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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
 MNW2 package example
Step1:  Make an MNW2 package from scratch
Step2:  MNW2 information by node
(this could be prepared externally from well reconds and read in from a csv or excel file)
* this table has two multi-node wells, the first (well1) consisting of two nodes that are manually specified
(where the variable rw is specified by node)
* node that some variables that are constant for the whole well are also included (losstype, zpump, etc.)
Step3:  convert the DataFrame to a rec array for compatibility with flopy
Step4:  Stress period information
(could also be developed externally)
Step5:  Make ModflowMnw2 package object
note that extraneous columns in node_data and stress_period_data are ignored
if itmp is positive, it must equal the number of active wells being specified in stress_period_data, otherwise the package class will raise an error.
Step6:  empty node_data and stress_period_data tables can also be generated by the package class, and then filled
Step7:  Mnw objects
at the base of the flopy mnw2 module is the Mnw object class, which describes a single multi-node well.
A list or dict of Mnw objects can be used to build a package (using the example above)
Step8:  Note that Mnw object attributes for variables that vary by node are lists (e.g. rw above)
Each Mnw object has its own node_data and stress_period_data
Step9:  Instead of a dict keyed by stress period, Mnw.stress_period_data is a recarray with pumping data listed by stress period for that well
note that data for period 2, where itmp < 1, is shown (was copied from s.p. 1 during construction of the Mnw object)
Step10:  Build the same package using only the Mnw objects
Step11:  By default, the node_data and stress_period_data tables attached to the ModflowMnw2 package class are definitive
on writing of the package output (mnw2.write_file()), the Mnw objects are regenerated from the tables. This setting is controlled by the default argument use_tables=True. To write the package file using the Mnw objects (ignoring the tables), use mnw2.write_file(use_tables=False).
Step12:  Write an MNW2 package file and inspect the results
Step13:  Load some example MNW2 packages
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Python Code:
import sys
import os
import numpy as np
try:
    import pandas as pd
except:
    pass
import flopy
Explanation: MNW2 package example
End of explanation
m = flopy.modflow.Modflow('mnw2example', model_ws='temp')
dis = flopy.modflow.ModflowDis(nrow=5, ncol=5, nlay=3, nper=3, top=10, botm=0, model=m)
Explanation: Make an MNW2 package from scratch
End of explanation
node_data = pd.DataFrame([[1, 1, 9.5, 7.1, 'well1', 'skin', -1, 0, 0, 0, 1., 2., 5., 6.2],
                   [1, 1, 7.1, 5.1, 'well1', 'skin', -1, 0, 0, 0, 0.5, 2., 5., 6.2],
 [3, 3, 9.1, 3.7, 'well2', 'skin', -1, 0, 0, 0, 1., 2., 5., 4.1]], 
             columns=['i', 'j', 'ztop', 'zbotm', 'wellid', 'losstype', 'pumploc', 'qlimit', 'ppflag', 'pumpcap', 
                    'rw', 'rskin', 'kskin', 'zpump'])
node_data
Explanation: MNW2 information by node
(this could be prepared externally from well reconds and read in from a csv or excel file)
* this table has two multi-node wells, the first (well1) consisting of two nodes that are manually specified
(where the variable rw is specified by node)
* node that some variables that are constant for the whole well are also included (losstype, zpump, etc.)
End of explanation
node_data = node_data.to_records()
node_data
Explanation: convert the DataFrame to a rec array for compatibility with flopy
End of explanation
stress_period_data = pd.DataFrame([[0, 'well1', 0],
                          [1, 'well1', 100.0],
                          [0, 'well2', 0],
                          [1, 'well2', 1000.]], columns=['per', 'wellid', 'qdes'])
stress_period_data
pers = stress_period_data.groupby('per')
stress_period_data = {i: pers.get_group(i).to_records() for i in [0, 1]}
stress_period_data
Explanation: Stress period information
(could also be developed externally)
End of explanation
mnw2 = flopy.modflow.ModflowMnw2(model=m, mnwmax=2,
                 node_data=node_data, 
                 stress_period_data=stress_period_data, 
                 itmp=[2, 2, -1], # reuse second per pumping for last stress period
                 )
# "nodtot" is computed automatically
mnw2.nodtot
pd.DataFrame(mnw2.node_data)
pd.DataFrame(mnw2.stress_period_data[0])
pd.DataFrame(mnw2.stress_period_data[1])
tmp = flopy.modflow.ModflowMnw2(model=m,
                 itmp=[1, 1, -1], # reuse second per pumping for last stress period
                 )
Explanation: Make ModflowMnw2 package object
note that extraneous columns in node_data and stress_period_data are ignored
if itmp is positive, it must equal the number of active wells being specified in stress_period_data, otherwise the package class will raise an error.
End of explanation
node_data = tmp.get_empty_node_data(3)
node_data
Explanation: empty node_data and stress_period_data tables can also be generated by the package class, and then filled
End of explanation
mnw2.mnw
mnw2.mnw['well1'].__dict__
Explanation: Mnw objects
at the base of the flopy mnw2 module is the Mnw object class, which describes a single multi-node well.
A list or dict of Mnw objects can be used to build a package (using the example above):
flopy.modflow.ModflowMnw2(model=m, mnwmax=2,
                 mnw=&lt;dict or list of Mnw objects&gt;,
                 itmp=[1, 1, -1], # reuse second per pumping for last stress period
                 )
or if node_data and stress_period_data are supplied, the Mnw objects are created on initialization of the ModflowMnw2 class instance, and assigned to the .mnw attribute, as items in a dictionary keyed by wellid.
End of explanation
pd.DataFrame(mnw2.mnw['well1'].node_data)
Explanation: Note that Mnw object attributes for variables that vary by node are lists (e.g. rw above)
Each Mnw object has its own node_data and stress_period_data
End of explanation
pd.DataFrame(mnw2.mnw['well2'].stress_period_data)
Explanation: Instead of a dict keyed by stress period, Mnw.stress_period_data is a recarray with pumping data listed by stress period for that well
note that data for period 2, where itmp < 1, is shown (was copied from s.p. 1 during construction of the Mnw object)
End of explanation
mnw2fromobj = flopy.modflow.ModflowMnw2(model=m, mnwmax=2,
                 mnw=mnw2.mnw,
                 itmp=[2, 2, -1], # reuse second per pumping for last stress period
                 )
pd.DataFrame(mnw2fromobj.node_data)
pd.DataFrame(mnw2fromobj.stress_period_data[0])
pd.DataFrame(mnw2fromobj.stress_period_data[1])
Explanation: Build the same package using only the Mnw objects
End of explanation
per1 = flopy.modflow.ModflowMnw2.get_empty_stress_period_data(itmp=2)
per1
Explanation: By default, the node_data and stress_period_data tables attached to the ModflowMnw2 package class are definitive
on writing of the package output (mnw2.write_file()), the Mnw objects are regenerated from the tables. This setting is controlled by the default argument use_tables=True. To write the package file using the Mnw objects (ignoring the tables), use mnw2.write_file(use_tables=False).
End of explanation
mnw2.write_file(os.path.join('temp/test.mnw2'))
junk = [print(l.strip('\n')) for l in open('temp/test.mnw2').readlines()]
Explanation: Write an MNW2 package file and inspect the results
End of explanation
path = os.path.join('..', '..', 'examples', 'data', 'mf2005_test')
cpth = os.path.join('..', '..', 'autotest', 'temp')
m = flopy.modflow.Modflow('MNW2-Fig28', model_ws=cpth)
dis = flopy.modflow.ModflowDis.load(path + '/MNW2-Fig28.dis', m)
m.get_package_list()
mnw2pth = os.path.join(path, 'MNW2-Fig28.mnw2')
mnw2 = flopy.modflow.ModflowMnw2.load(mnw2pth, m)
pd.DataFrame(mnw2.node_data)
pd.DataFrame(mnw2.stress_period_data[0])
mnw2.mnw
pd.DataFrame(mnw2.mnw['Well-A'].stress_period_data)
path = os.path.join('..', '..', 'examples', 'data', 'mnw2_examples')
cpth = os.path.join('temp')
m = flopy.modflow.Modflow('br', model_ws=cpth)
mnw2 = flopy.modflow.ModflowMnw2.load(path + '/BadRiver_cal.mnw2', m)
df = pd.DataFrame(mnw2.node_data)
df.loc[:, df.sum(axis=0) != 0]
Explanation: Load some example MNW2 packages
End of explanation
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