updated doc

README.md

@@ -22,13 +22,6 @@ You can install the latest version with the following command:
 
     pip install anaflow
 
-It is highly recomended to install the scipy-scikit `umfpack` to get a solver
-for sparse linear systems:
-
-    pip install scikit-umfpack
-
-Have a look at: https://github.com/scikit-umfpack/scikit-umfpack
-
 
 ## Documentation for AnaFlow
 
@@ -49,7 +42,7 @@ from anaflow import theis
 time = [10, 100, 1000]
 rad = np.geomspace(0.1, 10)
 
-head = theis(rad=rad, time=time, T=1e-4, S=1e-4, Qw=-1e-4)
+head = theis(time=time, rad=rad, T=1e-4, S=1e-4, Qw=-1e-4)
 
 for i, step in enumerate(time):
     plt.plot(rad, head[i], label="Theis(t={})".format(step))
@@ -74,6 +67,8 @@ anaflow.ext_thiem2D  # extended Thiem solution in 2D
 anaflow.ext_theis2D  # extended Theis solution in 2D
 anaflow.ext_thiem3D  # extended Thiem solution in 3D
 anaflow.ext_theis3D  # extended Theis solution in 3D
+anaflow.grf_model    # "General Radial Flow" Model
+anaflow.grf_dist     # extended "General Radial Flow" Model on disks
 ```
 
 
@@ -101,7 +96,7 @@ You can contact us via <info@geostat-framework.org>.
 
 ## License
 
-[GPL][gpl_link] © 2018-2019
+[GPL][gpl_link] © 2019
 
 [gpl_link]: https://github.com/GeoStat-Framework/AnaFlow/blob/master/LICENSE
 [ogs5_link]: https://www.opengeosys.org/ogs-5/

docs/source/index.rst

@@ -22,16 +22,6 @@ Python and pip running.
     pip install anaflow
 
 
-It is highly recomended to install the scipy-scikit `umfpack` to get a solver
-for sparse linear systems:
-
-.. code-block:: none
-
-    pip install scikit-umfpack
-
-Have a look at: https://github.com/scikit-umfpack/scikit-umfpack
-
-
 Provided Functions
 ==================
 
@@ -62,8 +52,8 @@ inverse laplace-transformation of a given function
 Requirements
 ============
 
-- `NumPy >= 1.10.0 <https://www.numpy.org>`_
-- `SciPy >= 0.19.0 <https://www.scipy.org/>`_
+- `NumPy >= 1.13.0 <https://www.numpy.org>`_
+- `SciPy >= 0.19.1 <https://www.scipy.org/>`_
 
 
 License

docs/source/tutorial_01_call.rst

@@ -15,7 +15,7 @@ different time-steps.
     time = [10, 100, 1000]
     rad = np.geomspace(0.1, 10)
 
-    head = theis(rad=rad, time=time, T=1e-4, S=1e-4, Qw=-1e-4)
+    head = theis(time=time, rad=rad, T=1e-4, S=1e-4, Qw=-1e-4)
 
     for i, step in enumerate(time):
         plt.plot(rad, head[i], label="Theis(t={})".format(step))

docs/source/tutorial_02_extended_theis.rst

@@ -19,15 +19,15 @@ transmissivity.
     time = [10, 600, 36000]      # 10s, 10min, 10h
     rad = np.geomspace(0.05, 4)  # radius from the pumping well in [0, 4]
     var = 0.5                    # variance of the log-transmissivity
-    corr = 10.0                  # correlation length of the transmissivity
+    corr = 10.0                  # correlation length of the log-transmissivity
     TG = 1e-4                    # the geometric mean of the transmissivity
     TH = TG*np.exp(-var/2.0)     # the harmonic mean of the transmissivity
     S = 1e-4                     # storativity
     Qw = -1e-4                   # pumping rate
 
-    head_TG = theis(rad=rad, time=time, T=TG, S=S, Qw=Qw)
-    head_TH = theis(rad=rad, time=time, T=TH, S=S, Qw=Qw)
-    head_ef = ext_theis2D(rad=rad, time=time, TG=TG, sig2=var, corr=corr, S=S, Qw=Qw)
+    head_TG = theis(time=time, rad=rad, T=TG, S=S, Qw=Qw)
+    head_TH = theis(time=time, rad=rad, T=TH, S=S, Qw=Qw)
+    head_ef = ext_theis2D(time=time, rad=rad, TG=TG, sig2=var, corr=corr, S=S, Qw=Qw)
 
     for i, step in enumerate(time):
         if i == 0:

examples/01_call_theis.py

@@ -7,7 +7,7 @@
 time = [10, 100, 1000]
 rad = np.geomspace(0.1, 10)
 
-head = theis(rad=rad, time=time, T=1e-4, S=1e-4, Qw=-1e-4)
+head = theis(time=time, rad=rad, T=1e-4, S=1e-4, Qw=-1e-4)
 
 for i, step in enumerate(time):
     plt.plot(rad, head[i], label="Theis(t={})".format(step))

examples/02_call_ext_theis.py

@@ -6,16 +6,16 @@
 
 time = [10, 600, 36000]      # 10s, 10min, 10h
 rad = np.geomspace(0.05, 4)  # radius from the pumping well in [0, 4]
-var = 0.5                    # variance of the transmissivity
-corr = 10.0                  # correlation length of the transmissivity
+var = 0.5                    # variance of the log-transmissivity
+corr = 10.0                  # correlation length of the log-transmissivity
 TG = 1e-4                    # the geometric mean of the transmissivity
 TH = TG*np.exp(-var/2.0)     # the harmonic mean of the transmissivity
 S = 1e-4                     # storativity
 Qw = -1e-4                   # pumping rate
 
-head_TG = theis(rad=rad, time=time, T=TG, S=S, Qw=Qw)
-head_TH = theis(rad=rad, time=time, T=TH, S=S, Qw=Qw)
-head_ef = ext_theis2D(rad=rad, time=time, TG=TG, sig2=var, corr=corr, S=S, Qw=Qw)
+head_TG = theis(time=time, rad=rad, T=TG, S=S, Qw=Qw)
+head_TH = theis(time=time, rad=rad, T=TH, S=S, Qw=Qw)
+head_ef = ext_theis2D(time=time, rad=rad, TG=TG, sig2=var, corr=corr, S=S, Qw=Qw)
 
 for i, step in enumerate(time):
     if i == 0:

examples/03_call_ext_theis3d.py

@@ -7,19 +7,19 @@
 
 time = [10, 600, 36000]                 # 10s, 10min, 10h
 rad = np.geomspace(0.05, 4)             # radial distance from the pumping well in [0, 4]
-var = 0.5                               # variance of the transmissivity
-corr = 10.0                             # correlation length of the conductivity
-e = 0.75                                # anisotropy ratio of the conductivity
+var = 0.5                               # variance of the log-conductivity
+corr = 10.0                             # correlation length of the log-conductivity
+e = 0.75                                # anisotropy ratio of the log-conductivity
 KG = 1e-4                               # the geometric mean of the conductivity
 Kefu = KG*np.exp(var*(0.5 - aniso(e)))  # the effective conductivity for uniform flow
 KH = KG*np.exp(-var/2.0)                # the harmonic mean of the conductivity
 S = 1e-4                                # storage
 Qw = -1e-4                              # pumping rate
 L = 1.0                                 # vertical extend of the aquifer
 
-head_Kefu = theis(rad=rad, time=time, T=Kefu*L, S=S, Qw=Qw)
-head_KH = theis(rad=rad, time=time, T=KH*L, S=S, Qw=Qw)
-head_ef = ext_theis3D(rad=rad, time=time, KG=KG, sig2=var, corr=corr, e=e, S=S, Qw=Qw, L=1)
+head_Kefu = theis(time=time, rad=rad, T=Kefu*L, S=S, Qw=Qw)
+head_KH = theis(time=time, rad=rad, T=KH*L, S=S, Qw=Qw)
+head_ef = ext_theis3D(time=time, rad=rad, KG=KG, sig2=var, corr=corr, e=e, S=S, Qw=Qw, L=1)
 
 for i, step in enumerate(time):
     if i == 0: