{"action":"created","comment":{"url":"https://api.github.com/repos/astropy/astropy/pulls/comments/228654200","pull_request_review_id":168984970,"id":228654200,"node_id":"MDI0OlB1bGxSZXF1ZXN0UmV2aWV3Q29tbWVudDIyODY1NDIwMA==","diff_hunk":"@@ -0,0 +1,192 @@\n+# -*- coding: utf-8 -*-\n+# Licensed under a 3-clause BSD style license - see LICENSE.rst\n+\n+\"\"\"\n+Built-in distribution-creation functions.\n+\"\"\"\n+\n+from __future__ import (absolute_import, division, print_function,\n+                        unicode_literals)\n+\n+import numpy as np\n+\n+from ..units import UnitsError\n+from .core import Distribution\n+\n+__all__ = ['normal', 'poisson', 'uniform', 'uniform_center_width']\n+\n+\n+def normal(center, std=None, var=None, ivar=None, n_samples=1000,\n+           dcls=Distribution, **kwargs):\n+    \"\"\"\n+    Create a Gaussian/normal distribution.\n+\n+    Parameters\n+    ----------\n+    center : `~astropy.units.Quantity`\n+        The center of this distribution\n+    std : `~astropy.units.Quantity` or `None`\n+        The standard deviation/σ of this distribution. Shape must match and unit\n+        must be compatible with ``center``, or be `None` (if ``var`` or ``ivar``\n+        are set).\n+    var : `~astropy.units.Quantity` or `None`\n+        The variance of this distribution. Shape must match and unit must be\n+        compatible with ``center``, or be `None` (if ``std`` or ``ivar`` are set).\n+    ivar : `~astropy.units.Quantity` or `None`\n+        The inverse variance of this distribution. Shape must match and unit\n+        must be compatible with ``center``, or be `None` (if ``std`` or ``var``\n+        are set).\n+    n_samples : int\n+        The number of Monte Carlo samples to use with this distribution\n+    dcls : class\n+        The class to use to create this distribution.  Typically a\n+        `Distribution` subclass.\n+\n+    Remaining keywords are passed into the constructor of the ``dcls``\n+\n+    Returns\n+    -------\n+    distr : ``dcls``, usually `Distribution`\n+        The sampled Gaussian distribution.\n+    \"\"\"\n+    center = np.asanyarray(center)\n+    if var is not None:\n+        if std is None:\n+            std = np.asanyarray(var)**0.5\n+        else:\n+            raise ValueError('normal cannot take both std and var')\n+    if ivar is not None:\n+        if std is None:\n+            std = np.asanyarray(ivar)**-0.5\n+        else:\n+            raise ValueError('normal cannot take both ivar and '\n+                             'and std or var')\n+    if std is None:\n+        raise ValueError('normal requires one of std, var, or ivar')\n+    else:\n+        std = np.asanyarray(std)\n+\n+    randshape = np.broadcast(std, center).shape + (n_samples,)\n+    samples = center[..., np.newaxis] + np.random.randn(*randshape) * std[..., np.newaxis]\n+    distr = dcls(samples, **kwargs)\n+    distr.distr_std = std\n+    return distr\n+\n+\n+def poisson(center, n_samples=1000, dcls=Distribution, **kwargs):\n+    \"\"\"\n+    Create a Poisson distribution.\n+\n+    Parameters\n+    ----------\n+    center : `~astropy.units.Quantity`\n+        The center value of this distribution (i.e., λ).\n+    n_samples : int\n+        The number of Monte Carlo samples to use with this distribution\n+    dcls : class\n+        The class to use to create this distribution.  Typically a\n+        `Distribution` subclass.\n+\n+    Remaining keywords are passed into the constructor of the ``dcls``\n+\n+    Returns\n+    -------\n+    distr : ``dcls``, usually `Distribution`\n+        The sampled poisson distribution.\n+    \"\"\"\n+    # we convert to arrays because np.random.poisson has trouble with quantities\n+    has_unit = False\n+    if hasattr(center, 'unit'):","path":"astropy/uncertainty/builtin_distrs.py","position":99,"original_position":99,"commit_id":"82639bbea1786db2a55cf9cc60de29f4eed2c6f5","original_commit_id":"82639bbea1786db2a55cf9cc60de29f4eed2c6f5","user":{"login":"eteq","id":346587,"node_id":"MDQ6VXNlcjM0NjU4Nw==","avatar_url":"https://avatars1.githubusercontent.com/u/346587?v=4","gravatar_id":"","url":"https://api.github.com/users/eteq","html_url":"https://github.com/eteq","followers_url":"https://api.github.com/users/eteq/followers","following_url":"https://api.github.com/users/eteq/following{/other_user}","gists_url":"https://api.github.com/users/eteq/gists{/gist_id}","starred_url":"https://api.github.com/users/eteq/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/eteq/subscriptions","organizations_url":"https://api.github.com/users/eteq/orgs","repos_url":"https://api.github.com/users/eteq/repos","events_url":"https://api.github.com/users/eteq/events{/privacy}","received_events_url":"https://api.github.com/users/eteq/received_events","type":"User","site_admin":false},"body":"I see your point that the example shouldn't use it since kpc is not a counting unit... but I think `electron`/`count`/`adu` are important use cases, particularly given that one of the significant applications here would be for CCDs (via `ccdproc`/`nddata`), which is explicitly made to allow such flexible \"counting\" units that follow poisson statistics.\r\n\r\nSo I'd rather be *flexible* here at the outset so that we can experiment.  But perhaps a compromise is to have a warning that is raised for anything other than dimensionless or one of our builtin \"counting\" units?  I'll give that a try and we'll see how it looks.","created_at":"2018-10-26T20:18:29Z","updated_at":"2018-10-26T20:18:29Z","html_url":"https://github.com/astropy/astropy/pull/6945#discussion_r228654200","pull_request_url":"https://api.github.com/repos/astropy/astropy/pulls/6945","author_association":"MEMBER","_links":{"self":{"href":"https://api.github.com/repos/astropy/astropy/pulls/comments/228654200"},"html":{"href":"https://github.com/astropy/astropy/pull/6945#discussion_r228654200"},"pull_request":{"href":"https://api.github.com/repos/astropy/astropy/pulls/6945"}},"in_reply_to_id":228430277},"pull_request":{"url":"https://api.github.com/repos/astropy/astropy/pulls/6945","id":157176322,"node_id":"MDExOlB1bGxSZXF1ZXN0MTU3MTc2MzIy","html_url":"https://github.com/astropy/astropy/pull/6945","diff_url":"https://github.com/astropy/astropy/pull/6945.diff","patch_url":"https://github.com/astropy/astropy/pull/6945.patch","issue_url":"https://api.github.com/repos/astropy/astropy/issues/6945","number":6945,"state":"open","locked":false,"title":"Add a distribution object to hold quantities with uncertainties","user":{"login":"eteq","id":346587,"node_id":"MDQ6VXNlcjM0NjU4Nw==","avatar_url":"https://avatars1.githubusercontent.com/u/346587?v=4","gravatar_id":"","url":"https://api.github.com/users/eteq","html_url":"https://github.com/eteq","followers_url":"https://api.github.com/users/eteq/followers","following_url":"https://api.github.com/users/eteq/following{/other_user}","gists_url":"https://api.github.com/users/eteq/gists{/gist_id}","starred_url":"https://api.github.com/users/eteq/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/eteq/subscriptions","organizations_url":"https://api.github.com/users/eteq/orgs","repos_url":"https://api.github.com/users/eteq/repos","events_url":"https://api.github.com/users/eteq/events{/privacy}","received_events_url":"https://api.github.com/users/eteq/received_events","type":"User","site_admin":false},"body":"This is a WIP that represents combined work of myself, @astrofrog, @mhvk, and @adrn.  The core idea is to create an object that acts like a `Quantity`, *but* instead of being a single value, is a set of samples from a *distribution*.  Any arbitrary operations applied to that object then act on the set of samples, and the result is essentially \"automatic\" uncertainty propogation (although at the cost of n_samples times the memory usage).\r\n\r\nSome items left to do (*possibly* doable by 3.0, but I don't want to jinx it by setting the milestone just yet...):\r\n- [x]  Get all the tests passing (part of the point of creating this now is to ensure there aren't bigger problems on the various additional versions on CI)\r\n- [x]  Documentation on this feature (including statistical caveats - esp when \"not enough samples\" is a problem)\r\n- [x] Decide on the name: @adrn wants to call it `MarginalDistribution` instead of `Distribution` (I still favor `Distribution`, but @adrn  can weigh in).\r\n\r\nLonger-term additions (i.e. would be separate PRs)\r\n* A `JointDistribution` class that carries a set of distribution and allows e.g. easy corner plots, expectation values, etc (@adrn's idea)\r\n* Integrate this with @mhvk's work adapting standard uncertainty propagation following the normal approximation and automatic differentiation (#3715 I believe - that is *complementary* to this, not necessarily a replacement). ","created_at":"2017-12-08T07:01:39Z","updated_at":"2018-10-26T20:18:29Z","closed_at":null,"merged_at":null,"merge_commit_sha":"6c3c532c4018e34731885e85a3045f0c70080636","assignee":null,"assignees":[],"requested_reviewers":[],"requested_teams":[],"labels":[{"id":756910620,"node_id":"MDU6TGFiZWw3NTY5MTA2MjA=","url":"https://api.github.com/repos/astropy/astropy/labels/closed-by-bot","name":"closed-by-bot","color":"d93f0b","default":false},{"id":703513128,"node_id":"MDU6TGFiZWw3MDM1MTMxMjg=","url":"https://api.github.com/repos/astropy/astropy/labels/keep-open","name":"keep-open","color":"0e8a16","default":false},{"id":12456977,"node_id":"MDU6TGFiZWwxMjQ1Njk3Nw==","url":"https://api.github.com/repos/astropy/astropy/labels/units","name":"units","color":"c7def8","default":false},{"id":453709432,"node_id":"MDU6TGFiZWw0NTM3MDk0MzI=","url":"https://api.github.com/repos/astropy/astropy/labels/whatsnew-needed","name":"whatsnew-needed","color":"c2e0c6","default":false}],"milestone":{"url":"https://api.github.com/repos/astropy/astropy/milestones/52","html_url":"https://github.com/astropy/astropy/milestone/52","labels_url":"https://api.github.com/repos/astropy/astropy/milestones/52/labels","id":2929745,"node_id":"MDk6TWlsZXN0b25lMjkyOTc0NQ==","number":52,"title":"v3.1","description":"","creator":{"login":"eteq","id":346587,"node_id":"MDQ6VXNlcjM0NjU4Nw==","avatar_url":"https://avatars1.githubusercontent.com/u/346587?v=4","gravatar_id":"","url":"https://api.github.com/users/eteq","html_url":"https://github.com/eteq","followers_url":"https://api.github.com/users/eteq/followers","following_url":"https://api.github.com/users/eteq/following{/other_user}","gists_url":"https://api.github.com/users/eteq/gists{/gist_id}","starred_url":"https://api.github.com/users/eteq/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/eteq/subscriptions","organizations_url":"https://api.github.com/users/eteq/orgs","repos_url":"https://api.github.com/users/eteq/repos","events_url":"https://api.github.com/users/eteq/events{/privacy}","received_events_url":"https://api.github.com/users/eteq/received_events","type":"User","site_admin":false},"open_issues":64,"closed_issues":177,"state":"open","created_at":"2017-11-21T23:24:18Z","updated_at":"2018-10-26T20:00:31Z","due_on":"2018-10-26T07:00:00Z","closed_at":null},"commits_url":"https://api.github.com/repos/astropy/astropy/pulls/6945/commits","review_comments_url":"https://api.github.com/repos/astropy/astropy/pulls/6945/comments","review_comment_url":"https://api.github.com/repos/astropy/astropy/pulls/comments{/number}","comments_url":"https://api.github.com/repos/astropy/astropy/issues/6945/comments","statuses_url":"https://api.github.com/repos/astropy/astropy/statuses/82639bbea1786db2a55cf9cc60de29f4eed2c6f5","head":{"label":"eteq:distribution-structured-array","ref":"distribution-structured-array","sha":"82639bbea1786db2a55cf9cc60de29f4eed2c6f5","user":{"login":"eteq","id":346587,"node_id":"MDQ6VXNlcjM0NjU4Nw==","avatar_url":"https://avatars1.githubusercontent.com/u/346587?v=4","gravatar_id":"","url":"https://api.github.com/users/eteq","html_url":"https://github.com/eteq","followers_url":"https://api.github.com/users/eteq/followers","following_url":"https://api.github.com/users/eteq/following{/other_user}","gists_url":"https://api.github.com/users/eteq/gists{/gist_id}","starred_url":"https://api.github.com/users/eteq/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/eteq/subscriptions","organizations_url":"https://api.github.com/users/eteq/orgs","repos_url":"https://api.github.com/users/eteq/repos","events_url":"https://api.github.com/users/eteq/events{/privacy}","received_events_url":"https://api.github.com/users/eteq/received_events","type":"User","site_admin":false},"repo":{"id":2103466,"node_id":"MDEwOlJlcG9zaXRvcnkyMTAzNDY2","name":"astropy","full_name":"eteq/astropy","private":false,"owner":{"login":"eteq","id":346587,"node_id":"MDQ6VXNlcjM0NjU4Nw==","avatar_url":"https://avatars1.githubusercontent.com/u/346587?v=4","gravatar_id":"","url":"https://api.github.com/users/eteq","html_url":"https://github.com/eteq","followers_url":"https://api.github.com/users/eteq/followers","following_url":"https://api.github.com/users/eteq/following{/other_user}","gists_url":"https://api.github.com/users/eteq/gists{/gist_id}","starred_url":"https://api.github.com/users/eteq/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/eteq/subscriptions","organizations_url":"https://api.github.com/users/eteq/orgs","repos_url":"https://api.github.com/users/eteq/repos","events_url":"https://api.github.com/users/eteq/events{/privacy}","received_events_url":"https://api.github.com/users/eteq/received_events","type":"User","site_admin":false},"html_url":"https://github.com/eteq/astropy","description":"Main 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