some prototypes

prototypes/c2cache.py

@@ -0,0 +1,20 @@
+from collections import deque
+from time import time
+
+
+class Cache:
+
+    def __init__(self, size=100):
+        self.times = deque(maxlen=size)
+        self.values  = deque(maxlen=size)
+
+    def append(self, value):
+        self.times.append(time())
+        self.values.append(value)
+
+
+
+cache = Cache()
+
+
+

prototypes/cabokeh1.py

@@ -0,0 +1,57 @@
+#!/usr/bin/env python
+
+from time import sleep, time
+from random import random
+import numpy as np
+from epics import PV
+from bokeh.plotting import curdoc, figure
+from bokeh.models import ColumnDataSource
+from bokeh.layouts import row
+
+
+data = {
+    "x": [],
+    "y": []
+}
+
+source = ColumnDataSource(data=data)
+histo = ColumnDataSource(dict(left=[], right=[], top=[]))
+
+fig1 = figure()
+fig1.step(x="x", y="y", source=source, mode="after")
+fig1.circle(x="x", y="y", source=source)
+
+fig2 = figure()
+fig2.quad(left="left", right="right", top="top", bottom=0, source=histo)
+
+pv = PV("MTEST:RAND0")
+
+cache = {
+    "x": [],
+    "y": []
+}
+
+def cb(value=None, **kwargs):
+    x = time()
+    y = value
+    cache["x"].append(x)
+    cache["y"].append(y)
+
+def update():
+    source.stream(cache, rollover=50)
+    cache["x"] = []
+    cache["y"] = []
+    data = source.data["y"]
+    counts, edges = np.histogram(data, bins="auto")
+    histo.data.update(left=edges[:-1], right=edges[1:], top=counts)
+
+
+
+pv.add_callback(cb)
+doc = curdoc()
+doc.add_periodic_callback(update, 1000)
+plt = row(fig1, fig2)
+doc.add_root(plt)
+
+
+

prototypes/cabokeh2.py

@@ -0,0 +1,93 @@
+#!/usr/bin/env python
+
+from time import sleep, time
+from random import random
+import numpy as np
+from epics import PV
+from bokeh.plotting import curdoc, figure
+from bokeh.models import ColumnDataSource
+from bokeh.layouts import row
+
+from c2cache import cache
+
+
+data = {
+    "x": [],
+    "y": []
+}
+
+source = ColumnDataSource(data=data)
+histo = ColumnDataSource(dict(left=[], right=[], top=[]))
+image = ColumnDataSource(dict(image=[np.random.random((1000, 1000))]))
+
+fig1 = figure()
+fig1.step(x="x", y="y", source=source, mode="after")
+fig1.circle(x="x", y="y", source=source)
+
+fig2 = figure()
+fig2.quad(left="left", right="right", top="top", bottom=0, source=histo)
+
+fig3 = figure()
+fig3.image(source=image, x=0, y=0, dw=1, dh=1, palette="Spectral11")
+
+pv = PV("MTEST:RAND0")
+
+pv_img    = PV("MTEST:CHAN-IMAGE:FPICTURE", auto_monitor=True)
+pv_height = PV("MTEST:CHAN-IMAGE:HEIGHT")
+pv_width  = PV("MTEST:CHAN-IMAGE:WIDTH")
+
+
+def cb(value=None, **kwargs):
+    cache.append(value)
+
+
+image_data = None
+
+def cb_img(value=None, **kwargs):
+    print(len(value))
+    global image_data
+    if value is None:
+        return
+    height = pv_height.get()
+    width = pv_width.get()
+    if height is None or value is None:
+        return
+    image_data = value
+    image_data.shape = (height, width)
+
+pv_img.add_callback(cb_img)
+
+
+def update():
+#    print(cache.values)
+    times = cache.times
+    values = cache.values
+    data = {
+        "x": times,
+        "y": values
+    }
+    source.data.update(data)
+
+    counts, edges = np.histogram(values, bins="auto")
+    histo.data.update(left=edges[:-1], right=edges[1:], top=counts)
+
+    if image_data is not None:
+#        print(image_data.shape)
+        image.data.update(image=[image_data])
+
+
+
+pv.add_callback(cb)
+doc = curdoc()
+doc.add_periodic_callback(update, 1000)
+
+plt = row(
+    fig1,
+    fig2,
+    fig3
+)
+
+doc.add_root(plt)
+
+
+

prototypes/stream-bokeh.py

@@ -0,0 +1,39 @@
+#!/usr/bin/env python
+
+from time import sleep
+from random import random
+from bokeh.plotting import curdoc, figure
+from bokeh.models import ColumnDataSource
+
+data = {
+    "x": [0, 1, 2, 3, 4],
+    "y": [6, 7, 2, 3, 5]
+}
+
+i = len(data["x"])
+
+source = ColumnDataSource(data=data)
+
+p = figure()
+p.line(x="x", y="y", source=source)
+
+
+def update():
+    global i
+    i += 1
+
+    new = {
+        "x": [i],
+        "y": [random()*10]
+    }
+
+    source.stream(new, rollover=50)
+
+
+
+doc = curdoc()
+doc.add_periodic_callback(update, 500)
+doc.add_root(p)
+
+
+

prototypes/stream-streamlit.py

@@ -0,0 +1,73 @@
+#!/usr/bin/env python
+
+from time import sleep, time
+import streamlit as st
+import altair as alt
+import numpy as np
+import pandas as pd
+
+
+st.title(__file__.rsplit("/")[-1])
+
+
+chart_data = pd.DataFrame(
+    np.random.randn(20, 3),
+    columns=['a', 'b', 'c'],
+    index=np.arange(10, 30)
+)
+
+ch1 = st.line_chart(chart_data)
+
+c = alt.Chart(chart_data.reset_index()).mark_line().encode(
+    x='index',
+    y='a',
+    tooltip="a"
+)
+
+ch2 = st.altair_chart(c)
+
+
+img_data = np.random.randn(2500, 2500)
+img_data -= img_data.min()
+img_data /= img_data.max()
+
+img = st.image(img_data)
+
+
+times = []
+last_time = time()
+
+for i in range(1000):
+    cd = pd.DataFrame(
+        np.random.randn(1, 3),
+        columns=['a', 'b', 'c'],
+        index=[chart_data.index.max()+1]
+    )
+
+    ch1.add_rows(cd)
+
+    chart_data = chart_data.append(cd)
+    chart_data = chart_data.iloc[1:]
+
+    c = alt.Chart(chart_data.reset_index()).mark_line().encode(
+        x='index',
+        y='a',
+        tooltip="a"
+    )
+
+    ch2.altair_chart(c)
+
+    img_data = np.random.randn(250, 250)
+    img_data -= img_data.min()
+    img_data /= img_data.max()
+    img.image(img_data)
+
+    current_time = time()
+    delta_t = current_time - last_time
+    times.append(delta_t)
+    last_time = current_time
+    print(delta_t, np.mean(times)) 
+
+    sleep(1)
+
+