packages

notebooks/Beta Distribution/Untitled.ipynb

+%% Cell type:code id:aff9571b-3bd8-41ab-8569-9ecc44ad1471 tags:
+
+``` python
+import pymc3
+```
+
+%%%% Output: error
+
+    ---------------------------------------------------------------------------
+    NoSectionError                            Traceback (most recent call last)
+    /opt/conda/lib/python3.9/site-packages/theano/configparser.py in fetch_val_for_key(self, key, delete_key)
+        237             try:
+    --> 238                 return self._theano_cfg.get(section, option)
+        239             except InterpolationError:
+    /opt/conda/lib/python3.9/configparser.py in get(self, section, option, raw, vars, fallback)
+        780         try:
+    --> 781             d = self._unify_values(section, vars)
+        782         except NoSectionError:
+    /opt/conda/lib/python3.9/configparser.py in _unify_values(self, section, vars)
+       1151             if section != self.default_section:
+    -> 1152                 raise NoSectionError(section) from None
+       1153         # Update with the entry specific variables
+    NoSectionError: No section: 'blas'
+
+During handling of the above exception, another exception occurred:
+    KeyError                                  Traceback (most recent call last)
+    /opt/conda/lib/python3.9/site-packages/theano/configparser.py in __get__(self, cls, type_, delete_key)
+        353             try:
+    --> 354                 val_str = cls.fetch_val_for_key(self.name, delete_key=delete_key)
+        355                 self.is_default = False
+    /opt/conda/lib/python3.9/site-packages/theano/configparser.py in fetch_val_for_key(self, key, delete_key)
+        241         except (NoOptionError, NoSectionError):
+    --> 242             raise KeyError(key)
+        243
+    KeyError: 'blas__ldflags'
+
+During handling of the above exception, another exception occurred:
+    AttributeError                            Traceback (most recent call last)
+    /tmp/ipykernel_677/1179053686.py in <module>
+    ----> 1 import pymc3
+
+    /opt/conda/lib/python3.9/site-packages/pymc3/__init__.py in <module>
+         21
+         22 import semver
+    ---> 23 import theano
+         24
+         25 _log = logging.getLogger("pymc3")
+    /opt/conda/lib/python3.9/site-packages/theano/__init__.py in <module>
+         81 __api_version__ = 1
+         82
+    ---> 83 from theano import scalar, tensor
+         84 from theano.compile import (
+         85     In,
+    /opt/conda/lib/python3.9/site-packages/theano/tensor/__init__.py in <module>
+         18     verify_grad,
+         19 )
+    ---> 20 from theano.tensor import nnet  # used for softmax, sigmoid, etc.
+         21 from theano.tensor import sharedvar  # adds shared-variable constructors
+         22 from theano.tensor import (
+    /opt/conda/lib/python3.9/site-packages/theano/tensor/nnet/__init__.py in <module>
+          1 import warnings
+          2
+    ----> 3 from . import opt
+          4 from .abstract_conv import conv2d as abstract_conv2d
+          5 from .abstract_conv import conv2d_grad_wrt_inputs, conv3d, separable_conv2d
+    /opt/conda/lib/python3.9/site-packages/theano/tensor/nnet/opt.py in <module>
+         30
+         31 # Cpu implementation
+    ---> 32 from theano.tensor.nnet.conv import ConvOp, conv2d
+         33 from theano.tensor.nnet.corr import CorrMM, CorrMM_gradInputs, CorrMM_gradWeights
+         34 from theano.tensor.nnet.corr3d import Corr3dMM, Corr3dMMGradInputs, Corr3dMMGradWeights
+    /opt/conda/lib/python3.9/site-packages/theano/tensor/nnet/conv.py in <module>
+         18 from theano.graph.basic import Apply
+         19 from theano.graph.op import OpenMPOp
+    ---> 20 from theano.tensor import blas
+         21 from theano.tensor.basic import (
+         22     NotScalarConstantError,
+    /opt/conda/lib/python3.9/site-packages/theano/tensor/blas.py in <module>
+        161 from theano.scalar import bool as bool_t
+        162 from theano.tensor import basic as tt
+    --> 163 from theano.tensor.blas_headers import blas_header_text, blas_header_version
+        164 from theano.tensor.opt import in2out, local_dimshuffle_lift
+        165 from theano.tensor.type import values_eq_approx_remove_inf_nan
+    /opt/conda/lib/python3.9/site-packages/theano/tensor/blas_headers.py in <module>
+       1014
+       1015
+    -> 1016 if not config.blas__ldflags:
+       1017     _logger.warning("Using NumPy C-API based implementation for BLAS functions.")
+       1018
+    /opt/conda/lib/python3.9/site-packages/theano/configparser.py in __get__(self, cls, type_, delete_key)
+        356             except KeyError:
+        357                 if callable(self.default):
+    --> 358                     val_str = self.default()
+        359                 else:
+        360                     val_str = self.default
+    /opt/conda/lib/python3.9/site-packages/theano/link/c/cmodule.py in default_blas_ldflags()
+       2619             # If the old private interface is available use it as it
+       2620             # don't print information to the user.
+    -> 2621             blas_info = numpy.distutils.__config__.blas_opt_info
+       2622         else:
+       2623             # We do this import only here, as in some setup, if we
+    AttributeError: module 'numpy.distutils.__config__' has no attribute 'blas_opt_info'

notebooks/Beta Distribution/hdi.ipynb

 %% Cell type:markdown id: tags:
 
 # Bestimmung 95%-HDI für die Betaverteilung
 
 Die folgende Prozedur definiert, das HDI für die Beta-Verteilung:
 
 %% Cell type:code id: tags:
 
 ``` python
 from scipy.stats import beta
 import numpy as np
 
 def hdi(a,b, prob = 0.95):
     k = 0
     x = np.linspace(0,1,1000)
     y = beta.pdf(x,a,b)
     while True:
        k = k+0.0001
        if np.sum(y[y > k])/np.size(x) < prob:
         break
     return x[np.argwhere(y > k)][0] ,x[np.argwhere(y > k)][np.argwhere(y > k).size-1]
 ```
 
 %% Cell type:markdown id: tags:
 
 In hdi(...) müssen nur noch die Parameter $a$ und $b$ eingegeben werden. Wenn die Prozentzahl noch geändert soll, fügen Sie ein zusätzliches prob=... ein. prob=0.5 würde dann bedeuten, dass 50% der glaubwürdigsten Parameter im HDI enthalten sind.
 
 %% Cell type:code id: tags:
 
 ``` python
 hdi(5,5)
 ```
 
 %%%% Output: execute_result
 
-    (array([0.21201212]), array([0.78798788]))
+    (array([0.21221221]), array([0.78778779]))

requirements.txt

@@ -9,7 +9,6 @@ pillow==8.3.2
 scikit-learn==1.0
 seaborn==0.11.2
 selenium==3.141.0
-tensorflow==2.6.0
 vega_datasets==0.9.0
 arviz==0.11.4
 pymc3==3.11.4