From ffdd0c841e6c945194e6d0452262ad2ebbf4d59d Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Oriol=20Tint=C3=B3?= <oriol.tinto@lmu.de>
Date: Thu, 22 Jun 2023 15:40:39 +0200
Subject: [PATCH] Update streamlit example.
---
.../python_scripts/compress_dummy_dataset.py | 36 ++++++++
...ression_section.py => advanced_section.py} | 68 +--------------
examples/streamlit/component/basic_section.py | 73 ++++++++++++++++
examples/streamlit/component/data_source.py | 2 +
examples/streamlit/component/plotter.py | 83 +++++++++++++++++++
examples/streamlit/playground.py | 35 ++++----
6 files changed, 216 insertions(+), 81 deletions(-)
create mode 100644 examples/python_scripts/compress_dummy_dataset.py
rename examples/streamlit/component/{compression_section.py => advanced_section.py} (52%)
create mode 100644 examples/streamlit/component/basic_section.py
create mode 100644 examples/streamlit/component/plotter.py
diff --git a/examples/python_scripts/compress_dummy_dataset.py b/examples/python_scripts/compress_dummy_dataset.py
new file mode 100644
index 0000000..402aca3
--- /dev/null
+++ b/examples/python_scripts/compress_dummy_dataset.py
@@ -0,0 +1,36 @@
+import xarray
+from enstools.compression.analyzer.analyzer import analyze_dataset
+import enstools.compression.xr_accessor # noqa
+
+dataset_names = [
+ "air_temperature",
+ # "air_temperature_gradient",
+ # "basin_mask",
+ # "rasm",
+ # "ROMS_example",
+ # "tiny",
+ # "era5-2mt-2019-03-uk.grib",
+ # "eraint_uvz",
+ # "ersstv5"
+]
+
+
+def main():
+ results = {}
+ failed_datasets = []
+ for dataset_name in dataset_names:
+ try:
+ with xarray.tutorial.open_dataset(dataset_name) as dataset:
+ encoding, metrics = analyze_dataset(dataset=dataset)
+ results[dataset_name] = (encoding, metrics)
+ dataset.to_netcdf(f"reference_{dataset_name}.nc")
+ dataset.to_compressed_netcdf(f"compressed_{dataset_name}.nc", compression=encoding)
+ except ValueError:
+ failed_datasets.append(dataset_name)
+
+ print(results)
+ print(failed_datasets)
+
+
+if __name__ == "__main__":
+ main()
diff --git a/examples/streamlit/component/compression_section.py b/examples/streamlit/component/advanced_section.py
similarity index 52%
rename from examples/streamlit/component/compression_section.py
rename to examples/streamlit/component/advanced_section.py
index 1114e71..ba0fe5d 100644
--- a/examples/streamlit/component/compression_section.py
+++ b/examples/streamlit/component/advanced_section.py
@@ -23,12 +23,12 @@ default_parameters = {
}
-def compression_section(data, slice_selection):
+def advanced_section(data, slice_selection):
if data.dataset is not None:
# st.markdown("# Compression")
with st.expander("Compression Specifications"):
- specification_mode = st.radio(label="", options=["String", "Options"], horizontal=True)
+ specification_mode = st.radio(label="", options=["Options", "String"], horizontal=True)
# specification, options = st.tabs(["String", "Options"])
if specification_mode == "String":
compression_specification = st.text_input(label="Compression", value="lossy,sz,abs,1")
@@ -60,66 +60,4 @@ def compression_section(data, slice_selection):
st.markdown(
"Check [the compression specification format](https://enstools-encoding.readthedocs.io/en/latest/CompressionSpecificationFormat.html)")
if data.compressed_da is not None:
- st.markdown(f"**Compression Ratio**: {data.compressed_da.attrs['compression_ratio']}")
-
-
-def plot_compressed(data, slice_selection):
- col1, col2, *others = st.columns(2)
-
- new_slice = {}
-
- for key, values in slice_selection.items():
- if isinstance(values, tuple):
- start, stop = values
- if start != stop:
- new_slice[key] = slice(start, stop)
- else:
- new_slice[key] = start
- else:
- new_slice[key] = values
-
- slice_selection = new_slice
-
- if data.reference_da is not None:
- print(f"{slice_selection=}")
- slice_selection = {key: (value if key != "lat" else slice(value.stop, value.start)) for key, value in
- slice_selection.items()}
-
- only_slices = {key: value for key, value in slice_selection.items() if isinstance(value, slice)}
- non_slices = {key: value for key, value in slice_selection.items() if not isinstance(value, slice)}
-
- if only_slices:
- reference_slice = data.reference_da.sel(**only_slices)
- else:
- reference_slice = data.reference_da
-
- if non_slices:
- reference_slice = reference_slice.sel(**non_slices, method="nearest")
- print(reference_slice)
- try:
- reference_slice.plot()
- fig1 = plt.gcf()
- with col1:
- st.pyplot(fig1)
- except TypeError:
- pass
-
- if data.compressed_da is not None:
- plt.figure()
- if only_slices:
- compressed_slice = data.compressed_da.sel(**only_slices)
- else:
- compressed_slice = data.compressed_da
- if non_slices:
- compressed_slice = compressed_slice.sel(**non_slices, method="nearest")
-
- try:
- compressed_slice.plot()
- fig2 = plt.gcf()
- with col2:
- st.pyplot(fig2)
- except TypeError:
- pass
-
- else:
- st.text("Compress the data to show the plot!")
+ st.markdown(f"**Compression Ratio**: {data.compressed_da.attrs['compression_ratio']}")
\ No newline at end of file
diff --git a/examples/streamlit/component/basic_section.py b/examples/streamlit/component/basic_section.py
new file mode 100644
index 0000000..c0a44e3
--- /dev/null
+++ b/examples/streamlit/component/basic_section.py
@@ -0,0 +1,73 @@
+import matplotlib.pyplot as plt
+import numpy as np
+import streamlit as st
+import xarray
+
+import enstools.compression.xr_accessor # noqa
+from .data_source import DataContainer
+
+
+def get_compression_ratio(data_array: xarray.DataArray, relative_tolerance: float, mode: str) -> float:
+ what = data_array.compression(f"lossy,sz,{mode},{relative_tolerance}", in_place=False)
+ return float(what.attrs["compression_ratio"])
+
+
+def invert_function(function):
+ # Define its derivative
+ f_prime = function.deriv()
+
+ # Define the function for which we want to find the root
+ def func(x, y_val):
+ return function(x) - y_val
+
+ def newtons_method(y_val, epsilon=1e-7, max_iterations=100):
+ x = -2 # np.log10(0.01)
+ print(f"{y_val=}")
+ for _ in range(max_iterations):
+ x_new = x - func(x, y_val) / f_prime(x)
+ if abs(x - x_new) < epsilon:
+ return x_new
+ x = x_new
+ print(x_new)
+ return None
+
+ return newtons_method
+
+
+def create_parameter_from_compression_ratio(data: DataContainer, mode: str):
+ train_x = np.logspace(-12, -.5, 15)
+ train_y = [get_compression_ratio(data.reference_da, parameter, mode=mode) for parameter in train_x]
+
+ parameter_range = min(train_y), min(100., max(train_y))
+
+ x_log = np.log10(train_x)
+ y_log = np.log10(train_y)
+
+ coeff = np.polyfit(x_log, y_log, 10)
+
+ # Create a polynomial function from the coefficients
+ f = np.poly1d(coeff)
+
+ f_inverse = invert_function(f)
+
+ def function_to_return(compression_ratio: float) -> float:
+ return 10 ** f_inverse(np.log10(compression_ratio))
+
+ return parameter_range, function_to_return
+
+
+def basic_section(data: DataContainer, slice_selection):
+ mode = st.selectbox(label="Mode", options=["rel", "pw_rel"])
+ parameter_range, get_parameter = create_parameter_from_compression_ratio(data, mode=mode)
+
+ _min, _max = parameter_range
+ options = [_min + (_max - _min) * _x for _x in np.logspace(-2, 0)]
+ options = [f"{op:.2f}" for op in options]
+
+ compression_ratio = st.select_slider(label="Compression Ratio", options=options)
+ compression_ratio = float(compression_ratio)
+
+ parameter = get_parameter(compression_ratio)
+
+ with st.spinner():
+ data.compress(f"lossy,sz,rel,{parameter}")
diff --git a/examples/streamlit/component/data_source.py b/examples/streamlit/component/data_source.py
index 1d52908..279cbe1 100644
--- a/examples/streamlit/component/data_source.py
+++ b/examples/streamlit/component/data_source.py
@@ -38,6 +38,8 @@ class DataContainer:
def compress(self, compression):
self.compressed_da = self.reference_da.compression(compression)
+ def __hash__(self):
+ return hash(self.reference_da.name)
@st.cache_resource
def create_data():
diff --git a/examples/streamlit/component/plotter.py b/examples/streamlit/component/plotter.py
new file mode 100644
index 0000000..5e9ae39
--- /dev/null
+++ b/examples/streamlit/component/plotter.py
@@ -0,0 +1,83 @@
+import streamlit as st
+import matplotlib.pyplot as plt
+
+def plot_comparison(data, slice_selection):
+ col1, col2, col3, *others = st.columns(3)
+
+ new_slice = {}
+
+ for key, values in slice_selection.items():
+ if isinstance(values, tuple):
+ start, stop = values
+ if start != stop:
+ new_slice[key] = slice(start, stop)
+ else:
+ new_slice[key] = start
+ else:
+ new_slice[key] = values
+
+ slice_selection = new_slice
+
+ if data.reference_da is not None:
+ print(f"{slice_selection=}")
+ slice_selection = {key: (value if key != "lat" else slice(value.stop, value.start)) for key, value in
+ slice_selection.items()}
+
+ only_slices = {key: value for key, value in slice_selection.items() if isinstance(value, slice)}
+ non_slices = {key: value for key, value in slice_selection.items() if not isinstance(value, slice)}
+
+ if only_slices:
+ reference_slice = data.reference_da.sel(**only_slices)
+ else:
+ reference_slice = data.reference_da
+
+ if non_slices:
+ reference_slice = reference_slice.sel(**non_slices, method="nearest")
+ print(reference_slice)
+ try:
+ reference_slice.plot()
+ fig1 = plt.gcf()
+ with col1:
+ st.pyplot(fig1)
+ except TypeError:
+ pass
+
+ if data.compressed_da is not None:
+ plt.figure()
+ if only_slices:
+ compressed_slice = data.compressed_da.sel(**only_slices)
+ else:
+ compressed_slice = data.compressed_da
+ if non_slices:
+ compressed_slice = compressed_slice.sel(**non_slices, method="nearest")
+
+ try:
+ compressed_slice.plot()
+ fig2 = plt.gcf()
+ with col2:
+ st.pyplot(fig2)
+ except TypeError:
+ pass
+
+ diff = data.compressed_da - data.reference_da
+ plt.figure()
+ if only_slices:
+ diff_slice = diff.sel(**only_slices)
+ else:
+ diff_slice = data.compressed_da
+ if non_slices:
+ diff_slice = diff_slice.sel(**non_slices, method="nearest")
+
+ try:
+ diff_slice.plot()
+ fig3 = plt.gcf()
+ with col3:
+ st.pyplot(fig3)
+ except TypeError:
+ pass
+
+
+
+
+ else:
+ st.text("Compress the data to show the plot!")
diff --git a/examples/streamlit/playground.py b/examples/streamlit/playground.py
index 8106016..8603b62 100644
--- a/examples/streamlit/playground.py
+++ b/examples/streamlit/playground.py
@@ -1,41 +1,44 @@
-
import streamlit as st
from component.data_source import create_data, select_dataset, select_slice
-from component.compression_section import compression_section, plot_compressed
+from component.basic_section import basic_section
+from component.advanced_section import advanced_section
from component.analysis_section import analysis_section
+from component.plotter import plot_comparison
-
-st.set_page_config(layout="wide")
+st.set_page_config(layout="wide", initial_sidebar_state="collapsed")
data = create_data()
-def sidebar():
- ...
-
-
def setup_main_frame():
- st.title("Lossy Compression playground!")
- # with st.expander("Data Selection"):
+ st.title("Welcome to the :green[enstools-compression] playground!")
with st.sidebar:
select_dataset(data)
slice_selection = select_slice(data)
st.markdown("---")
- options = ["Compression", "Analysis"]
- compression, analysis = st.tabs(options)
+ options = ["Compression", "Advanced Compression", "Analysis"]
+ basic, advanced, analysis = st.tabs(options)
+
+ with basic:
+ basic_section(data=data, slice_selection=slice_selection)
+ with st.spinner():
+ try:
+ plot_comparison(data=data, slice_selection=slice_selection)
+ except TypeError as err:
+ st.warning(err)
- with compression:
- compression_section(data=data, slice_selection=slice_selection)
+ with advanced:
+ advanced_section(data=data, slice_selection=slice_selection)
with st.spinner():
try:
- plot_compressed(data=data, slice_selection=slice_selection)
+ plot_comparison(data=data, slice_selection=slice_selection)
except TypeError as err:
st.warning(err)
with analysis:
analysis_section(data=data, slice_selection=slice_selection)
-sidebar()
+
setup_main_frame()
--
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