Merge pull request #65 from easyScience/plopp-plotting-more-strict-scipp

Bumped scipp to 23.08

EasyReflectometry/plot.py

@@ -1,14 +1,13 @@
 __author__ = 'github.com/arm61'
 
 import scipp as sc
-import ipympl
 import matplotlib.pyplot as plt
 from matplotlib.gridspec import GridSpec
 
 color_cycle = plt.rcParams['axes.prop_cycle'].by_key()['color']
 
 
-def plot(data: sc.Dataset) -> ipympl.backend_nbagg.Canvas:
+def plot(data: sc.Dataset):
     """
     A general plotting function for EasyReflectometry.
 
@@ -17,53 +16,57 @@ def plot(data: sc.Dataset) -> ipympl.backend_nbagg.Canvas:
     :returns: The plot canvas.
     """
     if len([i for i in list(data.keys()) if 'SLD' in i]) == 0:
+        plot_sld = False
         fig = plt.figure(figsize=(5, 3))
         gs = GridSpec(1, 1, figure=fig)
     else:
+        plot_sld = True
         fig = plt.figure(figsize=(5, 6))
         gs = GridSpec(2, 1, figure=fig)
         ax2 = fig.add_subplot(gs[1, 0])
     ax1 = fig.add_subplot(gs[0, 0])
     refl_nums = [k[3:] for k, v in data.coords.items() if 'Qz' == k[:2]]
-    for i, name in enumerate(refl_nums):
-        copy = data[f'R_{name}'].copy()
+    for i, refl_num in enumerate(refl_nums):
+        copy = data[f'R_{refl_num}'].copy()
         copy.data *= sc.scalar(10.**i, unit=copy.unit)
-        sc.plot(copy,
-                ax=ax1,
-                norm='log',
-                linestyle='',
-                marker='.',
-                color=color_cycle[i])
+        copy.coords[f'Qz_{refl_num}'].variances = None
+        sc.plot(
+            copy,
+            ax=ax1,
+            norm='log',
+            linestyle='',
+            marker='.',
+            color=color_cycle[i]
+        )
         try:
-            copy = data[f'R_{name}_model'].copy()
+            copy = data[f'R_{refl_num}_model'].copy()
             copy.data *= sc.scalar(10.**float(i))
-            sc.plot(copy,
-                    ax=ax1,
-                    norm='log',
-                    linestyle='--',
-                    color=color_cycle[i],
-                    marker='')
+            copy.coords[f'Qz_{refl_num}'].variances = None
+            sc.plot(
+                copy,
+                ax=ax1,
+                norm='log',
+                linestyle='--',
+                color=color_cycle[i],
+                marker=''
+            )
         except KeyError:
             pass
     ax1.autoscale(True)
     ax1.relim()
     ax1.autoscale_view()
 
-    for i, name in enumerate(refl_nums):
-        try:
-            copy = data[f'SLD_{name}'].copy()
+    if plot_sld:
+        for i, refl_num in enumerate(refl_nums):
+            copy = data[f'SLD_{refl_num}'].copy()
             copy.data += sc.scalar(10. * i, unit=copy.unit)
-            sc.plot(data[f'SLD_{name}'],
-                    ax=ax2,
-                    linestyle='-',
-                    color=color_cycle[i],
-                    marker='')
-        except KeyError:
-            pass
-    try:
+            sc.plot(
+                data[f'SLD_{refl_num}'],
+                ax=ax2,
+                linestyle='-',
+                color=color_cycle[i],
+                marker=''
+            )
         ax2.autoscale(True)
         ax2.relim()
         ax2.autoscale_view()
-    except UnboundLocalError:
-        pass
-    return fig.canvas

docs/monolayer.ipynb

@@ -12,13 +12,23 @@
     "First, we will import the relevant packages and functions."
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "e46c0e41",
+   "metadata": {},
+   "source": [
+    "First configure matplotlib to place figures in notebook and import needed modules"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "id": "619bb767-475a-408b-b576-552f0bc4f2a7",
    "metadata": {},
    "outputs": [],
    "source": [
+    "%matplotlib inline\n",
+    "\n",
     "import EasyReflectometry\n",
     "import refnx\n",
     "from EasyReflectometry.data import load\n",
@@ -441,7 +451,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.15"
+   "version": "3.11.5"
   }
  },
  "nbformat": 4,

docs/multi_contrast.ipynb

@@ -9,8 +9,15 @@
     "\n",
     "In the use of neutron reflectometry, it is common to use multiple isotopic contrasts of experimental data to analyse a system in a constrained fashion. \n",
     "That is to say, that we have data from multiple different species (where isotopic substitution has been used to produce data with different scattering length density) that shar ethe same structure. \n",
-    "In this tutorial we will look at how `EasyReflectometry` can be used to fit multiple contrasts of data from a [surfactant monolayer](./monolayer.html) system, if you haven't looked at the tutorial for a single contrast of surfactant monolayer data it is suggested that you as this tutorial will build on it.\n",
-    "First, as always, we import the relevant packages and print the version numbers."
+    "In this tutorial we will look at how `EasyReflectometry` can be used to fit multiple contrasts of data from a [surfactant monolayer](./monolayer.html) system, if you haven't looked at the tutorial for a single contrast of surfactant monolayer data it is suggested that you as this tutorial will build on it."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9e2929d2",
+   "metadata": {},
+   "source": [
+    "First configure matplotlib to place figures in notebook and import needed modules"
    ]
   },
   {
@@ -20,6 +27,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "%matplotlib inline\n",
+    "\n",
     "import EasyReflectometry\n",
     "import refnx\n",
     "from EasyReflectometry.data import load\n",
@@ -439,7 +448,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.15"
+   "version": "3.11.5"
   }
  },
  "nbformat": 4,

docs/repeating.ipynb

@@ -16,13 +16,23 @@
     "Before performing analysis, we should import the packages that we need."
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "f5d0bd58",
+   "metadata": {},
+   "source": [
+    "First configure matplotlib to place figures in notebook and import needed modules"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "id": "29d5d62d-af4a-416d-bbe2-1338d32b30f5",
    "metadata": {},
    "outputs": [],
    "source": [
+    "%matplotlib inline\n",
+    "\n",
     "import numpy as np\n",
     "import scipp as sc\n",
     "import EasyReflectometry\n",

docs/simple_fitting.ipynb

@@ -12,13 +12,23 @@
     "Before we start on any analysis, we will import the necessary packages and functions."
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "d0fea80b",
+   "metadata": {},
+   "source": [
+    "First configure matplotlib to place figures in notebook and import needed modules"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "id": "f026d35c-6a4a-4e9d-889c-d23ea6ee7adc",
    "metadata": {},
    "outputs": [],
    "source": [
+    "%matplotlib inline\n",
+    "\n",
     "import EasyReflectometry\n",
     "import refnx\n",
     "from EasyReflectometry.data import load\n",

docs/solvation.ipynb

@@ -15,13 +15,23 @@
     "Here, we will show how to use the `MaterialMixture` [type](./material_library.html#materialmixture) to perform this analysis. "
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "f404875e",
+   "metadata": {},
+   "source": [
+    "First configure matplotlib to place figures in notebook and import needed modules"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "id": "88c86e82-88dd-4c2d-ad99-826f409ec7b7",
    "metadata": {},
    "outputs": [],
    "source": [
+    "%matplotlib inline\n",
+    "\n",
     "import numpy as np\n",
     "import scipp as sc\n",
     "import EasyReflectometry\n",
@@ -333,7 +343,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.15"
+   "version": "3.11.5"
   }
  },
  "nbformat": 4,

pyproject.toml

@@ -34,20 +34,21 @@ dependencies = [
 
 [project.optional-dependencies]
 dev = [
-    "pytest>=5.2",
-    "pytest-cov>=3.0.0",
     "codecov>=2.1.11",
-    "yapf>=0.31.0",
-    "toml>=0.10",
-    "jupyter>=1.0.0",
-    "flake8>=6.0.0",
-    "jupyterlab",
     "coverage",
     "coveralls",
+    "flake8>=6.0.0",
     "ipykernel",
+    "jupyter>=1.0.0",
+    "jupyterlab",
     "nbsphinx",
+    "plopp",
+    "pytest>=5.2",
+    "pytest-cov>=3.0.0",
     "sphinx_book_theme",
-    "sphinx_autodoc_typehints"
+    "sphinx_autodoc_typehints",
+    "toml>=0.10",
+    "yapf>=0.31.0",
 ]
 
 [project.urls]