Repository: ICB-DCM/pyABC

Issue:
Confidence intervals -> credible intervals
In visualization: Called it confidence intervals now, but in a Bayesian context should better call it credible intervals.

Discussion:
codecov-io: # [Codecov](https://codecov.io/gh/ICB-DCM/pyABC/pull/121?src=pr&el=h1) Report
> Merging [#121](https://codecov.io/gh/ICB-DCM/pyABC/pull/121?src=pr&el=desc) into [develop](https://codecov.io/gh/ICB-DCM/pyABC/commit/73979c9ae1e8793efea390e308837528a56087a2?src=pr&el=desc) will **increase** coverage by `0.26%`.
> The diff coverage is `86.42%`.

[![Impacted file tree graph](https://codecov.io/gh/ICB-DCM/pyABC/pull/121/graphs/tree.svg?width=650&token=GcyGdqSygr&height=150&src=pr)](https://codecov.io/gh/ICB-DCM/pyABC/pull/121?src=pr&el=tree)

```diff
@@             Coverage Diff             @@
##           develop     #121      +/-   ##
===========================================
+ Coverage    78.25%   78.51%   +0.26%     
===========================================
  Files           75       75              
  Lines         3518     3645     +127     
===========================================
+ Hits          2753     2862     +109     
- Misses         765      783      +18
```


| [Impacted Files](https://codecov.io/gh/ICB-DCM/pyABC/pull/121?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [pyabc/visualization/\_\_init\_\_.py](https://codecov.io/gh/ICB-DCM/pyABC/pull/121/diff?src=pr&el=tree#diff-cHlhYmMvdmlzdWFsaXphdGlvbi9fX2luaXRfXy5weQ==) | `100% <ø> (ø)` | :arrow_up: |
| [pyabc/visualization/confidence.py](https://codecov.io/gh/ICB-DCM/pyABC/pull/121/diff?src=pr&el=tree#diff-cHlhYmMvdmlzdWFsaXphdGlvbi9jb25maWRlbmNlLnB5) | `87.84% <86.42%> (-4.75%)` | :arrow_down: |

------

[Continue to review full report at Codecov](https://codecov.io/gh/ICB-DCM/pyABC/pull/121?src=pr&el=continue).
> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)
> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`
> Powered by [Codecov](https://codecov.io/gh/ICB-DCM/pyABC/pull/121?src=pr&el=footer). Last update [73979c9...be904d7](https://codecov.io/gh/ICB-DCM/pyABC/pull/121?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).


Patch:
diff --git a/doc/examples/parameter_inference.ipynb b/doc/examples/parameter_inference.ipynb
index 72289d0..a038813 100644
--- a/doc/examples/parameter_inference.ipynb
+++ b/doc/examples/parameter_inference.ipynb
@@ -182,13 +182,13 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "INFO:History:Start <ABCSMC(id=1, start_time=2019-06-11 12:31:11.690476, end_time=None)>\n"
+      "INFO:History:Start <ABCSMC(id=3, start_time=2019-06-11 13:28:03.778371, end_time=None)>\n"
      ]
     },
     {
      "data": {
       "text/plain": [
-       "1"
+       "3"
       ]
      },
      "execution_count": 6,
@@ -227,13 +227,13 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "INFO:Epsilon:initial epsilon is 1.3252371561760032\n",
-      "INFO:ABC:t:0 eps:1.3252371561760032\n",
-      "INFO:ABC:t:1 eps:0.7379714774065499\n",
-      "INFO:ABC:t:2 eps:0.32054781128385373\n",
-      "INFO:ABC:t:3 eps:0.15724428450868994\n",
-      "INFO:ABC:t:4 eps:0.0873526738664017\n",
-      "INFO:History:Done <ABCSMC(id=1, start_time=2019-06-11 12:31:11.690476, end_time=2019-06-11 12:31:16.096195)>\n"
+      "INFO:Epsilon:initial epsilon is 1.1988101315348554\n",
+      "INFO:ABC:t:0 eps:1.1988101315348554\n",
+      "INFO:ABC:t:1 eps:0.6844428829409226\n",
+      "INFO:ABC:t:2 eps:0.3363284142600154\n",
+      "INFO:ABC:t:3 eps:0.14866581335738419\n",
+      "INFO:ABC:t:4 eps:0.07328002773631426\n",
+      "INFO:History:Done <ABCSMC(id=3, start_time=2019-06-11 13:28:03.778371, end_time=2019-06-11 13:28:07.724173)>\n"
      ]
     }
    ],
@@ -289,7 +289,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -328,7 +328,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f77819ff7f0>"
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f049e9c6a58>"
       ]
      },
      "execution_count": 10,
@@ -337,7 +337,7 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -349,7 +349,7 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -361,7 +361,7 @@
     },
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -373,7 +373,7 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -387,8 +387,8 @@
    "source": [
     "pyabc.visualization.plot_sample_numbers(history)\n",
     "pyabc.visualization.plot_epsilons(history)\n",
-    "pyabc.visualization.plot_confidence_intervals(\n",
-    "    history, confidences=[0.95, 0.9, 0.5], ts=[0, 1, 2, 3, 4],\n",
+    "pyabc.visualization.plot_credible_intervals(\n",
+    "    history, levels=[0.95, 0.9, 0.5], ts=[0, 1, 2, 3, 4],\n",
     "    show_mean=True, show_kde_max_1d=True,\n",
     "    refval={'mean': 2.5})\n",
     "pyabc.visualization.plot_effective_sample_sizes(history)"
diff --git a/pyabc/visualization/__init__.py b/pyabc/visualization/__init__.py
index 2bfae5d..8a9f990 100644
--- a/pyabc/visualization/__init__.py
+++ b/pyabc/visualization/__init__.py
@@ -22,8 +22,8 @@ from .histogram import (
     plot_histogram_matrix,
     plot_histogram_matrix_lowlevel)
 from .confidence import (
-    plot_confidence_intervals,
-    plot_confidence_intervals_for_time)
+    plot_credible_intervals,
+    plot_credible_intervals_for_time)
 from .model_probabilities import (
     plot_model_probabilities)
 from .effective_sample_size import (
@@ -42,8 +42,8 @@ __all__ = [
     "plot_histogram_2d_lowlevel",
     "plot_histogram_matrix",
     "plot_histogram_matrix_lowlevel",
-    "plot_confidence_intervals",
-    "plot_confidence_intervals_for_time",
+    "plot_credible_intervals",
+    "plot_credible_intervals_for_time",
     "plot_model_probabilities",
     "plot_effective_sample_sizes",
 ]
diff --git a/pyabc/visualization/confidence.py b/pyabc/visualization/confidence.py
index 8f54f2d..1ca6de8 100644
--- a/pyabc/visualization/confidence.py
+++ b/pyabc/visualization/confidence.py
@@ -9,12 +9,12 @@ from ..transition import Transition, MultivariateNormalTransition
 from .util import to_lists_or_default
 
 
-def plot_confidence_intervals(
+def plot_credible_intervals(
         history: History,
         m: int = 0,
         ts: Union[List[int], int] = None,
         par_names: List = None,
-        confidences: List = None,
+        levels: List = None,
         show_mean: bool = False,
         show_kde_max: bool = False,
         show_kde_max_1d: bool = False,
@@ -23,7 +23,7 @@ def plot_confidence_intervals(
         kde: Transition = None,
         kde_1d: Transition = None):
     """
-    Plot confidence intervals over time.
+    Plot credible intervals over time.
 
     Parameters
     ----------
@@ -36,7 +36,7 @@ def plot_confidence_intervals(
         The time points to plot for.
     par_names: List[str], optional
         The parameter to plot for. If None, then all parameters are used.
-    confidences: List[float], optional (default = [0.95])
+    levels: List[float], optional (default = [0.95])
         Confidence intervals to compute.
     show_mean: bool, optional (default = False)
         Whether to show the mean apart from the median as well.
@@ -58,16 +58,16 @@ def plot_confidence_intervals(
     kde_1d: Transition, optional (default = MultivariateNormalTransition)
         The KDE to use for `show_kde_max_1d`.
     """
-    if confidences is None:
-        confidences = [0.95]
-    confidences = sorted(confidences)
+    if levels is None:
+        levels = [0.95]
+    levels = sorted(levels)
     if par_names is None:
         # extract all parameter names
         df, _ = history.get_distribution(m=m)
         par_names = list(df.columns.values)
     # dimensions
     n_par = len(par_names)
-    n_confidence = len(confidences)
+    n_confidence = len(levels)
     if ts is None:
         ts = list(range(0, history.max_t + 1))
     n_pop = len(ts)
@@ -116,16 +116,16 @@ def plot_confidence_intervals(
             if show_kde_max_1d:
                 _kde_max_1d_pnt = compute_kde_max(kde_1d, df[[par]], w)
                 kde_max_1d[i_par, i_t] = _kde_max_1d_pnt[par]
-            # confidences
-            for i_c, confidence in enumerate(confidences):
-                lb, ub = compute_confidence_interval(
+            # levels
+            for i_c, confidence in enumerate(levels):
+                lb, ub = compute_credible_interval(
                     vals, w, confidence)
                 cis[i_par, i_t, i_c] = lb
                 cis[i_par, i_t, -1 - i_c] = ub
 
     # plot
     for i_par, (par, ax) in enumerate(zip(par_names, arr_ax)):
-        for i_c, confidence in reversed(list(enumerate(confidences))):
+        for i_c, confidence in reversed(list(enumerate(levels))):
             ax.errorbar(
                 x=range(n_pop),
                 y=median[i_par].flatten(),
@@ -160,13 +160,13 @@ def plot_confidence_intervals(
     return arr_ax
 
 
-def plot_confidence_intervals_for_time(
+def plot_credible_intervals_for_time(
         histories: Union[List[History], History],
         labels: Union[List[str], str] = None,
         ms: Union[List[int], int] = None,
         ts: Union[List[int], int] = None,
         par_names: List[str] = None,
-        confidences: List[float] = None,
+        levels: List[float] = None,
         show_mean: bool = False,
         show_kde_max: bool = False,
         show_kde_max_1d: bool = False,
@@ -176,7 +176,7 @@ def plot_confidence_intervals_for_time(
         kde: Transition = None,
         kde_1d: Transition = None):
     """
-    Plot confidence intervals over time.
+    Plot credible intervals over time.
 
     Parameters
     ----------
@@ -194,10 +194,10 @@ def plot_confidence_intervals_for_time(
     par_names: List[str], optional
         The parameter to plot for. If None, then all parameters are used.
         Assumes all histories have these parameters.
-    confidences: List[float], optional (default = [0.95])
+    levels: List[float], optional (default = [0.95])
         Confidence intervals to compute.
     show_mean, show_kde_max, show_kde_max_1d: bool, optional (default = False)
-        As in `plot_confidence_intervals`.
+        As in `plot_credible_intervals`.
     size: tuple of float
         Size of the plot.
     refvals: Union[List[dict], dict], optional (default = None)
@@ -214,15 +214,15 @@ def plot_confidence_intervals_for_time(
         ms = [0] * n_run
     elif not isinstance(ms, list) or len(ms) == 1:
         ms = [ms] * n_run
-    if confidences is None:
-        confidences = [0.95]
-    confidences = sorted(confidences)
+    if levels is None:
+        levels = [0.95]
+    levels = sorted(levels)
     if par_names is None:
         # extract all parameter names
         df, _ = histories[0].get_distribution(m=ms[0])
         par_names = list(df.columns.values)
     n_par = len(par_names)
-    n_confidence = len(confidences)
+    n_confidence = len(levels)
     if ts is None:
         ts = [history.max_t for history in histories]
     if refvals is not None and not isinstance(refvals, list):
@@ -272,9 +272,9 @@ def plot_confidence_intervals_for_time(
             if show_kde_max_1d:
                 _kde_max_1d_pnt = compute_kde_max(kde_1d, df[[par]], w)
                 kde_max_1d[i_par, i_run] = _kde_max_1d_pnt[par]
-            # confidences
-            for i_c, confidence in enumerate(confidences):
-                lb, ub = compute_confidence_interval(
+            # levels
+            for i_c, confidence in enumerate(levels):
+                lb, ub = compute_credible_interval(
                     vals, w, confidence)
                 cis[i_par, i_run, i_c] = lb
                 cis[i_par, i_run, -1 - i_c] = ub
@@ -282,7 +282,7 @@ def plot_confidence_intervals_for_time(
     # plot
     for i_par, (par, ax) in enumerate(zip(par_names, arr_ax)):
         for i_run, h in enumerate(histories):
-            for i_c, confidence in reversed(list(enumerate(confidences))):
+            for i_c, confidence in reversed(list(enumerate(levels))):
                 y_err = np.array(
                     [median[i_par, i_run] - cis[i_par, i_run, i_c],
                      cis[i_par, i_run, -1 - i_c] - median[i_par, i_run]])
@@ -313,7 +313,7 @@ def plot_confidence_intervals_for_time(
         ax.set_xticks(range(n_run))
         ax.set_xticklabels(labels, rotation=rotation)
         leg_colors = [f'C{i_c}' for i_c in reversed(range(n_confidence))]
-        leg_labels = ['{:.2f}'.format(c) for c in reversed(confidences)]
+        leg_labels = ['{:.2f}'.format(c) for c in reversed(levels)]
         if show_mean:
             leg_colors.append(f'C{n_confidence}')
             leg_labels.append("Mean")
@@ -339,15 +339,15 @@ def plot_confidence_intervals_for_time(
     return arr_ax
 
 
-def compute_confidence_interval(vals, weights, confidence: float = 0.95):
+def compute_credible_interval(vals, weights, confidence: float = 0.95):
     """
-    Compute confidence interval to confidence level `confidence` for points
+    Compute credible interval to confidence level `confidence` for points
     `vals` associated to weights `weights`.
 
     Returns
     -------
     lb, ub: tuple of float
-        Lower and upper bound of the confidence interval.
+        Lower and upper bound of the credible interval.
     """
     if confidence <= 0.0 or confidence >= 1.0:
         raise ValueError(


Test patch:
diff --git a/test/visualization/test_visualization.py b/test/visualization/test_visualization.py
index 99cf057..b0a532f 100644
--- a/test/visualization/test_visualization.py
+++ b/test/visualization/test_visualization.py
@@ -75,12 +75,12 @@ def test_kdes():
     pyabc.visualization.plot_kde_matrix(df, w)
 
 
-def test_confidence_intervals():
-    pyabc.visualization.plot_confidence_intervals(histories[0])
-    pyabc.visualization.plot_confidence_intervals(
-        histories[0], confidences=[0.2, 0.5, 0.9])
-    pyabc.visualization.plot_confidence_intervals_for_time(
-        histories, confidences=[0.5, 0.99],
+def test_credible_intervals():
+    pyabc.visualization.plot_credible_intervals(histories[0])
+    pyabc.visualization.plot_credible_intervals(
+        histories[0], levels=[0.2, 0.5, 0.9])
+    pyabc.visualization.plot_credible_intervals_for_time(
+        histories, levels=[0.5, 0.99],
         show_kde_max_1d=True, show_kde_max=True, show_mean=True,
         refvals=p_true)