86
86
-----
87
87
88
88
.. currentmodule :: pymc3.plots
89
- :members:
90
89
91
90
.. automodule :: pymc3.plots
92
91
:members:
95
94
-----
96
95
97
96
.. currentmodule :: pymc3.stats
98
- :members:
99
97
100
98
.. automodule :: pymc3.stats
101
99
:members:
@@ -104,7 +102,6 @@ Diagnostics
104
102
-----------
105
103
106
104
.. currentmodule :: pymc3.diagnostics
107
- :members:
108
105
109
106
.. automodule :: pymc3.diagnostics
110
107
:members:
@@ -117,8 +114,7 @@ Inference
117
114
Sampling
118
115
^^^^^^^^
119
116
120
- .. currentomdule :: pymc3.sampling
121
- :members:
117
+ .. currentmodule :: pymc3.sampling
122
118
123
119
.. automodule :: pymc3.sampling
124
120
:members:
131
127
""""
132
128
133
129
.. currentmodule :: pymc3.step_methods.nuts
134
- :members:
135
130
136
131
.. automodule :: pymc3.step_methods.nuts
137
132
:members:
@@ -140,7 +135,6 @@ Metropolis
140
135
""""""""""
141
136
142
137
.. currentmodule :: pymc3.step_methods.metropolis
143
- :members:
144
138
145
139
.. automodule :: pymc3.step_methods.metropolis
146
140
:members:
@@ -149,7 +143,6 @@ Slice
149
143
"""""
150
144
151
145
.. currentmodule :: pymc3.step_methods.slicer
152
- :members:
153
146
154
147
.. automodule :: pymc3.step_methods.slicer
155
148
:members:
@@ -158,7 +151,6 @@ Hamiltonian Monte Carlo
158
151
"""""""""""""""""""""""
159
152
160
153
.. currentmodule :: pymc3.step_methods.hmc
161
- :members:
162
154
163
155
.. automodule :: pymc3.step_methods.hmc
164
156
:members:
171
163
""""
172
164
173
165
.. currentmodule :: pymc3.variational.advi
174
- :members:
175
166
176
167
.. automodule :: pymc3.variational.advi
177
168
:members:
@@ -180,7 +171,6 @@ ADVI minibatch
180
171
""""""""""""""
181
172
182
173
.. currentmodule :: pymc3.variational.advi_minibatch
183
- :members:
184
174
185
175
.. automodule :: pymc3.variational.advi_minibatch
186
176
:members:
@@ -189,7 +179,6 @@ Backends
189
179
--------
190
180
191
181
.. currentmodule :: pymc3.backends
192
- :members:
193
182
194
183
.. automodule :: pymc3.backends
195
184
:members:
@@ -198,7 +187,6 @@ ndarray
198
187
^^^^^^^
199
188
200
189
.. currentmodule :: pymc3.backends.ndarray
201
- :members:
202
190
203
191
.. automodule :: pymc3.backends.ndarray
204
192
:members:
@@ -207,7 +195,6 @@ sqlite
207
195
^^^^^^
208
196
209
197
.. currentmodule :: pymc3.backends.sqlite
210
- :members:
211
198
212
199
.. automodule :: pymc3.backends.sqlite
213
200
:members:
216
203
^^^^
217
204
218
205
.. currentmodule :: pymc3.backends.text
219
- :members:
220
206
221
207
.. automodule :: pymc3.backends.text
222
208
:members:
@@ -225,22 +211,78 @@ tracetab
225
211
^^^^^^^^
226
212
227
213
.. currentmodule :: pymc3.backends.tracetab
228
- :members:
229
214
230
215
.. automodule :: pymc3.backends.tracetab
231
216
:members:
232
217
233
218
234
-
235
-
236
-
237
-
238
219
GLM
239
220
---
240
221
241
222
.. currentmodule :: pymc3.glm.glm
242
- :members:
243
223
244
224
.. automodule :: pymc3.glm.glm
245
225
:members:
246
226
227
+ Math
228
+ ----
229
+
230
+ This submodule contains various mathematical functions. Most of them
231
+ are imported directly from theano.tensor (see there for more
232
+ details). Doing any kind of math with PyMC3 random variables, or
233
+ defining custom likelihoods or priors requires you to use these theano
234
+ expressions rather than NumPy or Python code.
235
+
236
+ .. currentmodule :: pymc3.math
237
+ .. autosummary ::
238
+ dot
239
+ constant
240
+ flatten
241
+ zeros_like
242
+ ones_like
243
+ stack
244
+ concatenate
245
+ sum
246
+ prod
247
+ lt
248
+ gt
249
+ le
250
+ ge
251
+ eq
252
+ neq
253
+ switch
254
+ clip
255
+ where
256
+ and _
257
+ or _
258
+ abs _
259
+ exp
260
+ log
261
+ cos
262
+ sin
263
+ tan
264
+ cosh
265
+ sinh
266
+ tanh
267
+ sqr
268
+ sqrt
269
+ erf
270
+ erfinv
271
+ dot
272
+ maximum
273
+ minimum
274
+ sgn
275
+ ceil
276
+ floor
277
+ det
278
+ matrix_inverse
279
+ extract_diag
280
+ matrix_dot
281
+ trace
282
+ sigmoid
283
+ logsumexp
284
+ invlogit
285
+ logit
286
+
287
+ .. automodule :: pymc3.math
288
+ :members:
0 commit comments