
data.append([int(t[0]),
int(t[1]),
int(t[2]),
float(t[3]),
float(t[4]),
'# ' + remark.strip()])
pak_df = pd.DataFrame(data,
columns=['k', 'i', 'j', 'alt_va', 'cond', 'remark'])
pak_df.loc[:, ['k', 'i', 'j']] -= 1
# specify data format
formats = OrderedDict([('k', ':>10d'.format),
('i', ':>10d'.format),
('j', ':>10d'.format),
('alt_va', ':>.2F'.format),
('cond', ':>15.6E'.format),
('remark', '>:50'.format)])
# create new stress period data: for numpy record array use DataFrame.to_records()
pak_spd = 0: pak_df[list(formats.keys())].to_records(index=False)
# attach DRN package to new model
pak = fpm.ModflowDrn(mf,
stress_period_data=pak_spd,
ipakcb=53,
options=['NOPRINT'],
filenames=os.path.join('..', 'ss2010', 'ss2010.'.format(pak_nam)),
dtype=pak_spd[0].dtype)
pak.write_file(check=False)
1
Hey Jason, I was able to read in my files in a similar way to yours too, but it would be cool to see something within flopy.
– rosskush
Nov 14 at 16:58
add a comment |
2 Answers
2
active
oldest
votes
2 Answers
2
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
2
down vote
Like in this example, you can extend the default dtype
to include extra attributes that the MfList
instance will carry to the write:
well_dtype = [('k', '<i8'), ('i', '<i8'), ('j', '<i8'),('flux', '<f4'), ('wel_id', object)]
stress_period_data = np.zeros((3), dtype=well_dtype)
wel = flopy.modflow.ModflowWel(m, stress_period_data=stress_period_data, dtype=well_dtype)
I'm not sure of an easy way to load an existing wel
package with extra attributes - just FYI
Awesome, thanks, changing the dtype makes perfect sense.
– rosskush
Nov 11 at 18:23
So for stress period data I typically use dictionaries and not arrays, for example: spd = 0:[l,r,c,flux],1:[l,r,c,flux]... etc, how would I go about making it to where I can use a dictionary that looks like 0:[l,r,c,flux,well_ID],1:[l,r,c,flux,well_ID]? or if it's easier, convert my dictionaries to arrays, I know I could force my dictionary to an array but would be curious to know if it is possible to stick with only dictionaries
– rosskush
Nov 26 at 19:17
add a comment |
up vote
2
down vote
Like in this example, you can extend the default dtype
to include extra attributes that the MfList
instance will carry to the write:
well_dtype = [('k', '<i8'), ('i', '<i8'), ('j', '<i8'),('flux', '<f4'), ('wel_id', object)]
stress_period_data = np.zeros((3), dtype=well_dtype)
wel = flopy.modflow.ModflowWel(m, stress_period_data=stress_period_data, dtype=well_dtype)
I'm not sure of an easy way to load an existing wel
package with extra attributes - just FYI
Awesome, thanks, changing the dtype makes perfect sense.
– rosskush
Nov 11 at 18:23
So for stress period data I typically use dictionaries and not arrays, for example: spd = 0:[l,r,c,flux],1:[l,r,c,flux]... etc, how would I go about making it to where I can use a dictionary that looks like 0:[l,r,c,flux,well_ID],1:[l,r,c,flux,well_ID]? or if it's easier, convert my dictionaries to arrays, I know I could force my dictionary to an array but would be curious to know if it is possible to stick with only dictionaries
– rosskush
Nov 26 at 19:17
add a comment |
up vote
2
down vote
up vote
2
down vote
Like in this example, you can extend the default dtype
to include extra attributes that the MfList
instance will carry to the write:
well_dtype = [('k', '<i8'), ('i', '<i8'), ('j', '<i8'),('flux', '<f4'), ('wel_id', object)]
stress_period_data = np.zeros((3), dtype=well_dtype)
wel = flopy.modflow.ModflowWel(m, stress_period_data=stress_period_data, dtype=well_dtype)
I'm not sure of an easy way to load an existing wel
package with extra attributes - just FYI
Like in this example, you can extend the default dtype
to include extra attributes that the MfList
instance will carry to the write:
well_dtype = [('k', '<i8'), ('i', '<i8'), ('j', '<i8'),('flux', '<f4'), ('wel_id', object)]
stress_period_data = np.zeros((3), dtype=well_dtype)
wel = flopy.modflow.ModflowWel(m, stress_period_data=stress_period_data, dtype=well_dtype)
I'm not sure of an easy way to load an existing wel
package with extra attributes - just FYI
answered Nov 11 at 17:51
JDub
212
212
Awesome, thanks, changing the dtype makes perfect sense.
– rosskush
Nov 11 at 18:23
So for stress period data I typically use dictionaries and not arrays, for example: spd = 0:[l,r,c,flux],1:[l,r,c,flux]... etc, how would I go about making it to where I can use a dictionary that looks like 0:[l,r,c,flux,well_ID],1:[l,r,c,flux,well_ID]? or if it's easier, convert my dictionaries to arrays, I know I could force my dictionary to an array but would be curious to know if it is possible to stick with only dictionaries
– rosskush
Nov 26 at 19:17
add a comment |
Awesome, thanks, changing the dtype makes perfect sense.
– rosskush
Nov 11 at 18:23
So for stress period data I typically use dictionaries and not arrays, for example: spd = 0:[l,r,c,flux],1:[l,r,c,flux]... etc, how would I go about making it to where I can use a dictionary that looks like 0:[l,r,c,flux,well_ID],1:[l,r,c,flux,well_ID]? or if it's easier, convert my dictionaries to arrays, I know I could force my dictionary to an array but would be curious to know if it is possible to stick with only dictionaries
– rosskush
Nov 26 at 19:17
Awesome, thanks, changing the dtype makes perfect sense.
– rosskush
Nov 11 at 18:23
Awesome, thanks, changing the dtype makes perfect sense.
– rosskush
Nov 11 at 18:23
So for stress period data I typically use dictionaries and not arrays, for example: spd = 0:[l,r,c,flux],1:[l,r,c,flux]... etc, how would I go about making it to where I can use a dictionary that looks like 0:[l,r,c,flux,well_ID],1:[l,r,c,flux,well_ID]? or if it's easier, convert my dictionaries to arrays, I know I could force my dictionary to an array but would be curious to know if it is possible to stick with only dictionaries
– rosskush
Nov 26 at 19:17
So for stress period data I typically use dictionaries and not arrays, for example: spd = 0:[l,r,c,flux],1:[l,r,c,flux]... etc, how would I go about making it to where I can use a dictionary that looks like 0:[l,r,c,flux,well_ID],1:[l,r,c,flux,well_ID]? or if it's easier, convert my dictionaries to arrays, I know I could force my dictionary to an array but would be curious to know if it is possible to stick with only dictionaries
– rosskush
Nov 26 at 19:17
add a comment |
up vote
0
down vote
The only way I know to carry remarks over from an existing package is to open the file in read mode, create a pandas DataFrame with the column data, and build a new package out of it. Here is an example:
import os
import pandas as pd
import flopy.modflow as fpm
from collections import OrderedDict
pak_nam = 'drn'
mf_version = 'mfnwt'
# the model from which the DRN package will be copied
inmod = fpm.Modflow.load('10kTDS.nam',
model_ws=r'..10kTDS',
version=mf_version,
load_only=['drn'],
check=False)
# the model where the new DRN package will be attached
mf = fpm.Modflow.load('ss2010.nam',
model_ws=os.path.join('..', 'ss2010'),
version=mf_version,
load_only=['dis', 'bas6'],
check=False)
# read the contents of the DRN package
with open(inmod.drn.fn_path, 'r') as f:
lines = f.readlines()
# create pandas DataFrame
data =
for line in lines[3:]:
pieces = line.strip().split('#')
t = pieces[0].strip().split()
remark = pieces[-1]
if t[0] == '-1':
break
else:
data.append([int(t[0]),
int(t[1]),
int(t[2]),
float(t[3]),
float(t[4]),
'# ' + remark.strip()])
pak_df = pd.DataFrame(data,
columns=['k', 'i', 'j', 'alt_va', 'cond', 'remark'])
pak_df.loc[:, ['k', 'i', 'j']] -= 1
# specify data format
formats = OrderedDict([('k', ':>10d'.format),
('i', ':>10d'.format),
('j', ':>10d'.format),
('alt_va', ':>.2F'.format),
('cond', ':>15.6E'.format),
('remark', '>:50'.format)])
# create new stress period data: for numpy record array use DataFrame.to_records()
pak_spd = 0: pak_df[list(formats.keys())].to_records(index=False)
# attach DRN package to new model
pak = fpm.ModflowDrn(mf,
stress_period_data=pak_spd,
ipakcb=53,
options=['NOPRINT'],
filenames=os.path.join('..', 'ss2010', 'ss2010.'.format(pak_nam)),
dtype=pak_spd[0].dtype)
pak.write_file(check=False)
1
Hey Jason, I was able to read in my files in a similar way to yours too, but it would be cool to see something within flopy.
– rosskush
Nov 14 at 16:58
add a comment |
up vote
0
down vote
The only way I know to carry remarks over from an existing package is to open the file in read mode, create a pandas DataFrame with the column data, and build a new package out of it. Here is an example:
import os
import pandas as pd
import flopy.modflow as fpm
from collections import OrderedDict
pak_nam = 'drn'
mf_version = 'mfnwt'
# the model from which the DRN package will be copied
inmod = fpm.Modflow.load('10kTDS.nam',
model_ws=r'..10kTDS',
version=mf_version,
load_only=['drn'],
check=False)
# the model where the new DRN package will be attached
mf = fpm.Modflow.load('ss2010.nam',
model_ws=os.path.join('..', 'ss2010'),
version=mf_version,
load_only=['dis', 'bas6'],
check=False)
# read the contents of the DRN package
with open(inmod.drn.fn_path, 'r') as f:
lines = f.readlines()
# create pandas DataFrame
data =
for line in lines[3:]:
pieces = line.strip().split('#')
t = pieces[0].strip().split()
remark = pieces[-1]
if t[0] == '-1':
break
else:
data.append([int(t[0]),
int(t[1]),
int(t[2]),
float(t[3]),
float(t[4]),
'# ' + remark.strip()])
pak_df = pd.DataFrame(data,
columns=['k', 'i', 'j', 'alt_va', 'cond', 'remark'])
pak_df.loc[:, ['k', 'i', 'j']] -= 1
# specify data format
formats = OrderedDict([('k', ':>10d'.format),
('i', ':>10d'.format),
('j', ':>10d'.format),
('alt_va', ':>.2F'.format),
('cond', ':>15.6E'.format),
('remark', '>:50'.format)])
# create new stress period data: for numpy record array use DataFrame.to_records()
pak_spd = 0: pak_df[list(formats.keys())].to_records(index=False)
# attach DRN package to new model
pak = fpm.ModflowDrn(mf,
stress_period_data=pak_spd,
ipakcb=53,
options=['NOPRINT'],
filenames=os.path.join('..', 'ss2010', 'ss2010.'.format(pak_nam)),
dtype=pak_spd[0].dtype)
pak.write_file(check=False)
1
Hey Jason, I was able to read in my files in a similar way to yours too, but it would be cool to see something within flopy.
– rosskush
Nov 14 at 16:58
add a comment |
up vote
0
down vote
up vote
0
down vote
The only way I know to carry remarks over from an existing package is to open the file in read mode, create a pandas DataFrame with the column data, and build a new package out of it. Here is an example:
import os
import pandas as pd
import flopy.modflow as fpm
from collections import OrderedDict
pak_nam = 'drn'
mf_version = 'mfnwt'
# the model from which the DRN package will be copied
inmod = fpm.Modflow.load('10kTDS.nam',
model_ws=r'..10kTDS',
version=mf_version,
load_only=['drn'],
check=False)
# the model where the new DRN package will be attached
mf = fpm.Modflow.load('ss2010.nam',
model_ws=os.path.join('..', 'ss2010'),
version=mf_version,
load_only=['dis', 'bas6'],
check=False)
# read the contents of the DRN package
with open(inmod.drn.fn_path, 'r') as f:
lines = f.readlines()
# create pandas DataFrame
data =
for line in lines[3:]:
pieces = line.strip().split('#')
t = pieces[0].strip().split()
remark = pieces[-1]
if t[0] == '-1':
break
else:
data.append([int(t[0]),
int(t[1]),
int(t[2]),
float(t[3]),
float(t[4]),
'# ' + remark.strip()])
pak_df = pd.DataFrame(data,
columns=['k', 'i', 'j', 'alt_va', 'cond', 'remark'])
pak_df.loc[:, ['k', 'i', 'j']] -= 1
# specify data format
formats = OrderedDict([('k', ':>10d'.format),
('i', ':>10d'.format),
('j', ':>10d'.format),
('alt_va', ':>.2F'.format),
('cond', ':>15.6E'.format),
('remark', '>:50'.format)])
# create new stress period data: for numpy record array use DataFrame.to_records()
pak_spd = 0: pak_df[list(formats.keys())].to_records(index=False)
# attach DRN package to new model
pak = fpm.ModflowDrn(mf,
stress_period_data=pak_spd,
ipakcb=53,
options=['NOPRINT'],
filenames=os.path.join('..', 'ss2010', 'ss2010.'.format(pak_nam)),
dtype=pak_spd[0].dtype)
pak.write_file(check=False)
The only way I know to carry remarks over from an existing package is to open the file in read mode, create a pandas DataFrame with the column data, and build a new package out of it. Here is an example:
import os
import pandas as pd
import flopy.modflow as fpm
from collections import OrderedDict
pak_nam = 'drn'
mf_version = 'mfnwt'
# the model from which the DRN package will be copied
inmod = fpm.Modflow.load('10kTDS.nam',
model_ws=r'..10kTDS',
version=mf_version,
load_only=['drn'],
check=False)
# the model where the new DRN package will be attached
mf = fpm.Modflow.load('ss2010.nam',
model_ws=os.path.join('..', 'ss2010'),
version=mf_version,
load_only=['dis', 'bas6'],
check=False)
# read the contents of the DRN package
with open(inmod.drn.fn_path, 'r') as f:
lines = f.readlines()
# create pandas DataFrame
data =
for line in lines[3:]:
pieces = line.strip().split('#')
t = pieces[0].strip().split()
remark = pieces[-1]
if t[0] == '-1':
break
else:
data.append([int(t[0]),
int(t[1]),
int(t[2]),
float(t[3]),
float(t[4]),
'# ' + remark.strip()])
pak_df = pd.DataFrame(data,
columns=['k', 'i', 'j', 'alt_va', 'cond', 'remark'])
pak_df.loc[:, ['k', 'i', 'j']] -= 1
# specify data format
formats = OrderedDict([('k', ':>10d'.format),
('i', ':>10d'.format),
('j', ':>10d'.format),
('alt_va', ':>.2F'.format),
('cond', ':>15.6E'.format),
('remark', '>:50'.format)])
# create new stress period data: for numpy record array use DataFrame.to_records()
pak_spd = 0: pak_df[list(formats.keys())].to_records(index=False)
# attach DRN package to new model
pak = fpm.ModflowDrn(mf,
stress_period_data=pak_spd,
ipakcb=53,
options=['NOPRINT'],
filenames=os.path.join('..', 'ss2010', 'ss2010.'.format(pak_nam)),
dtype=pak_spd[0].dtype)
pak.write_file(check=False)
edited Nov 13 at 16:21
answered Nov 13 at 14:06
Jason
2871416
2871416
1
Hey Jason, I was able to read in my files in a similar way to yours too, but it would be cool to see something within flopy.
– rosskush
Nov 14 at 16:58
add a comment |
1
Hey Jason, I was able to read in my files in a similar way to yours too, but it would be cool to see something within flopy.
– rosskush
Nov 14 at 16:58
1
1
Hey Jason, I was able to read in my files in a similar way to yours too, but it would be cool to see something within flopy.
– rosskush
Nov 14 at 16:58
Hey Jason, I was able to read in my files in a similar way to yours too, but it would be cool to see something within flopy.
– rosskush
Nov 14 at 16:58
add a comment |
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